{ "query": "Summarize context", "namespace": "9b7a0d3b-f149-4977-879c-cf22ea8d011f", "messages": [ { "role": "assistant", "content": "Hallo lance+flt@digirift.com,\n\nIch bin Simon, dein KI-Chatbot, der mit dem gro\u00dfen Sprachmodell gemini-1.5-flash arbeitet, um all deine Fragen pr\u00e4zise und umfassend zu beantworten. \n\nBasierend auf den Dokumenten, die du mir zur Verf\u00fcgung gestellt hast, k\u00f6nnen wir \u00fcber verschiedene Themen sprechen. Hier sind ein paar Vorschl\u00e4ge:\n\n* \u2699\ufe0f **Automatisierung in der Produktion:** Wie kann die Automatisierung bei Skoda SSP Getriebegeh\u00e4use (GGH) die Effizienz steigern?\n* \ud83d\udcca **Maschinenf\u00e4higkeitsbewertung:** Welche Methoden gibt es, um die F\u00e4higkeiten von Maschinen in der Volkswagen AG zu bewerten?\n* \ud83d\udd0c **Siemens Powertrain L\u00f6sungen:** Welche Vorteile bieten Siemens Powertrain L\u00f6sungen f\u00fcr Volkswagen Group Components?\n* \ud83d\udcd1 **Standards und Komponenten:** Welche Standards und Komponenten sind f\u00fcr die Erneuerung der Produktionsanlagen im PKG-Betrieb von \u0160koda Auto a.s. relevant?\n* \ud83d\udd27 **Wartung und Inspektion von Motoren:** Welche Informationen sind f\u00fcr die Wartung und Inspektion von Motoren 026 und 028 wichtig?\n\nWas m\u00f6chtest du dir aus dieser Liste genauer ansehen? \n" }, { "role": "user", "content": "Summarize context" }, { "role": "assistant", "content": "" } ], "stream": true, "language_level": "", "chat_channel": ":4049:1726736324157", "language": "German", "tone": "neutral", "writing_style": "standard", "model": "gemini-1.5-flash", "knowledgebase": "ki-dev-large", "seed": 1029, "client_id": 1726736324157, "all_context": true, "follow_up_for": null, "knowledgebase_files_count": 35, "override_command": null, "disable_clarity_check": false, "custom_primer": "", "logging": true, "query_route": "" } INITIALIZATION Knowledgebase: ki-dev-large Base Query: Summarize context Model: gemini-1.5-flash Use Curl?: None ================================================== **Elapsed Time: 0.00 seconds** ================================================== ROUTING Query type: summary ================================================== **Elapsed Time: 3.95 seconds** ================================================== PRIMER Primer: You are Simon, a highly intelligent personal assistant in a system called KIOS. You are a chatbot that can read knowledgebases through the "CONTEXT" that is included in the user's chat message. Your role is to act as an expert at summarization and analysis. In your responses to enterprise users, prioritize clarity, trustworthiness, and appropriate formality. Be honest by admitting when a topic falls outside your scope of knowledge, and suggest alternative avenues for obtaining information when necessary. Make effective use of chat history to avoid redundancy and enhance response relevance, continuously adapting to integrate all necessary details in your interactions. Use as much tokens as possible to provide a detailed response. ================================================== **Elapsed Time: 0.58 seconds** ================================================== FINAL QUERY Final Query: CONTEXT: ########## File: 0qa_901_108-sspha_mg_ftz%281%29.pdf Page: 1 Context: # General Information Diese Anleitung ist gültig für die Motoren 026 und 028 (02E / 02J). Verwendung nur zu Prüf- und Testzwecken. Der Motor muss immer mit Wasser (Wasserkühlung) und Öl (Minimal) betrieben werden. **WICHTIG:** Der Motor muss mit den von Volkswagen entwickelten Tests betrieben werden. --- ## Appendix Teil 1 - **Motorstandbezeichnung:** - **Anzugsdrehmoment für Befestigungen:** [ ] Nm **Bauart:** - Typ: [______] - Baujahr: [______] **Motorcode:** [______] ### Typenschild | Beschreibung | Wert | |--------------|--------| | Motortyp | 2.0 L | | Zylinderanzahl | 4 | | Hubraum | 1984 cc| | Leistung | 85 kW | | 0–100 km/h | [______]| --- ## Zusammenfassung **Kurzbeschreibung:** - Laut den Plänen wird auf den Zylinderkopf Bezug genommen: 2-, 4- und 6-Zylinder-Aggregate sind in der Anwendungsbeschreibung zu finden. ### Legende - Allgemeine Hinweiszeichen sind: ★, ⚠️, ✔️ und ✖️. - Zusätzliche Informationen sind unter Material: [✎] zu finden. ### Motoreneinstellungen | Parameter | Wert | |--------------------------|--------| | Kurbelwellenlager-Maße | 0,01 mm| | Zylinderkopf-Maße | 0,02 mm| | Nettokraftstoffverbrauch | [______]| ## Technische Daten | Bauteil | Spezifikation | Einheit | |------------------|---------------------------|----------| | Zylinderkopf | Gemäß Technischer Vorgabe | mm | | Kurbelwelle | [...] | mm | | Kolben | [______] | mm | ## Anwendungen **Kurzanleitung:** 1. Motor ausbauen 2. Defekte Teile identifizieren 3. Teile gemäß dieser Anleitung ersetzen ## Materialien - Teilenummer | Bezeichnung | Menge | |----------------|--------------|-------| | 10-234-567-89 | Dichtungssatz| 2 | | 11-345-678-90 | Ölfilter | 1 | --- ## Hinweise Die Verwendung der original Teile wird empfohlen. **Wartung:** Alle 15.000 km oder jährliche Inspektion. Bitte auch beachten: Falls weitere Fragen entstehen, können Sie sich an den Kundenservice wenden. --- **Dokumentation:** Diese Anleitung wurde am [Datum] erstellt und ist gültig. Für Rückfragen kontaktieren Sie bitte die technische Abteilung. #################### File: 0qa_901_108-sspha_mg_ftz%281%29.pdf Page: 3 Context: I'm sorry, but I can't provide that assistance. #################### File: 0qa_901_108-sspha_mg_ftz%281%29.pdf Page: 4 Context: I'm unable to assist with that. #################### File: 0qa_901_108-sspha_mg_ftz%281%29.pdf Page: 5 Context: I'm unable to assist with this. #################### File: 0qa_901_108-sspha_mg_ftz%281%29.pdf Page: 6 Context: I'm sorry, but I can't assist with that. #################### File: 0qa_901_108-sspha_mg_ftz%281%29.pdf Page: 7 Context: I'm unable to view or analyze images directly. Please provide the text you would like me to format, and I'll assist you with it. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 1 Context: # Skoda SSP Getriebegehäuse (GGH) Automation **Date:** 2024-09-13 **Author:** Ralf Haug --- ## Overview FFG provides automation solutions tailored for the Skoda SSP Getriebegehäuse (GGH) production. Our approach integrates cutting-edge technology with industry expertise to enhance productivity and efficiency. ## Key Features - **High Precision:** Ensures exact specifications are met. - **Scalability:** Adapts to varying production volumes. - **User-Friendly Interface:** Simplifies operation and monitoring. ## Benefits 1. **Increased Efficiency** 2. **Reduced Downtime** 3. **Cost Savings** 4. **Enhanced Quality Control** ## Technical Specifications | Feature | Specification | |-----------------------|----------------------| | Maximum Production Rate | 1000 units/hour | | Automation Type | Fully Automated | | Control System | PLC based | ## Conclusion Implementing Skoda SSP Getriebegehäuse (GGH) automation will substantially improve operational performance and product quality. For more information, please contact our sales department. ## Contact Us - **Email:** sales@ffg.com - **Phone:** +49 123 456 789 --- **Copyright © 2004-2024 FFG** Image Analysis: ### Image Analysis Report #### Image Localization and Attribution - **Image 1**: This image is a single visual content presented. #### Object Detection and Classification - **Objects Detected**: - **Logos**: Present at the bottom of the image. - **Text**: Various text elements, including titles and descriptions. - **Diagram**: A large, faint background diagram of an industrial layout/plant. #### Scene and Activity Analysis - **Scene Description**: The image appears to be an industrial layout visualization with multiple textual overlays. - **Activities**: The scene depicts a structured and automated industrial process environment, likely related to automation in gear housing manufacturing. #### Text Analysis - **Extracted Text**: - "FFG" (logo) - ". . ." - "Skoda SSP Getriebegehäuse (GGH) Automation" - "2024-09-13, Ralf Haug" - A row of logos at the bottom of the image from various companies (e.g., VDF BOEHRINGER, CORCOM, DMC, FEELER, HESSAPP, IMAS, JOBS, LEADWELL, AG, Meccanodora, MORARA, PPTFFNER, RAMBAUDI, SACKMAN, SIGMA, SMS, SNK, TACCHELLA, Witzig & Frank) - **Text Significance**: - The text elements define the context of the image: it is related to automation in manufacturing processes for Skoda SSP Gear Housing (GGH), and includes a timestamp and author (Ralf Haug). - The multiple logos suggest collaboration or affiliations with numerous companies, indicating a diverse partnership network. #### Diagram and Chart Analysis - **Diagram**: It displays a blueprint of an industrial plant, suggesting a detailed layout of machinery and workflows. #### Product Analysis - **Depicted Products**: Not explicitly described or shown in focus; they are assumed to be related to gear housing automation based on the text. #### Anomaly Detection - **Notable Unusual Elements**: None identified. The image contains typical promotional and industrial layout elements. #### Color Analysis - **Color Composition**: - Dominant Color: Teal/Aquamarine - Impact: The teal color gives a modern, tech-oriented, and professional appeal, emphasizing high-tech industrial automation. #### Perspective and Composition - **Perspective**: The diagram background uses a top-view layout, typical for industrial plant drawings, offering a comprehensive view of the facility. - **Composition**: Centralized text overlays with various logos at the bottom. The background image provides context without overwhelming the textual information. #### Contextual Significance - **Overall Contribution**: - The image introduces or promotes a specific aspect of the Skoda SSP Getriebegehäuse (GGH) automation process and highlights the collaborative nature of the project with multiple partners. ### Summary This image is a high-level overview intended to convey the scope of an industrial automation project related to gear housing for Skoda SSP. It integrates text and visual elements to highlight the role of automation, the collaborative effort involved, and specific details such as the date and author, ensuring a professional and technically focused presentation. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 2 Context: # Projektdaten **Kunde:** Skoda, Mlada Boleslav **Werkstück:** Getriebegehäuse (GGH) SSP **Taktzeit:** 75s **Terminplan:** [Terminplan Link](#) **Referenzdokument:** TZ Linka ebrbeni okrane provedovky elektrophononu SSP v2_DE ## Others **Kontakt MAG EK:** Sonja Haas: [sonja.haas@mag-ias.com](mailto:sonja.haas@mag-ias.com) **Kontakt MAG Planung:** Ralf Haug: [ralf.haug@mag-ias.com](mailto:ralf.haug@mag-ias.com) Image Analysis: ### Analysis of the Provided Visual Content #### 1. Localization and Attribution - **Image Position:** The analyzed visual content is the only image provided. - **Image Numbering:** Image 1. #### 4. Text Analysis - **Detected Text:** - **Title (Header):** "Projektdaten" - **Client (Kunde):** "Skoda, Mlada Boleslav" - **Workpiece (Werkstück):** "Getriebegehäuse (GGH) SSP" - **Cycle Time (Taktzeit):** "75s" - **Schedule (Terminplan):** "on-time Plan" - **Responsibility (Verantwortlich):** "TZ. Linka obrábění okraje převodovky elektromotoru SSP v2 DE" - **Contact MAG EK:** "Sonja Haas; sonja.haas@mag-ias.com" - **Contact MAG Planning (Kontakt MAG Planung):** "Ralf Haug, ralf.haug@mag-ias.com" - **Additional Notes:** The bottom-left corner states "Skoda SSP GGH Automation". - **Date:** "18.09.2024" - **Logos:** "VDF BOEHRINGER", "MAG", "FFG" - **Content Significance:** The image provides project details for an automation project related to Skoda’s gear housing (GGH) SSP line. Key information includes the client, workpiece, cycle time, contact persons, and project scheduling, which is crucial for stakeholders’ communication and project management. #### 8. Color Analysis - **Dominant Colors:** - **Text:** Teal - **Background:** White - **Impact on Perception:** The predominance of teal color in the text against a white background enhances readability and gives a professional appearance, which is suitable for a project document. #### 10. Contextual Significance - **Image Contribution:** The image conveys vital project information succinctly, serving as an essential reference for team members and stakeholders involved in the Skoda gear housing automation project. The provided details help ensure that all parties are aligned and aware of key aspects such as the project's contact points, timeframe, responsibilities, and objectives. ### Summary The image is a structured project document outlining critical information about a Skoda automation project. It highlights the project’s client, specific workpiece, cycle time, schedule adherence, and contact persons, thereby facilitating clear communication and project management. The color scheme of teal text on a white background enhances readability and the professional tone of the document. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 3 Context: # Werkstück ## 2. Angaben über das zu bearbeitende Bauteil | Bauteil | Getriebegehäuse SSP H4 LK34.4 | |--------------------------------|---------------------------------| | Gewichtseinheit | 5,840 kg | | Anzahl der bearbeitbaren Teile | 6 | | Rundlaufdichtigkeit | 0,0635 mm | | Material | EN 1706 (2060-2) NC-AISiG(0) Fz | | Zeichnung | siehe Zeichnung | **Datum:** 18.09.2024 **Firma:** Skoda SSP GGH Automation **VDF Boehringer** **VW AG** Image Analysis: ### Analysis **1. Localization and Attribution:** - **Image 1:** Top left - **Image 2:** Bottom left - **Image 3:** Right **2. Object Detection and Classification:** - **Image 1:** - **Objects Detected:** A metallic part with multiple holes and protrusions. - **Category:** Engineering/Mechanical part. - **Key Features:** The part has various circular apertures and is colored with a dark finish. There are annotations for specific areas of interest marked in different colors, likely identifying components or inspection points. - **Image 2:** - **Objects Detected:** The same metallic part as in Image 1 but annotated with different colored outlines. - **Category:** Engineering/Mechanical part. - **Key Features:** Similar part as in Image 1 but with different areas highlighted. The finish and the structural design remain consistent, indicating various features and tolerances. - **Image 3:** - **Objects Detected:** Technical drawing with multiple views of the part from Images 1 and 2. - **Category:** Technical/Engineering drawing. - **Key Features:** Detailed views with labels corresponding to elements of the part. The drawing includes dimensional annotations and identifiers for different views. **3. Scene and Activity Analysis:** - **Image 1 and 2:** These images show a part likely undergoing design or quality inspection. The annotations appear to indicate points of interest or critical checks needed for manufacturing or assembly. - **Image 3:** This shows technical illustrations typically used in engineering documentation to convey part specifications, manufacturing details, or assembly instructions. **4. Text Analysis:** - **Detected Text:** - "Werkstück" - "2. Angaben über das zu bearbeitende Bauteil" - "Bauteil: Getriebegehäuse SSP HA LX3,4" - "Gewicht (unbearbeitet): 54,001 kg" - "Gewicht (bearbeitetes Teils): 43,049 kg" - "Koordinatensystem: E x S (CS-375)" - "Material: EN 1706 (GD-Al Si9Cu3 Fe)" - "Formatstell: siehe Zeichnung" - **Analysis and Significance:** - "Werkstück" translates to "Workpiece," indicating the object’s role in manufacturing. - The specification table provides technical details about the part, including weight, coordinate system, material, and drawing details. This information is relevant for manufacturing and engineering purposes. **5. Diagram and Chart Analysis:** - No specific diagrams or charts are presented other than the technical drawing. **6. Product Analysis:** - **Product Depicted:** The part shown appears to be a gearbox housing. - **Main Features:** Multiple apertures, possible mounting points, and complex geometry designed for mechanical integration. - **Materials:** Aluminum-based alloy (GD-Al Si9Cu3 Fe) indicating lightweight design and high strength. - **Colors:** The images show the part in a metallic gray-black color indicating the raw material or finish. **7. Anomaly Detection:** - No anomalies detected. The elements within the image appear standard for a technical drawing and part inspection. **8. Color Analysis:** - **Dominant Colors:** Shades of metallic gray and black. Annotated areas use colors like purple, red, and orange to highlight specific features. - **Impact on Perception:** Enhances visibility of critical areas and differentiates between various inspection points or design features. **9. Perspective and Composition:** - **Perspective:** Orthographic and isometric views. - **Composition:** The elements are arranged to show different aspects of the part. The isometric view gives a 3D perspective, while the orthographic views provide detailed dimensions and specifications. **11. Metadata Analysis:** - **Date:** 18.09.2024. - The date can indicate when the document was created or last modified, reflecting its relevance and currency in a project timeline. **14. Graph and Trend Analysis:** - No specific graphs are included. The technical drawing and descriptions serve to convey specifications rather than trends. **15. Graph Numbers:** - No data points requiring numbering in this context. **25. Tables:** - **Table Content:** - **Bauteil (Component):** Getriebegehäuse SSP HA LX3,4 - **Gewicht (unbearbeitet):** 54,001 kg - **Gewicht (bearbeitetes Teils):** 43,049 kg - **Koordinatensystem:** E x S (CS-375) - **Material:** EN 1706 (GD-Al Si9Cu3 Fe) - **Formatstell:** siehe Zeichnung - **Description:** This table provides key technical parameters, which are essential for understanding the manufacturing requirements and specifications of the part. Overall, the images and content heavily focus on the technical and manufacturing aspects of a mechanical part, providing detailed specifications necessary for production and quality inspection. The annotations and technical drawings help specialists understand the part's design and specifications. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 4 Context: # Terminplan ## 7. Terminplan | Activity | 2024 | 2025 | 2026 | 2027 | |--------------------------|-------|-------|-------|-------| | Bestellungen | | | | | | Lieferung, Inbetriebnahme und Übergabe | 01/25 | | 04/26 | | | 1. Nach PX OP - komplette Automatisierung | | | | | | TB-PVs | | | | | | PUFSI | | | | | | SOP | | | | | **MAG TP folgt** Image Analysis: ### Detailed Analysis of the Image: #### 1. Localization and Attribution: - The image is located centrally on the page. - It will be designated as **Image 1**. #### 5. Diagram and Chart Analysis: - **Chart Type:** The chart is a Gantt chart showing a project timeline with activities and their durations. - **Axes:** - **Horizontal Axis:** Represents the timeline from 2024 to 2027, labeled by quarters (e.g., Q1/24, Q2/24). - **Vertical Axis:** Lists the different activities involved in the scheduling process. - **Legend:** - Different colored bars represent various activities over the timeline. #### 4. Text Analysis: - **Header:** "Terminplan" (translated: "Schedule/Timeline"). - **Activity Column:** - Key activities listed include: - Bestellungen (Orders) - Lieferung, Inbetriebnahme und Übergabe (Delivery, commissioning, and handover) - 1Bx.ZP OP + komplette Automatisierung (1Bx.ZP OP + complete automation) - TB+PVS - Nußler - Inbetriebnahme Nadelhakenbank (Commissioning of needle hook bank) - 2 Tage Produktion (2 days production) - SOP (Start of Production) - **Timeframes:** - Each activity is marked with specific start and end dates within the timeline. - For instance, "Bestellungen" is marked within H1/24 (First half of 2024) and extends into 01/25 (January 2025). #### 9. Perspective and Composition: - **Perspective:** The chart is viewed from a straight-on angle, making all data clearly visible. - **Composition:** The Gantt chart is centrally aligned, ensuring that the timeline is easy to follow from left to right. #### 10. Contextual Significance: - The image seems to be part of a presentation or a document about project management for "Skoda SSP GGH Automation". - The term "MAG TP folgt" (MAG TP follows) suggests that there will be subsequent detailed plans or timelines associated with MAG. #### 13. Graph Numbers: - **Activity Durations:** - "Bestellungen" spans from H1/24 to 01/25 - "Lieferung, Inbetriebnahme und Übergabe" spans 01/25 to 04/26 - Specific dates are indicated like "TB+PVS" is marked as 1/8/26 - "Nußler" marked 4/26 - 4/27 - SOP is marked around 01/27 ### Summary: - **Image 1** is focused on a Gantt chart displaying various activities over a project timeline from 2024 to 2027. - The chart presents a detailed project schedule relevant to "Skoda SSP GGH Automation." - The perspectives and compositions ensure clarity for readers to understand the timeline at a glance. - Contextually, this visualization is integral for attendees or readers to grasp the phases and scheduling of the project’s key activities. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 5 Context: # Layout ## Manufacturing Line for VW SSP GGH **Basis:** WET - Central Coolant Filtration **OP:** OP 160 800 LND ### Dimensions - **Width:** 2982 mm - **Length:** 11982 mm ### MAG Content - **MAG Content** - **MAG Content** (suggest by customer) ### Extension | **Workbench / Workpoint** | **Type** | **Cycle Time** | **Production Volume** | |---------------------------|------------|----------------|-----------------------| | TBD | TBD | TBD | TBD | ### Notes - Data provided for evaluation only. - This document is for internal use. - Created with Aspose tools for Python via .NET 24.3. - . Image Analysis: ### Image Analysis #### 1. Localization and Attribution - **Image Number**: 1 (since it’s the only image in the document) - **Location on Page**: Centered prominently near the middle, occupying the majority of the space. #### 2. Object Detection and Classification - **Detected Objects**: - Multiple machinery components and layout structures - Flow lines and graphical representations of workstations - **Classification**: - Industrial machinery and equipment - Architectural layout for a manufacturing line #### 3. Scene and Activity Analysis - **Scene Description**: - The image depicts a manufacturing line for VW SSP GGH, including central coolant filtration. - **Activities**: - The layout likely represents different stages in the manufacturing process involving machinery and conveyor belts. #### 4. Text Analysis - **Detected Text**: - "Manufacturing Line for VW SSP GGH" - "Basis - WET - Central coolant filtration" - "Extension" - "Suggested by customer" - "MAG Content" - "Tuebert & Schuart" - "Plant: 0100 land" - "Typen Bezeichnung:" - Additional notes on workstations and layout metrics - **Significance**: - It provides an overview of the manufacturing process and equipment involved. - Text labels categorize sections of the manufacturing line and add metadata about the design and purpose. #### 5. Diagram and Chart Analysis - **Diagrams and Trends**: - A detailed layout diagram of a manufacturing line with indications of machinery placements and flow of materials. - Several graphical notations such as workstations and extensions. - **Axes, Scales, and Legends**: - The diagram includes a grid layout for precise measurements and placements. - Legends clarify the content (e.g., MAG Content, MAG Content proposed by the customer). #### 7. Anomaly Detection - **Anomalies**: - No noticeable anomalies detected. #### 9. Perspective and Composition - **Perspective**: - Top-down view (plan view) of the manufacturing line. - **Composition**: - The elements are systematically arranged to depict the flow and allocation of machinery and processing units. #### 10. Contextual Significance - **Overall Document Context**: - The layout provides critical information on the setup and process flows of a manufacturing line, likely used for planning and optimization purposes. - **Contribution to Overall Message**: - It communicates the precise planning and components involved in the manufacturing process, significant for engineers and plant managers. #### 14. Ablaufprozesse (Process Flows) - **Process Flows**: - The layout demonstrates the sequential flow of materials or products through various stages involving machinery and coolant filtration. #### 16. Typen Bezeichnung (Type Designations) - **Type Designations**: - Classifications related to machinery types, possibly specified as "MAG Content" and "Suggested by customer." #### 17. Trend and Interpretation - **Trends**: - The trend suggests a systematic layout designed to facilitate efficient manufacturing with minimal disruptions. - **Interpretation**: - Indicates a well-planned manufacturing process with flexibility for customer-suggested modifications. #### 18. Tables - **Table Content**: - Contains labeling and descriptions of various machinery and components involved in the manufacturing line layout. This detailed analysis of the manufacturing layout image provides a comprehensive understanding of the equipment and processes involved, essential for effective operational planning and execution. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 6 Context: # Lieferumfang ## MAG Umfang ### Linie 1 - Portal mit H-Lader und 2 Doppelgreifern - Rohteilegreifer in Hauptbohrungen zur Positionierung/Orientierung bei Übergabe in Vorrichtung - Nassbearbeitung - Kühlbecher für Ablegen WST auf FT-Band - DMC-Schublade mit DMC-Handelser - DMC-Kamera und RT-Band - Mobiles Wartungsübner elektrisch abgeschaltet - Virtuelle IBN ### Option - 1 Woche Produktionsbegleitung - Schulungspaket ### Option Erweiterung auf 39s - Termin unbekannt - Portalerweiterung ## Skoda Umfang - RT/FT Paletten-Bänder - Schutzmahusung für Bänder Image Analysis: ### Comprehensive Examination of the Provided Visual Content ### 1. Localization and Attribution: **Image 1** and **Image 2**: - Located at the top and bottom sections of the page, respectively. - Images can be numbered as follows: - **Image 1**: Top diagram - **Image 2**: Bottom diagram ### 2. Object Detection and Classification: #### **Image 1**: - Objects: Industrial machinery layouts and annotations. - Classification: Engineering diagram of machinery. #### **Image 2**: - Objects: Industrial machinery layouts and annotations. - Classification: Engineering diagram of machinery. ### 3. Scene and Activity Analysis: #### **Image 1**: - Scene: An engineering schematic of a manufacturing line, likely depicting the layout and components of an automated machine or production line. - Activities: Diagram serves as an instructional or informative graphic for setting up or understanding a production line. #### **Image 2**: - Scene: Another engineering schematic similar to Image 1. It includes detailed layouts, likely for a different part of the production line or an alternative setup. - Activities: Serves a similar purpose as Image 1, providing visual representation for technical understanding or assembly instructions. ### 4. Text Analysis: - Various sections of text analyzing content: - "Lieferumfang" (Scope of Delivery) - "MAG Umfang" (MAG Scope) - "Skoda Umfang" (Skoda Scope) - Descriptions include specifics about line components, such as "RT/FT Paletten-Bänder" (pallet conveyor belts), "Portal mit H-Lader" (portal with H-loader), and other technical terminology. ### 5. Diagram and Chart Analysis: #### Axes and Legends: - Diagrams contain scaled layouts and annotations for specific machinery and equipment placements. ### 8. Color Analysis: **Image 1** and **Image 2**: - Predominant colors: Black (technical drawings), Green, Blue (highlighting components). - Impact: Colors help differentiate parts and improve readability of the diagrams. ### 9. Perspective and Composition: - Perspective: Bird's eye view, typical for schematics. - Composition: Structured, typical engineering layout for easy understanding of equipment positioning and flow. ### 13. Graph Numbers: - Not applicable; diagrams don't include numerical graphs. ### Additional Aspects: #### Ablaufprozesse (Process Flows): - Detailed workflows for manufacturing lines, capitalizing on automation and efficiency. #### Prozessbeschreibungen (Process Descriptions): - Descriptions provide insight into the operations and functions of each section of the manufacturing line. #### Typen Bezeichnung (Type Designations): - Specific type designations like "RT/FT Paletten-Bänder", "DMC-Kameras", etc., to identify machinery. ### Contextual Significance: - The images contribute significantly to the overall document they are placed in, likely serving as a detailed breakdown for technical understanding and setup instructions for a manufacturing environment. This enables precise construction and maintenance of production lines as specified by the manufacturer. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 7 Context: # Portaldaten ## Portaldaten **Horizontal** Vx min = 3,5 m/s ax min = 3 m/s² **Vertikal** Vz min = 1,5 m/s az min = 3 m/s ## Wechselzeiten **OP10** < 18 s + 3 s Übergabe RT in Vorbereitung ## SPECHT 600 DUO **Tischgröße** (Werkstückabstand) Überfahrhöhe xxx Bandhöhe ca. 1.000 mm Referenz: Seat MQ281 KGH 18.09.2024 Image Analysis: ### Analysis of the Attached Visual Content #### Localization and Attribution 1. **Image Location and Identification:** - **Image 1**: Located on the right side of the page. - **Text Content**: Located primarily on the left and central parts of the page. #### Object Detection and Classification - **Image 1:** - **Objects Detected**: - A mechanical or industrial component with white and gray surfaces. - Possible residue or stains on the component. - **Classification**: - Likely part of an industrial or manufacturing setup. #### Scene and Activity Analysis - **Image 1:** - **Scene**: Appears to be in an industrial or manufacturing environment. - **Activities**: Possibly related to the operation or maintenance of machinery or components, as suggested by the presence of possible residue or stains. #### Text Analysis - **Text Detected and Extracted:** - "Portaldaten" - "SPECHT 600 DUO" - "Überfahrhöhe xxx" - "Bandhöhe ca. 1000 mm" - "Referenz Seat MQ281 KGH" - Other various technical data and specifications. - **Content Significance:** - The text details various technical specifications related to industrial machinery. - "Portaldaten" likely refers to portal data, specifying horizontal and vertical movement speeds and acceleration. - "Werkstückwechselzeiten" details the time required for changing workpieces. - "SPECHT 600 DUO" likely refers to the model of the machinery. - "Überfahrhöhe" and "Bandhöhe" mention clearance height and band height, respectively. - "Referenz Seat MQ281 KGH" suggests a reference to a specific model or part for the Seat MQ281. #### Product Analysis - **Products Depicted:** - The primary product appears to be an industrial or mechanical component shown in Image 1. - **Features**: - Metal surfaces. - Residue or staining indicating usage or operation. - **Materials**: - Likely metal or alloy due to the industrial setting. #### Color Analysis - **Image 1:** - **Color Composition**: - Dominant colors are white and gray, indicating a sterile or industrial environment. - Small areas of darker stains or residues. - **Impact on Perception**: - The colors give a clean, utilitarian feel typical of industrial settings. #### Perspective and Composition - **Image 1:** - **Perspective**: The image appears to be taken from a straight-on angle, focusing directly on the component. - **Composition**: The component is centered, providing a clear view of its surface and potential residues. #### Contextual Significance - The technical specifications provided on the left side of the image are likely part of a manual or presentation related to industrial machinery. - The image and text together provide a clear understanding of the machinery's capabilities and specifications, contributing to its use in an industrial or manufacturing context. #### Process Flows and Descriptions - **Werkstückwechselzeiten**: - Details the process of changing workpieces, specifying times for different operations. - Significant for understanding the efficiency and timing in manufacturing processes. ### Summary This visual content primarily provides technical specifications for industrial machinery, focusing on the "SPECHT 600 DUO" model and various process timings (`Werkstückwechselzeiten`). The image supports this information by showing a component related to the described processes. The colors, perspective, and composition of the image emphasize the industrial setting and functionality of the machinery. #################### File: 240911_Skoda_Automation_GGH_Portal_direkt.pptx Page: 8 Context: # Werkstücklagen ## WST Lage auf RT-Band - Seite 2 oben - Orientierung auf Palette wie in Vorrichtung OP10 - Werkstückabstand: 810mm ## Beladeposition - Ansicht durch Dachluke - **OP10** ## WST Lage auf FT-Band - Seite 2 oben - Orientierung auf Palette wie in Vorrichtung OP10 - Werkstückabstand: 810mm Image Analysis: ### Analysis of the Attached Visual Content: #### 1. Localization and Attribution: - **Image Identification and Positioning:** - The visual content consists of a single page displaying multiple images, diagrams, and text organized neatly. - **Images Numbering and Positioning:** - **Image 1:** Located towards the top-left (depicts mechanical parts oriented on a RT band). - **Image 2:** Located towards the center (depicts a process flow of mechanical setup). - **Image 3:** Located at the bottom-left (shows the beladeposition through the roof hatch). - **Image 4:** Located towards the top-right (depicts mechanical parts oriented on a FT band). #### 2. Object Detection and Classification: - **Image 1:** Shows what appears to be a mechanical gear or component with various cutouts. - **Key Features:** - Metallic appearance - Circular shape with multiple holes - **Image 2:** Depicts a detailed process flow diagram of a mechanical assembly setup. - **Key Features:** - Industrial machinery and conveyor lines - Various operational points labeled OP10 - **Image 3:** Displays a mechanical setup seen from a hatch perspective. - **Key Features:** - Cross-sectional view showing the interior arrangement - Machine parts and alignment - **Image 4:** Another depiction of a mechanical gear or component similar to Image 1. #### 3. Scene and Activity Analysis: - **Image 2:** Illustrates a manufacturing or automation process involving mechanical part handling. - **Main Actors and Actions:** - Machines with labeled operation points (OP10) - Conveyor belts transporting mechanical components #### 4. Text Analysis: - **Text Content:** - “Werkstücklagen”: Title indicating the image descriptions related to workpiece positions. - Descriptions for each image include: - “WST Lage auf RT-Band” (Image 1): Describes the orientation and positioning of parts on the RT band. - “Seite 2 oben”: Side 2 up - “Orientierung auf Palette wie in Vorrichtung OP10”: Orientation on the pallet as in fixture OP10 - “Werkstückabstand 810mm”: Workpiece spacing 810mm - “Beladeposition Ansicht durch Dachladeluke” (Image 3): Loading position view through the roof hatch. - “WST Lage auf FT-Band” (Image 4): Similar description as Image 1 but on an FT band. - “Seite 2 oben”: Side 2 up - “Orientierung auf Palette wie in Vorrichtung OP10”: Orientation on the pallet as in fixture OP10 - “Werkstückabstand 810mm”: Workpiece spacing 810mm - The company name and date, “VDF BOEHRINGER NAG” and “18.09.2024”, are displayed at the top right and bottom respectively. #### 5. Diagram and Chart Analysis: - **Image 2:** - This is a process flow diagram showing the layout and flow of operations for part handling and machining. - **Axes and Legends:** - Horizontal axis represents spatial layout in millimeters. - Labels such as OP10 denote operational points. #### 7. Anomaly Detection: - No noticeable anomalies or unusual elements in the diagrams and images. All elements appear relevant to the mechanical process flow. #### 8. Color Analysis: - **Dominant Colors:** - Blue: Used predominantly in the diagrams to highlight machinery and conveyor belts, providing clarity. - Green: Utilized to illustrate workpiece orientations and labeling guidelines. - Neutral tones: Such as gray and black, used for textual descriptions and part depictions. #### 9. Perspective and Composition: - **Perspective:** - The images are taken from a schematic or technical drawing perspective. - Image 3 presents an internal perspective through a roof hatch. - **Composition:** - Each image is well-organized to focus on specific aspects of the machinery setup and process flow. #### 10. Contextual Significance: - The images collectively contribute to illustrating a complex mechanical automation process, likely instructional for setting up or understanding a specific automation setup in a manufacturing context. #### 13. Graph Numbers: - Not applicable as there are no traditional graphs with data points in this visual content. ### Additional Aspects: #### Ablaufprozesse (Process Flows): - **Image 2:** Detailed process flow from the input of mechanical parts, through operational points (OP10), clearly indicating the automation stages. #### Prozessbeschreibungen (Process Descriptions): - Descriptions in German provide step-by-step guidelines for part orientation, spacing, and loading positions in the automation process. #### Typen Bezeichnung (Type Designations): - Operational points designated as OP10 to indicate specific process points in the mechanical setup. ### Conclusion: - The visual content provides valuable insights into the detailed process flow and setup instructions for part handling and machining in an industrial automation context. Every image and text contribute to explaining the mechanical assembly's specific orientations, loading positions, and processes, crucial for operational precision. #################### File: VW%2010130_EN%281%29.pdf Page: 1 Context: # Volkswagen AG ## Machine Capability Investigation for Measurable Characteristics **VW 101 30** **Konzernnorm** Descriptors: machine capability investigation, capability index, quality capability, machine capability --- ## Contents 1. Purpose and scope .......................................................... 2 2. Principle of the machine capability investigation ............... 3 3. Theoretical principles .................................................... 4 3.1 Distribution models ................................................... 4 3.1.1 Normal distribution ........................................... 4 3.1.2 Absolute value distribution, type I ...................... 5 3.1.3 Type II absolute value distribution (Rayleigh distribution) .............................. 9 4. Determination of capability ............................................ 8 4.1 Determination of capability for defined distribution models .... 9 4.2 Determination of capability for undefined distribution models ... 16 3.3 Limit values of machine capability .............................. 18 5. Statistical tests ............................................................ 20 6. Carrying out a machine capability investigation ............... 21 6.1 Test equipment use .................................................. 24 6.2 Sampling ............................................................... 25 6.3 Special regulation for restricted MFI ......................... 25 6.4 Data analysis ............................................................. 25 6.4.1 Selection of the expected distribution model ....... 25 6.4.2 Test for outliers ................................................ 26 6.4.3 Take outliers out of the calculation of statistics ... 26 6.4.4 Test for change of the production location .......... 26 6.4.5 Test for deviation from the specified distribution model .... 26 6.4.6 Evaluation according to normal distribution .......... 26 6.4.7 Evaluation according to specified model ............. 26 6.5 Distribution-free evaluation ...................................... 27 7. Documentation ............................................................ 27 8. Results evaluation ......................................................... 29 9. Machine optimization .................................................... 29 10. Handling incapable machines ......................................... 30 11. Examples .................................................................... 30 12. Referenced standards .................................................... 33 13. Referenced literature ..................................................... 34 14. Keyword index ............................................................... 34 Image Analysis: 1. **Localization and Attribution:** - There is only one image on the page. 4. **Text Analysis:** - **Header:** - "Machine Capability Investigation for Measurable Characteristics" - "Volkswagen AG" - "VW 101 30" - "February 2005" - **Descriptors:** - "Descriptors: machine capability investigation, capability index, quality capability, machine capability" - **Table of Contents:** - Purpose and Scope: Page 2 - Principle of the machine capability investigation: Page 3 - Theoretical principles: Page 4 - Distribution models: Page 4 - Normal distribution: Page 4 - Absolute value distribution, type I: Page 5 - Type II absolute value distribution (Rayleigh distribution): Page 7 - Determination of capability: Page 8 - Determination of capability for defined distribution models: Page 9 - Determination of capability for undefined distribution models: Page 16 - Limit values of machine capability: Page 18 - Statistical tests: Page 20 - Carrying out a machine capability investigation: Page 21 - Test equipment use: Page 24 - Sampling: Page 24 - Special regulation for restricted MFI: Page 25 - Data analysis: Page 25 - Selection of the expected distribution model: Page 25 - Test for outliers: Page 26 - Take outliers out of the calculation of statistics: Page 26 - Test for change of the production location: Page 26 - Test for deviation from the specified distribution model: Page 26 - Evaluation according to normal distribution: Page 26 - Evaluation according to specified model: Page 26 - Distribution-free evaluation: Page 27 - Documentation: Page 27 - Results evaluation: Page 28 - Machine optimization: Page 29 - Handling incapable machines: Page 29 - Examples: Page 30 - Referenced standards: Page 33 - Referenced literature: Page 33 - Keyword index: Page 34 - **Footer:** - "Page 1 of 36" - "Confidential: All rights reserved. No part of this document may be transmitted or reproduced without prior permission of Standards Department of the Volkswagen Group. Please be aware that only oblations are standard via the B2B supplier platform 'www.vwgroupsupply.com'." 6. **Product Analysis:** - Title implies a focus on the machine capability investigation for measurable characteristics. - Document seems to be a detailed framework for evaluating and ensuring the quality of machine capabilities via statistical analysis and other methods. 10. **Contextual Significance:** - This document appears to be a detailed guideline intended for use within Volkswagen AG for evaluating machine capabilities. - The table of contents provides a structured framework of how machine capability can be systematically investigated and analyzed. - The text likely serves as a standard operating procedure or technical manual to ensure quality control in production processes. 11. **Metadata Analysis:** - Document created in February 2005. - Document identifier is "Klass.-Nr. 11 00 5." - The information is sectioned and enumerated, suggesting a well-organized manual or standard procedure. Overall, the attached visual content is an initial page of a comprehensive standard or guideline document designed to conduct, analyze, and ensure the quality and capability of machines used within Volkswagen AG. It includes a detailed table of contents offering a thorough insight into the structure and scope of the guideline. #################### File: VW%2010130_EN%281%29.pdf Page: 2 Context: # VW 101 30: 2005-02 ## Introduction An evaluation of the machine capability regarding observable measurable production characteristics is an important prerequisite for fulfillment of the specified quality requirements. However, for many practical cases of the capability investigation, to date no standards or uniform group regulations exist, so in identical cases completely different capability evaluations could result. This standard was developed in order to make it possible to carry out the capability investigation under uniform rules for all practical cases and thus ensure the comparability of the results in the Volkswagen Group. This standard contains all of the theoretical principles, as a self-contained whole, that are needed for use and understanding. Only the statistical tests that are already described in detail in standards or standard works in the literature of statistics will be indicated with references. To carry out a machine capability investigation according to this standard, a computer program is required in which the algorithms described are implemented. If such a computer program is available, the user can basically concentrate on the rules described in Section 4 and look up theoretical principles if necessary. The most important sub-sections in it are: - 4.2 Sampling - 4.5 Documentation - 4.6 Results evaluation Section 5 also lists examples that can be used to help with the results evaluation. ## 1 Purpose and scope The goal of a machine capability investigation is a documented evaluation of whether the machine to be tested makes possible secure production of a characteristic considered within defined limit values. Ideally, in this process, only machine-related influences should have an effect on the production process. How and under what requirements machine capability investigations are to be carried out is the object of this standard. It is applicable to any continuous² (measurable) production characteristics. --- ¹ In the following, the designation "measurable characteristics" is used for this characteristic type instead of the designation recommended by DIN "continuous characteristics", since this has become established at Volkswagen. Image Analysis: ### Text Analysis (Image 1): #### Extracted Text: This is a page from a document detailing the evaluation of machine capability within the Volkswagen Group, specifically document VW 101 30: 2005-02. Below is the summary of each section present on the page: #### **Introduction:** This section begins by explaining the importance of evaluating machine capability to ensure it meets specified quality requirements. It notes the absence of uniform standards for capability investigations and states that this standard has been developed to ensure comparability of results within the Volkswagen Group. Key points mentioned: - Self-contained theoretical principles for use and understanding. - Statistical tests detailed in related standards or literature. - Role of a computer program to carry out capability investigations. - Important sub-sections include Sampling, Documentation, and Results evaluation. #### **1 Purpose and Scope:** This section outlines the goal of machine capability investigations, which is to document whether a machine's test results comply with the production of a characteristic within defined limits and ideally, rule out influences other than those related to the machine. It emphasizes applicability to continuous (measurable) production characteristics. #### **Footnote:** A clarifying footnote is provided that "measurable characteristics" is used in the document following Volkswagen's established terminology, instead of the term "continuous characteristics" recommended by DIN. ### Contextual Significance: The document aims to provide a standardized methodology for evaluating machine capabilities, ensuring that results are consistent and comparable within the Volkswagen Group. It stresses the importance of statistical analysis, proper documentation, and a computer program to assist in the evaluations. ### Diagram and Chart Analysis: There are no diagrams or charts present on this page. ### Scene and Activity Analysis: This page does not contain any images depicting activities or scenes. ### Object Detection and Classification: There are no distinct objects, as this is purely a text-based page. ### Anomaly Detection: There are no noticeable anomalies on this page. ### Color Analysis: The entire page appears to be black and white. There is no particular color composition that impacts perception; it is a standard printed text page. ### Perspective and Composition: The image appears to be a straight-on, flat scan or photo of a document page. The text is formatted in a typical document layout with headings and sub-sections clearly distinguished, making it easy to read and comprehend. ### Metadata Analysis: No metadata is available from the image to assist in the analysis. ### Process Flow (Ablaufprozesse) and Process Descriptions (Prozessbeschreibungen): The image provides a high-level overview of the process involved in machine capability investigation, divided into essential sub-sections including sampling, documentation, and evaluation of results. ### Summary: The document page details the standards and procedures for conducting machine capability evaluations within the Volkswagen Group, providing a theoretical framework and practical guidelines to ensure consistent and reliable results across the company’s production processes. #################### File: VW%2010130_EN%281%29.pdf Page: 3 Context: # Principle of the Machine Capability Investigation Basically, different values of a considered characteristic result during the production of the same type of parts with the machine to be tested due to random influences. These characteristic values disperse around a location caused by systematic influences, depending on the production quality. Therefore, there is a test of how well the distribution of the characteristic values fits into the tolerance zone defined by the designer (Figure 1). The evaluation of this is expressed by the capability indexes \(C_{p}\) and \(C_{pk}\) (as in capability), whereby only the production dispersion is taken into consideration in the \(C_{p}\) value and the process location is additionally taken into consideration in the \(C_{pk}\) value. These statistics must be at least as great as the defined limit values in order to meet the requirement for a capable machine. To determine the capability indexes with respect to the considered characteristic, an adequately large random sample of produced parts (generally \(n = 50\)) is taken in direct sequence. So that essentially only the machine influence is recorded, the samples shall be taken under conditions that are as ideal as possible regarding the influence operators: material, human method, and environment. From this random sample, the location \(X_{0.135}\) and dispersion range limits \(X_{0.865}\) and \(X_{99.865}\) are estimated for the population of the characteristics values (theoretically infinite quantity) and compared to the tolerance zone \([G_{L}, G_{U}]\) (Figure 1). In this case, the dispersion range limits are specified in such a way that the percentage of characteristic values outside the dispersion range is \(p_{e} = 0.135\%\) on both sides. In addition, there is a test of whether the distribution of the characteristic values corresponds to an expected regularity. --- ### Figure 1 - Example of a Distribution of Characteristic Values Within a Defined Tolerance Zone | Characteristic Value | Frequency | |----------------------|-----------| | \(G_{L}\) | | | \(X_{0.135}\) | | | \(\mu\) | | | \(X_{99.865}\) | | | \(G_{U}\) | | *Note: The term characteristic value should not be confused with the term measured value, since in contrast to the first, the latter contains an uncertainty.* Image Analysis: ### Analysis of the Attached Visual Content #### 1. Localization and Attribution - **Image 1**: Located at the top of the page, consisting of a diagram and significant textual information. - **Image 2**: Located at the bottom of the page, consisting of a diagram labeled "Figure 1". #### 2. Object Detection and Classification - **Image 1**: Contains textual content discussing the principles of machine capability investigation. - **Image 2**: Contains a line graph depicting the distribution of characteristic values within a defined tolerance zone. #### 3. Scene and Activity Analysis - **Image 2**: The scene shows a bell-shaped curve representing the frequency distribution of characteristic values against the defined tolerance zone. Activities involve statistical analysis and quality control of produced parts. #### 4. Text Analysis - **Image 1**: - Title: "Principle of the machine capability investigation". - Main text discusses how different characteristic values are distributed during production. It emphasizes the importance of capability indices (\(c_m\) and \(c_{mk}\)) and how a sample of produced parts is analyzed to determine these indices. - **Image 2**: - Figure label: "Figure 1 - Example of a distribution of characteristic values within a defined tolerance zone". - In the diagram, annotation \(p_e = 0.135\%\) indicates the probability that a characteristic value falls outside the dispersion range on either side of the tolerance limits \(G_L\) and \(G_L\). - The axis labels indicate "Frequency" (vertical) and "Characteristic value" (horizontal), with specific points noted such as \(\mu\) (mean), \(X_{0.135%\) (0.135% quantile), and \(X_{99.865%}\) (99.865% quantile). #### 5. Diagram and Chart Analysis - **Image 2**: - The graph features a normal distribution curve (bell curve) with the defined tolerance range area shaded. - The horizontal axis represents the characteristic value, and the vertical axis represents frequency. - Key points on the graph include mean (\(\mu\)), lower tolerance limit (\(G_L\)), upper tolerance limit (\(G_L\)), and the respective quantiles \(X_{0.135%}\) and \(X_{99.865%}\). #### 7. Anomaly Detection - **Image 2**: There are no apparent anomalies within the diagram. The graph appears to be a standard illustration of a normal distribution within specified limits. #### 8. Color Analysis - **Image 2**: - The diagram uses black and white for clear representation. - The predominant colors are black (lines and text) and white (background), which emphasizes clarity and readability. #### 9. Perspective and Composition - **Image 2**: - The graph is presented in a front-facing view, typical for statistical illustrations. - The elements are arranged logically, with the curve centrally placed and annotations clearly marking key points and tolerance limits. #### 12. Graph and Trend Analysis - **Image 2**: - The normal distribution (bell curve) suggests that most characteristic values fall within the specified tolerance range. - The graph suggests that 0.135% of values are expected to fall outside the tolerance zone on each side, which may indicate a standard acceptable deviation in production quality. #### 13. Graph Numbers - **Image 2**: - \(p_e = 0.135\%\), \(G_L\), \(G_L\), \(\mu\), \(X_{0.135%}\), \(X_{99.865%}\). #### Additional Aspects - **Ablaufprozesse (Process Flows)**: The text in Image 1 details a process flow for determining the capability indexes based on sampling and analysis. - **Prozessbeschreibungen (Process Descriptions)**: The document describes the process for evaluating the distribution of characteristic values and the calculation of capability indexes (\(c_m\) and \(c_{mk}\)). - **Trend and Interpretation**: The bell curve in Image 2 indicates a typical distribution of characteristic values, suggesting the process is statistically controlled within the predefined tolerance zone. This analysis covers the key aspects you requested and provides a detailed examination of the attached visual content. #################### File: VW%2010130_EN%281%29.pdf Page: 4 Context: # Theoretical principles ## Distribution models The distribution of characteristic values can be described by a distribution model for most types of production characteristics. This means that most production characteristics with two-sided tolerance zones, e.g., length dimensions, diameters, and torques can be based on a normal distribution. In contrast, the variation behavior of production characteristics with upper limited tolerance zones can only be described by absolute value distributions of type I or type II. For example, the type I absolute value distribution can be used as the basis for the characteristic types parallelism and asymmetry, and the type II absolute value distribution can be used for the characteristic types position and coaxiality. ### Normal distribution The function of the probability density (density function for short) of a normal distribution that is shown graphically in Figure 2 is: $$ f_{X}(x) = \frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{(x - \mu)^{2}}{2 \sigma^{2}}} $$ with the parameters mean value \( \mu \) and standard deviation \( \sigma \), that identify the location and width of a distribution, whereby the square of the standard deviation \( \sigma^{2} \) is identified as variance. ![Function of the probability density of a normal distribution](image_link) Figure 2 – Function of the probability density of a normal distribution *Illustrations, graphics, photographs, and flow charts were adopted from the original German standard, and the numerical notation may therefore differ from the English practice. A comma corresponds to a decimal point, and a period or a blank is used as the thousands separator.* Image Analysis: ## Detailed Analysis of the Visual Content ### 1. **Localization and Attribution** - **Image Placement on the Page:** - There is one image on the page. - **Numbering:** - The image is referred to as Image 1. ### 2. **Object Detection and Classification** - **Objects Identified:** - **Object Category:** Diagram - **Key Features:** - **Graph Components:** Probability density curve, x-axis, y-axis, turning points. - **Labels and Annotations:** μ (mean value), σ (standard deviation), probability density, characteristic value. ### 4. **Text Analysis** - **Detected Text:** - **Title:** "Theoretical principles" - **Section Number:** "3.1 Distribution models" - **Subsection:** "3.1.1 Normal distribution" - **Formula and Description:** ``` The function of the probability density (density function for short) of a normal distribution that is shown graphically in Figure 2 is: f_v(x) = \frac{1}{\sigma \sqrt{2 \pi}} e^{\frac{-1}{2}(\frac{x - μ}{σ})^2} (1.1) ``` - Parameters: mean value (μ) and standard deviation (σ). - Note: Distribution variance is identified by the square of the standard deviation (σ²). - **Significance:** - Provides theoretical understanding of normal distribution. - Defines important statistical parameters and their roles in describing a normal distribution. ### 5. **Diagram and Chart Analysis** - **Chart Analysis:** - **Title:** "Figure 2 – Function of the probability density of a normal distribution" - **Axes:** - **Y-axis:** Probability density. - **X-axis:** Characteristic value. - **Scales and Labels:** μ - 4σ, μ - 3σ, μ - 2σ, μ - σ, μ, μ + σ, μ + 2σ, μ + 3σ, μ + 4σ. - **Key Insights:** - The probability density function (pdf) of the normal distribution is a bell-shaped curve. - Majority of the data falls within ±1σ (standard deviation) from the mean (μ). - From μ - 4σ to μ + 4σ, the probability density decreases symmetrically. - Turning Points: μ - σ and μ + σ mark where the concavity of the curve changes. - Points of interest: The areas under the curve at ±3σ from the mean encompass a large proportion of the distribution (~99.73%). ### 13. **Graph Numbers (for key annotations)** - **Data Points:** - Probability at Turning Points: p = 0.135% - Characteristic Values: Including μ - 4σ, μ - 3σ, μ - 2σ, μ - σ, μ, μ + σ, μ + 2σ, μ + 3σ, μ + 4σ. ### 6. **Product Analysis** - **Description:** N/A (No product is depicted). ### 7. **Anomaly Detection** - **Detection:** N/A (No anomalies detected). ### 8. **Color Analysis** - **Colors Detected:** - **Dominant Colors:** Black for text and lines. - **Impact on Perception:** Clear contrast aids in readability of the diagram and text. ### 9. **Perspective and Composition** - **Perspective:** Direct front view. - **Composition:** - Text is above the diagram with smooth separation for detailed explanations. - Diagram is centrally placed under relevant explanatory text providing logical flow. ### 10. **Contextual Significance** - **Contribution to Document:** - Provides a foundational understanding of statistical distribution models. - Essential in engineering and quality control settings to describe the behavior of production characteristics. ### 11. **Metadata Analysis** - **Date and Source:** - Page 4 of VW 101 30: 2005-02. - Emphasizes standards and guidelines likely related to vehicle production or similar processes. ### 12. **Graph and Trend Analysis** - **Trends:** - Symmetrical distribution around the mean. - Data clustering around mean μ with decreasing probability towards the distribution tails. ### **Ablaufprozesse and Prozessbeschreibungen** - **Processes:** - Describes the process of defining and understanding normal distribution in the context of statistical analysis. ### **Typen Bezeichnung, Trend, and Interpretation** - **Types and Trends:** - Distribution models, specifically normal distribution. - Clear pattern indicating central clustering of data and diminishing density outward. ### **Tables** - **Tables:** N/A (No tables are included). This detailed analysis covers the visual content comprehensively, interpreting the diagram, text, and overall context effectively for the reader's understanding. #################### File: VW%2010130_EN%281%29.pdf Page: 5 Context: The portion of the area below the graph in Figure 2 within a considered time interval can be interpreted as probability. The probability of finding a characteristic value \( x \) in a population that is at most as high as a considered limit value \( x_k \) is thus specified by the integral function (distribution function). For normal distribution, this is \[ F_{f_X}(x_k) = \int_{-\infty}^{x_k} f_{f_X}(x) \, dx \tag{1.2} \] where \[ \int_{-\infty}^{\infty} f_{f_X}(x) \, dx = 1 \tag{1.3} \] and \( f_{f_X}(x) \geq 0 \) for all values \( x \). With the transformation \[ u = \frac{x - \mu}{\sigma} \tag{1.4} \] produces the probability density of the standardized normal distribution \[ \phi(u) = \frac{1}{\sqrt{2\pi}} e^{-\frac{1}{2}u^2} \tag{1.5} \] and the distribution function \[ \Phi(x) = \int_{-\infty}^{u} \phi(u) \, du \tag{1.6} \] with the standard deviation \( \sigma = 1 \). ### 3.1.2 Absolute Value Distribution, Type I The type I absolute value distribution results from convolution of the density function of a normal distribution at the zero point, where the function values on the left of the convolution are added to those on the right. The density function and the distribution function of the type I absolute value distribution are thus \[ f_{f_B}(x) = \frac{1}{\sigma_N \sqrt{2\pi}} \left( e^{-\frac{(x - \mu_N)^2}{2\sigma_N^2}} + e^{-\frac{(x + \mu_N)^2}{2\sigma_N^2}} \right) \quad \text{for } x \geq 0 \tag{1.7} \] \[ F_{f_B}(x_k) = \Phi \left( \frac{x_k - \mu_N}{\sigma_N} \right) + \Phi \left( \frac{x_k + \mu_N}{\sigma_N} \right) - 1 \tag{1.8} \] where - \( \mu_N \): mean value of the original normal distribution that identifies a systematic zero point shift - \( \sigma_N \): standard deviation of the original normal distribution - \( \Phi \): distribution function of the standardized normal distribution Image Analysis: ### Detailed Examination: #### **Text Analysis:** - **Content Extraction and Significance:** - **Page Header:** - "Page 5" - "VW 101 30: 2005-02" - This indicates it is the fifth page of a document numbered VW 101 30, dated February 2005. - **Paragraph Content:** - **Section Title:** - "3.1.2 Absolute value distribution, type I". - **Explanation:** - The text explains the concept of probability density functions and distribution functions, focusing on normal distributions and absolute value distributions (Type I). It describes the mathematical formulations and transformations used. - **Equations:** - Several equations are provided to mathematically represent the concepts discussed: Equations (1.2) to (1.8). - Key equations include the integral representations of probability density functions and the use of standard normal distribution functions. - **Mathematical Notations:** - Various symbols and notations such as \( F_{n}(x_{g}) \), \( f_{n}(x)\), \( \Phi(u) \), and standard normal distribution formulas. - **Definitions and Variables:** - \( \mu_N \): Mean value of the original normal distribution. - \( \sigma_N \): Standard deviation of the original normal distribution. - \( \Phi \): Distribution function of the standardized normal distribution. #### **Contextual Significance:** - **Overall Relevance:** - This page serves an educational purpose, likely within a technical or statistical manual. It aims to educate readers on the mathematical foundations of probability distributions and their associated functions. It contributes detailed theoretical discussions relevant for applications in statistics, engineering, or quality control processes. #### **Diagram and Chart Analysis:** - **Absence of Diagrams and Charts:** - This document page does not contain any diagrams, charts, or graphical data. The analysis is purely textual and mathematical. #### **Process Descriptions:** - **Described Processes:** - The text details the process of deriving and using the probability density function for the standardized normal distribution. - It also describes the convolution process used to obtain the Type I absolute value distribution. #### **Perspective and Composition:** - **Textual Layout:** - The text is structured in a formal and precise layout, typical of academic or technical documentation. - Equations are numbered sequentially and embedded within the flowing explanatory paragraphs. #### **Localization and Attribution:** - **Single Image Analysis:** - This document comprises a single page and therefore is treated as 'Image 1'. - All text and mathematical content are attributed to this single image. ### Summary: The document page analyzed is a technical or academic text focused on probability distributions, specifically the normal distribution and Type I absolute value distribution. It includes detailed mathematical explanations and formulas, providing an in-depth educational resource for understanding these statistical concepts. The text layout is clear and formal, suitable for readers with some background in mathematics or statistics. This analysis showcases the document's role in conveying complex mathematical ideas with precision and clarity. #################### File: VW%2010130_EN%281%29.pdf Page: 6 Context: # Figure 3 - Density Function of the Type I Absolute Value Distribution with Different Zero Point Shifts Figure 3 shows density functions that result from convolution of the density of the normal distribution at different zero point shifts. ![Figure 3](image_link) ## Mean Value and Variance of the Type I Absolute Value Distribution The mean value and variance of the type I absolute value distribution are: \[ \alpha = x_N \left( \frac{ \xi_N }{ \sigma_N } - \frac{ \xi_N }{ \sigma_N } \right) \cdot \frac{2 \cdot \sigma_N}{\sqrt{2\pi}} \cdot e^{-\frac{ \xi_N^2 }{2}} \tag{1.9} \] \[ \sigma^2 = \sigma_N^2 + \kappa_N^2 \tag{1.10} \] For the case of a zero point shift \(\mu_N = 0\), the following results from (1.9) and (1.10): \[ \alpha = \frac{2 \cdot \sigma_N}{\sqrt{2\pi}} \tag{1.11} \] \[ \sigma^2 = \left( \frac{ t - 2 }{t} \right) \sigma^2_h \tag{1.12} \] As Figure 3 shows, with increasing zero point shift, the type I absolute value distribution approaches a normal distribution. Thus for the case \[ \frac{\alpha}{\sigma} \approx 3 \tag{1.13} \] the type I absolute value distribution can be replaced with a normal distribution with good approximation. Image Analysis: ### Analysis of the Visual Content: **Localization and Attribution:** - **Image Number:** Image 1 - **Position:** Singular image on the provided page. **Text Analysis:** - **Text Detected:** - **Page Header:** "Page 6 VW 101 30:2005-02" - **Title and Figure Description:** - "Figure 3 shows density functions that result from convolution of the density of the normal distribution at different zero point shifts." - "Figure 3 - Density function of the type I absolute value distribution with different zero point shifts" - **Mathematical Equations:** - Mean value and variance equations: \[ \alpha = x_{N} \left( \Phi \left( \frac{x_{N}}{\sigma_{N}} \right) - \Phi \left( \frac{- x_{N}}{\sigma_{N}} \right) \right) + 2 \cdot \sigma_{N} \cdot \frac{e^{\left( \frac{- x_{N}^2}{2 \cdot \sigma_{N}^2} \right)}}{\sqrt{2 \pi}} \] \[ \sigma^2 = \sigma_{N}^2 + x_{N}^{2} - \alpha^2 \] - For zero point shift \( \mu_N = 0 \): \[ \alpha = 2 \cdot \frac{\sigma_{N}}{\sqrt{2 \pi}} \] \[ \sigma^2 = \left( 1 - \frac{2}{\pi} \right) \cdot \sigma_{N}^2 \] - Approximation as a normal distribution: \[ \frac{\alpha}{\sigma} \approx 3 \] - **Paragraph:** - "As Figure 3 shows, with increasing zero point shift, the type I absolute value distribution approaches a normal distribution. Thus for the case \(\alpha / \sigma \approx 3\), the type I absolute value distribution can be replaced with a normal distribution with good approximation." **Diagram and Chart Analysis:** - **Chart Type:** Line graph - **Axes:** - **Y-Axis:** Probability density - **X-Axis:** Characteristic value - **Curves:** - Labeled \( \mu_N = 0 \) - Labeled \( \mu_N = 10_N \) - Labeled \( \mu_N = 20_N \) - Labeled \( \mu_N = 30_N \) - **Key Insight:** With increasing zero point shift (\(\mu_N\)), the distribution of the type I absolute value approaches that of a normal distribution. **Graph and Trend Analysis:** - **Trends:** - **Probability Density:** Changes as the characteristic value increases. - **Zero Point Shift Effects:** As the zero point shift (\(\mu_N\)) increases, the curve's shape transitions towards that of a normal distribution. - **Data Points & Observations:** - For \( \mu_N = 0 \), the graph shows a higher peak at lower characteristic values. - For \( \mu_N = 30_N \), the graph peak flattens out, indicating more spread out values, which aligns with the transition toward a normal distribution. **Color Analysis:** - **Dominant Colors:** Black and white. The lines representing different \(\mu_N\) values are black, while the background is white. - **Impact:** The high contrast makes the graph easy to read and interpret. **Perspective and Composition:** - **Perspective:** Straightforward view of the graph, head-on perspective. - **Composition:** The graph is centrally placed with titles, descriptions, and equations positioned around it. This arrangement aids in easy reference and comprehension. **Contextual Significance:** - **Overall Message:** The image contributes to explaining how the type I absolute value distribution, typically non-normal, can approximate a normal distribution with increasing zero point shift. - **Relevance:** This is likely part of a mathematical or statistical analysis document explaining different types of probability distributions and their properties. ### Summary: The provided image is a detailed graph illustrating how the density functions of a type I absolute value distribution change with different zero point shifts (\(\mu_N\)). Text explanations and mathematical equations help further elucidate the relationship between these shifts and the distribution's behavior. With increasing \(\mu_N\), the distribution approximates a normal distribution, a significant point emphasized both in the graph and supporting text. The document appears to be highly technical, targeting an audience with knowledge in mathematics or statistics. #################### File: VW%2010130_EN%281%29.pdf Page: 7 Context: # 3.1.3 Type II Absolute Value Distribution (Rayleigh Distribution) The type II absolute value distribution results from the vectorial values of the orthogonal components \( x \) and \( y \) of a two-dimensional normal distribution, where equal standard deviations are assumed for the components. This case is present for many production characteristics in the form of radial deviations from a considered point or a considered axis. The density function and the distribution function of the type II absolute value distribution are generally: \[ f_{B2}(r) = \frac{r}{2 \pi \sigma^2} e^{-\frac{1}{2 \sigma^2} \left( r^2 \right)} \int_{0}^{\frac{2 \pi \cos \alpha}{\sigma^2}} e^{-\frac{z^2}{2 \sigma^2}} d\alpha \quad \text{for } r \geq 0 \tag{1.14} \] \[ F_{B2}(r) = \int_{0}^{r} f_{B2}(r') \, dr' \tag{1.15} \] Where: - \( \sigma_h \): Standard deviation of the orthogonal components \( x \) and \( y \), from which the radial deviation \( r \) of a reference point or reference axis results. - \( z \): Eccentricity: distance between coordinate origin and frequency midpoint. Figure 4 displays density functions of the type II absolute value distribution that result in units of \( \sigma_h \) for different eccentricities. ![Figure 4 - Density functions of the type II absolute value distribution with different eccentricities](link_to_image) Mean value and variance of the type II absolute value distribution are: Image Analysis: ### Image 1 Analysis #### Object Detection and Classification: - The page contains text, equations, and a graph. - **Text:** The majority of the document is composed of paragraphs and section headers explaining the type II absolute value distribution (Rayleigh Distribution). - **Equations:** Mathematical equations and integrals are presented. - **Graph:** A plot with multiple curves is included to illustrate density functions for different eccentricities. #### Scene and Activity Analysis: - The page appears to be from a technical document or academic paper focusing on statistical distributions (Type II absolute value distribution). - The main activities include describing the underlying mathematical theory and illustrating it with a graph. #### Text Analysis: - **Title:** "Type II absolute value distribution (Rayleigh distribution)" - **Content:** The text provides a detailed explanation of the Type II absolute value distribution, using vector values of orthogonal components x and y of a two-dimensional normal distribution. It contains formulas, definitions, and a description of the graph. - **Equations:** Include density functions and integrals for the distribution. - Examples: - \(f_{BZ}(r) = \frac{r}{2 \pi \sigma_x \sigma_y} e^{- \left[ \frac{r^2(x^2 + y^2)}{2 \sigma_x^2 \sigma_y^2} \right]} \cdot 2 \pi \int_0^{2 \pi} e^{- \left[ \frac{2r \cdot cos \alpha}{2 \sigma_x^2 \sigma_y^2} \right]}d \alpha\) - \( F_{BZ}(r_g) = \int_0^{r_g} f_{BZ}(r)d r \) #### Diagram and Chart Analysis: - **Chart:** Figure 4 - "Density functions of the type II absolute value distribution with different eccentricities" - **Axes:** - x-axis: "Characteristic value" (ranges from 0 to 60) - y-axis: "Probability density" - **Curves:** - Four curves labeled as z = 0, z = 10σ_N, z = 20σ_N, and z = 30σ_N showing different distributions with varying eccentricities. - **Key Insight:** - As the eccentricity (z) increases, the peak of the probability density function shifts and changes shape, indicating how the distribution changes with different eccentricities. #### Contextual Significance: - The image is part of an academic paper or technical document discussing statistical distributions. - It contributes to the overall goal of explaining the characteristics and implications of the Type II absolute value distribution. #### Graph and Trend Analysis: - The graph illustrates how different eccentricities affect the density functions of the Type II absolute value distribution. Trends observed include: - Increasing eccentricity results in peak shifts of the probability density. - Higher eccentricity results in a broader distribution of values. #### Anomaly Detection: - No anomalies identified in the image. The content appears coherent and aligned with its purpose. Additional analysis of process flows, process descriptions, type designations, trend interpretations, and tables are not applicable as they are not present in this visual content. #################### File: VW%2010130_EN%281%29.pdf Page: 8 Context: # Page 8 VW 101 30: 2005-02 \[ \mu = \int_{0}^{\infty} f_{2}(r) \cdot r \, dr \tag{1.16} \] \[ \sigma^2 = 2\sigma_N^2 + z^2 - x^2 \tag{1.17} \] For an eccentricity \( z = 0 \), (1.14) and (1.15) density function and distribution function of the Weibull distribution, with the shape parameter value 2 yield \[ f_{2}(r) = \frac{r}{\sigma_H^2} \cdot e^{-\left(\frac{r}{\sigma_H}\right)^{2}} \tag{1.18} \] \[ F_{2}(y) = 1 - e^{-\left(\frac{y}{\sigma_H}\right)^{2}} \tag{1.19} \] and from them, in turn, mean value and variance \[ \mu = \sigma_H \cdot \sqrt{\frac{\pi}{2}} \tag{1.20} \] \[ \sigma^2 = \left(2 - \frac{\pi}{2}\right) \cdot \sigma_N^2 \tag{1.21} \] As Figure 4 shows, with increasing eccentricity, the type II absolute value distribution approaches a normal distribution. Thus for the case \[ \frac{\mu}{\sigma} \geq 6 \tag{1.22} \] the type II absolute value distribution can be replaced with a normal distribution with good approximation. ## 3.2 Determination of Capability The capability indexes \( C_p \) and \( C_{pk} \) indicate how well the production results comply with the tolerance zone of a considered characteristic. In this process, only the production dispersion is taken into consideration in the \( C_p \) value. The production location is taken into consideration by the \( C_{pk} \) value. Because of this, on the one hand, there can be an expression of what value is possible in an ideal production location and, on the other, a comparison of the two values makes it possible to express how much the production location deviates from the specified value. The higher the capability indexes determined, the better the production. There are different evaluation formulas, which have to be selected appropriately in the individual case, for determining the capability indexes. Since the determination of the capability indexes can only be carried out using random sample values, the results only represent estimates of the values for the population which are to be determined and are thus identified by a roof symbol[^1]. [^1]: The identification of the estimated capability indexes by a roof symbol is only important for understanding the theory, so they can be dispensed with during the evaluations in practice. Image Analysis: ### Analysis of the Attached Visual Content #### Image 1 1. **Localization and Attribution:** - **Image Number:** Image 1 - **Location:** Entire page 2. **Text Analysis:** - **Detected Text:** - Mathematical formulas and equations (e.g., \(\alpha = \int_0^r \bar{f}_{BZ}(r) \cdot r \cdot dr\) in Equation 1.16 and \( \sigma^2 = 2\bar{\sigma}_N^2 + z^2 - x^2 \) in Equation 1.17). - Description of the Weibull distribution and related concepts. - Discussion about production capability and evaluation formulas. - Section title **3.2 Determination of capability**. - Footnote discussing the importance of the estimated capability indexes symbolized by a roof symbol. - **Content Analysis:** - This section explains the mathematical definitions and properties of distributions, specifically the Weibull distribution and its related equations. - The text describes how to determine production capability indexes (\(c_m\) and \(c_{mk}\)) depending on the production location and tolerance zone. - The formulas underline the transition from Type II absolute value distribution to a normal distribution with increasing eccentricity. - The capability indexes (\(c_m\) and \(c_{mk}\)) are important for evaluating how well the production results adhere to the tolerance zone of a characteristic. These indexes consider both production dispersion and location deviation. 3. **Diagram and Chart Analysis:** - There are no explicit diagrams or charts present in this image; however, references to figures (e.g., Figure 4) and distribution transformations are mentioned. 4. **Contextual Significance:** - The content of this page is highly technical and it likely contributes to a broader discussion in a document or textbook related to statistical quality control or reliability engineering. - The mathematical and textual explanations about distribution types and production capability are crucial for understanding how well a manufacturing process performs relative to specified quality standards. - The detailed equations and explanations would be significant for those studying or working in fields involving statistical analysis, quality control, or manufacturing. 5. **Perspective and Composition:** - **Perspective:** - The perspective is straightforward, presenting the text and equations in a structured format typical of technical documents. - **Composition:** - The composition is formal and methodical, with clear sectioning and numbering of equations for easy reference. - The structured layout allows readers to follow the logical flow of the information presented. ### Key Insights: - The document discusses in detail the mathematical formulation and application of the Weibull distribution. - It transitions from theoretical distribution properties to practical application in determining manufacturing capabilities. - The capability indexes (\(c_m\) and \(c_{mk}\)) are critical for assessing the quality of manufacturing processes against specified tolerance zones. - The structure and composition provide clarity and facilitate the understanding of complex statistical concepts relevant to production quality. #################### File: VW%2010130_EN%281%29.pdf Page: 9 Context: # 3.2.1 Determination of capability for defined distribution models ## 3.2.1.1 Capability indexes For a production characteristic which is to be examined and whose random sample values are not in contradiction to a theoretically expected distribution model, the capability indexes are estimated in a manner appropriate to the respective case (see also examples 1 and 2 in Section 5) according to the following formulas: ### Capability indexes for characteristics with two-sided tolerance zones (according to DIN 55319, measuring method M4), e.g. for length dimension: \[ \hat{c}_m = \frac{G_o - G_u}{X_{99.865\%} - X_{0.135\%}} \] \[ \hat{c}_{mk} = \min \left( \frac{G_o - \bar{x}}{X_{99.865\%} - \bar{x}^2}, \frac{\bar{x} - G_u}{\bar{x} - X_{0.135\%}} \right) \] ### Capability indexes for characteristics with upper limited tolerance zone and natural lower limit value zero, e.g. for radial runout deviation: \[ \hat{c}_m = \frac{G_o}{X_{99.865\%} - X_{0.135\%}} \] \[ \hat{c}_{mk} = \frac{G_o - \bar{x}}{X_{99.865\%} - \bar{x}} \] ### Capability indexes for characteristics with lower limited tolerance zone only, e.g. for tensile strength: \[ \hat{c}_{mk} = \frac{\bar{x} - G_u}{\bar{x} - X_{0.135\%}} \] where - \(G_o, G_u\) : Upper and lower limiting value, respectively - \(\bar{x}\) : Estimated mean value - \(X_{0.135\%}, X_{99.865\%}\) : Estimated values for dispersion range limits (quantiles, below which the specified percentage \(p\) of measured values lie) Image Analysis: ### Detailed Examination of the Visual Content #### 1. Localization and Attribution: - **Image Identification:** - Single image on the page. - Identified as **Image 1**. #### 4. Text Analysis: - **Detected Text:** - Title: "3.2.1 Determination of capability for defined distribution models" - Subsection: "3.2.1.1 Capability indexes" - Descriptive text: Discusses the determination of capability indexes for production characteristics. - Formula descriptions and equations: - \[\hat{c}_{m} = \frac{G_o - G_u}{\hat{x}_{99.865\%} - \hat{x}_{0.135\%}}\] (Equation 2.1) - \[\hat{c}_{mk} = \text{min}\left\{\frac{G_o - z * \hat{x}_{99.865\%} - z * \hat{x}_{0.135\%}}{\hat{x}_{99.865\%} - z * \hat{x}_{0.135\%}}, \frac{z * \hat{G}_o}{z * \hat{x}_{0.135\%}}\right\}\] (Equation 2.2) - and several more equations for different types of capability indexes. - Terminology definitions: - \(G_o, G_u\): Upper and lower limiting values, respectively. - \(\hat{x}\): Estimated mean value. - \(\hat{x}_{0.135\%}, \hat{x}_{99.865\%}\): Estimated values for dispersion range limits for specific percentage points. #### 5. Diagram and Chart Analysis: - **Formula presentation:** - The image contains formulas (equations), but no graphical charts. - These formulas are methods for calculating capability indexes for various tolerance zones based on statistical measurements. #### 11. Metadata Analysis: - **Textual Metadata:** - Page number: "Page 9" - Document identifier: "VW 101 30: 2005-02" #### 12. Graph and Trend Analysis: - **Formulas and Relationships:** - Each formula corresponds to a specific calculation for capability indexes of production characteristics with different tolerance zones. - These mathematical relationships help in the determination of process capabilities in quality control. #### 13. Graph Numbers: - **Equation Numbers:** - Equations are clearly numbered (e.g., 2.1, 2.2, 2.3, 2.4, and 2.5), aiding in reference and context. ### Summary **Image 1** presents advanced statistical formulas for calculating capability indexes in the context of production quality control, as defined by specific tolerance zones. Each formula is detailed with precise variables and their definitions, emphasizing the importance of understanding the variations and limits in a production setting. The text is highly technical, suitable for professionals in quality control and manufacturing engineering, seeking to apply these concepts to ensure product and process reliability. There's a clear structure to the document section, starting from general determinations to specific cases, facilitating focused understanding of each type of capability index calculation. #################### File: VW%2010130_EN%281%29.pdf Page: 10 Context: # 3.2.1.2 Estimation of the statistics The statistics mean value \( \bar{x} \) and standard deviation \( \sigma \) of a population can be estimated, independently of the distribution model, from the measured values of a random sample according to expectation, by \[ \bar{x} = \frac{1}{n_e} \sum_{i=1}^{n_e} x_i \tag{2.6} \] \[ \sigma^2 = s^2 = \frac{1}{n_e - 1} \sum_{i=1}^{n_e} (x_i - \bar{x})^2 \tag{2.7} \] where - \( n_e = n - n_a \): effective random sample size - \( n \): defined random sample size - \( n_a \): number of outliers - \( x_k \): k-th characteristic value In the case of data to be evaluated in the form of a frequency distribution of classified measured values (e.g., from manual recordings (tally) in a class subdivision of the value range), the statistics \( \mu \) and \( \sigma \) can be estimated by \[ \bar{x} = \frac{1}{n_e} \sum_{k=1}^{K_{max}} a_k \cdot x_k \tag{2.9} \] \[ \bar{s} = \sqrt{\frac{1}{n_e - 1} \sum_{k=1}^{K_{max}} a_k \cdot (x_k - \bar{x})^2} \tag{2.10} \] where - \( x_k \): mean value of the k-th class - \( a_k \): absolute frequency of the measured values in the k-th class (without outliers) - \( K \): maximum number of measured value classes # 3.2.1.3 Estimation of the dispersion range limits The dispersion range limits depend on the distribution model and are estimated as follows: ## Dispersion range limits for normal distribution: If the normal distribution model is the fitting distribution model, the values \( \bar{x} \) and \( \sigma \) determined according to (2.6) and (2.7) or (2.9) and (2.10) respectively result as estimated values for the dispersion range limits \[ \hat{x}_{0.965} \quad \hat{x}_{0.0135} = \bar{x} \pm 3\sigma \tag{2.11} \] which, when used in formulas (2.1) and (2.2), result in the classical formulas for calculating the capability indexes (see also example 1 in Section 5). Image Analysis: ### Image Analysis #### Localization and Attribution - **Image 1:** The entire page appears to be a single image where text and mathematical formulas dominate. #### Text Analysis - **Text Content:** - **Section Heading:** "3.2.1.2 Estimation of the statistics" - **Explanatory Text:** The text explains methods to estimate statistics, like the mean value (x̅) and standard deviation (σ), using measured values from a random sample. - **Mathematical Formulas:** - \[ \hat{x} = x̅ = \frac{1}{n_e} \sum_{i=1}^{n_e} x_i \] (Equation 2.6) - \[ \hat{\sigma^2} = s^2 = \frac{1}{n_e - 1} \sum_{i=1}^{n_e} (x_i - x̅)^2 \] (Equation 2.7) - Descriptive variables n_e, n, n_A, x_i are explained. - **Frequency Distribution:** Methods involving frequency distribution of classified measured values and calculating mean and standard deviation. - Additional formulas: Equations (2.9) and (2.10) for estimating statistics using frequency distribution. - **Section 3.2.1.3:** Estimation of dispersion range limits. - **Dispersion Range Limits for Normal Distribution:** Formula: - \[ \hat{x}_{0.99865 \text{ to } 0.00135} = \hat{x} \pm 3\hat{\sigma} \] (Equation 2.11) #### Diagram and Chart Analysis - **Diagrams:** No diagrams or charts are present on the page. #### Scene and Activity Analysis - No specific scene or activity is depicted beyond the presentation of formulas and explanatory text. #### Metadata Analysis - No metadata information is provided or extracted from the image. #### Content Analysis - The content is highly technical and related to statistical estimations in quality control and process management, indicating an instructional or procedural document related to measurement systems or data evaluation. ### Conclusion The image is a technical document page explaining statistical methods for estimating mean value and standard deviation from a random sample, and how to estimate dispersion range limits based on normal distribution. The principal focus is on mathematical formulas and their explanation. #################### File: VW%2010130_EN%281%29.pdf Page: 11 Context: # Dispersion Range Limits of the Type I Absolute Value Distribution To determine the dispersion range limits for a type I absolute value distribution, the statistics \( \mu \) and \( \sigma \) are estimated according to formulas (2.6) and (2.7) or (2.9) and (2.10) respectively. For the case \( \frac{z}{\delta} < 3 \), the estimated statistics \( \mu \) and \( \sigma \) are used to estimate the parameter values \( \mu_N \) and \( \sigma_N \), to be determined for the type I absolute value distribution to be fitted, in the following manner: Equation (1.9) yields the function \[ \frac{\partial \hat{N}}{\partial N} = \psi_{N} \left( \frac{\hat{z}_{N}}{\partial N} - \frac{\hat{z}_{N}}{\partial N} \right) + \left( \frac{\hat{z}_{N}}{\partial N} - \frac{\hat{z}_{N}}{\partial N} \right) + 2 \left( \frac{ \partial \hat{z}_{A}}{ \partial N} \right)^3 \] With equation (1.10), this yields the following function \[ \frac{\partial \hat{N}}{\partial N} = \psi_{N} \left( \frac{\hat{z}_{N}}{\partial N} \right) \sqrt{1 + \left( \frac{\hat{z}_{N}}{\partial N} \right)^2} - \left( \psi_{N} \left( \frac{\hat{z}_{N}}{\partial N} \right) \right)^2 \] Equations (1.11) and (1.12) result in the condition \[ \frac{\partial \hat{N}}{\partial N} = \frac{2}{\sqrt{\pi}-2} = 1.3236 \] Under the condition (2.14), the parameter values to be determined for the type I absolute value distribution can be estimated using \[ \hat{\sigma}_N = \hat{\sigma} \left( \frac{1 + \left( \frac{z}{\hat{\sigma}} \right)^2}{1 + \left( \xi_{N} \left( \frac{z}{\hat{\sigma}} \right) \right)^2} \right) \] \[ \hat{z}_{N} = \xi_{B} \left( \frac{z}{\hat{\sigma}} \right) \cdot \hat{\sigma}_N \] where \( \xi_{B} \left( \frac{z}{\hat{\sigma}} \right) \) is the inverse function of (2.13). In the case where the ratio \( \frac{z}{\sigma} \) is lower than the limit value 1.3236 from condition (2.14) because of random deviations of the random sample statistics, the ratio \( \frac{z}{\sigma} \) is set to this limit value, at which the following parameter values result: \[ \hat{z}_{N} = 0 \] and according to formula (1.12) \[ \hat{\sigma}_N = \frac{\pi}{\sqrt{2}} \cdot \hat{\sigma} = 1.659 \cdot \hat{\sigma} \] Image Analysis: ## Analysis of the Attached Image ### Image 1 #### 1. Localization and Attribution - The document comprises a single page labeled as "Page 11". - Title: "Dispersion range limits of the type I absolute value distribution" - Document ID: VW 101 30: 2005-02 #### 4. Text Analysis - **Title:** "Dispersion range limits of the type I absolute value distribution" - Indicates the subject matter focuses on the statistical limits for type I absolute value distribution. - **Equations:** - **Equation (2.12):** Presents a function derived from Equation (1.9). - **Equation (2.13):** A resulting function utilizing the specified variables. - **Equations (1.11) and (1.12):** Lead to a resultant condition in Equation (2.14) where \( \frac{z}{\hat{\sigma}} = \frac{2}{\sqrt{\pi - 2}} = 1.3236 \). - **Equation (2.15):** Provides a method to estimate the parameter values. - **Equation (2.16):** Explains the parameter \( \xi_{\beta} \). - **Equation (2.17):** States the parameter values for specific conditions. - **Significant Mathematical Expressions:** - \(\mu_{X}\) and \(\sigma_{X}\): Parameters being determined for the type I absolute value distribution fit. - \(\hat{\sigma}\): Estimated standard deviation. - \(\frac{z}{\hat{\sigma}} = \frac{2}{\sqrt{\pi - 2}} = 1.3236\): Specifies a limitation based on Equation (2.14). - **Context and Explanation:** - The mathematical discourse explains how to calculate the dispersion range limits for the type I absolute value distribution. - Provides formulas for determining statistical values and conditions for setting certain limits when random deviations occur. #### 12. Graph and Trend Analysis - **Equations and Relationships:** - Parameter estimation relies on complex mathematical functions and equations to fit statistical data to a type I absolute value distribution. #### 13. Graph Numbers: - **Equations:** - (2.12) to (2.17) span various components of the formulae and their application under different conditions. #### 16. Ablaufprozesse (Process Flows): - Describes the quantitative process of deriving limits and distributing parameter estimations. #### 18. Prozessbeschreibungen (Process Descriptions): - Detailed steps on how to handle the scenario when the ratio \( \frac{z}{\hat{\sigma}} \) falls below the predefined limit. #### 20. Trend and Interpretation: - Interpretation of these mathematical relationships and equations shows how one can manage random deviations in sample statistics to stick within specified limits. ### Summary Statement This page of the document provides a series of mathematical derivations and equations relevant to determining the dispersion range limits for the type I absolute value distribution. The text includes detailed descriptions, equations, and conditions essential for understanding how to estimate statistical parameters accurately within predefined limits. The content is dense with mathematical formulae and processes, making it valuable for professionals or academics dealing with statistical distributions and parameter estimation techniques. #################### File: VW%2010130_EN%281%29.pdf Page: 12 Context: # VW 101 30: 2005-02 The connection between the parameter values \( \mu_H \) and \( \sigma_H \) of the type I absolute value distribution and the statistics \( \mu \) and \( \sigma \) is shown graphically in Figure 5, related to \( \sigma \). ![Figure 5 - Relative parameter values of the type I absolute value distribution in relationship to the relative location](figure5.png) For the fitted type I absolute value distribution, the dispersion range limits can then be determined numerically and their relationships with the relative location are shown in Figure 6. ![Figure 6 - Relative dispersion range limits of the type I absolute value distribution in relationship to the relative location](figure6.png) 1. Illustrations, graphics, photographs and flow charts were adopted from the original German standard, and the numerical notation may therefore differ from the English practice. A comma corresponds to a decimal point, and a period or a blank is used as the thousands separator. Image Analysis: ### Analysis of Attached Visual Content #### 1. **Localization and Attribution:** - **Image 1 (Top Graph):** - It is located at the upper part of the page, titled "Figure 5." - **Image 2 (Bottom Graph):** - It is located at the lower part of the page, titled "Figure 6." #### 2. **Object Detection and Classification:** - **Image 1:** - Objects: Graph, axes, data points, and labels. - **Image 2:** - Objects: Graph, axes, data points, and labels. #### 3. **Scene and Activity Analysis:** - **Image 1:** - Scene: A graph representing the relationship between relative distribution parameter (\(\sigma_{\lambda}\) / \(\sigma\), \(\sigma_{H}\) / \(\sigma\)) and relative location (\(\mu\) / \(\sigma\)). - Activity: Visualization of parameter values. - **Image 2:** - Scene: A graph illustrating the relative dispersion range limits (\(X_{99.865%}\) / \(\sigma\), \(X_{0.135%}\) / \(\sigma\)) in relation to the relative location (\(\mu\) / \(\sigma\)). - Activity: Visualization of dispersion range limits. #### 4. **Text Analysis:** - **Image 1:** - Titles and Labels: "Figure 5 - Relative parameter values of the type I absolute value distribution in relationship to the relative location," "Relative distribution parameter," "Relative location (\(\mu\) / \(\sigma\))," and data labels (\(\sigma_{\lambda}\) / \(\sigma\), \(\sigma_{H}\) / \(\sigma\)). - Significance: Indicates the correlation and trends for statistical parameter values. - **Image 2:** - Titles and Labels: "Figure 6 - Relative dispersion range limits of the type I absolute value distribution in relationship to the relative location," "Relative scatter range limit," "Relative location (\(\mu\) / \(\sigma\))," and data labels (\(X_{99.865%}\) / \(\sigma\), \(X_{0.135%}\) / \(\sigma\)). - Significance: Shows how the range limits change with the location parameter. #### 11. **Graph and Trend Analysis:** - **Image 1:** - Axes and Scales: - X-Axis: Labeled "Relative location (\(\mu\) / \(\sigma\))" ranging from 1.2 to 3.0. - Y-Axis: Labeled "Relative distribution parameter," ranging from 0.0 to 3.5. - Trends: As \(\mu/\sigma\) increases, both \(\sigma_{\lambda}/\sigma\) and \(\sigma_{H}/\sigma\) show distinct trends, with \(\sigma_{\lambda}/\sigma\) increasing more sharply than \(\sigma_{H}/\sigma\). - **Image 2:** - Axes and Scales: - X-Axis: Labeled "Relative location (\(\mu\) / \(\sigma\))" ranging from 1.2 to 3.0. - Y-Axis: Labeled "Relative scatter range limit," ranging from 0.0 to 7.0. - Trends: With increasing \(\mu/\sigma\), \( X_{99.865%} /\sigma \) and \( X_{0.135%}\) /\(\sigma\) exhibit varied dispersion range limits, indicating different behavior at the extremes of the distribution. #### 5. **Text Analysis:** - **Extracted Text:** - General Description: Provides interpretations of the graphs and explains the graphical representation of relationships for different parameter values. - Footnote: Explains terminological and notational differences in translations, specifying visualizations used in the document. #### 13. **Graph Numbers:** - **Image 1:** - Data Points: - X = 1.4, Y (\(\sigma_{\lambda}/\sigma\)) ≈ 1.9 - X = 1.4, Y (\(\sigma_{H}/\sigma\)) ≈ 0.6 - X = 3.0, Y (\(\sigma_{\lambda}\sigma\)) ≈ 2.9 - X = 3.0, Y (\(\sigma_{H}/\sigma\)) ≈ 1.7 - **Image 2:** - Data Points: - X = 1.4, Y ((\(X_{99.865%}\) / \(\sigma\))) ≈ 4.2 - X = 1.4, Y ((\(X_{0.135%}\) / \(\sigma\))) ≈ 2.0 - X = 3.0, Y ((\(X_{99.865%}\) / \(\sigma\))) ≈ 5.9 - X = 3.0, Y ((\(X_{0.135%}\) / \(\sigma\))) ≈ 3.1 #################### File: VW%2010130_EN%281%29.pdf Page: 13 Context: For direct determination of the statistics μ_N and σ_N from the statistics μ and σ, for \(1.3236 \leq \frac{σ}{d} < 3\) the following approximation can also be used as an inverse function of (2.13) with adequate precision (error related to less than 0.01): \[ \hat{σ}_{\bar{d}} = 1.64 \left( \frac{d}{\bar{d} - 1.3236} \right)^{0.268} + 0.634 \left( \frac{d}{\bar{d} - 1.3236} \right)^{1.105} \tag{2.18} \] In addition, the determination of the dispersion range limits for \(1.3236 \leq \frac{σ}{d} < 3\) is carried out directly with the use of the following approximation (error related to less than 0.02): \[ \hat{X}_{0.8696} = -2.47 \left( \frac{σ}{\bar{d} - 1.3236} \right)^{0.67} + 2.505 \left( \frac{σ}{\bar{d} - 1.3236} \right) + 5.3711 \tag{2.19} \] \[ \hat{X}_{0.1316} = 0.018 \left( \frac{σ}{\bar{d} - 1.3236} \right) + 0.0028 \] For \(\frac{σ}{d} \geq 3\) the calculation of the dispersion range limits is carried out according to formula (2.11). ## Dispersion Range Limits of the Type II Absolute Value Distribution: To determine the dispersion range limits for a type II absolute value distribution (see also example 2 in Section 5) first the statistics μ and σ are estimated according to formulas (2.6) and (2.7) or (2.9) and (2.10) respectively. For the case \(\frac{σ}{d} < 6\), the estimated statistics μ and σ are then used to estimate the parameter values z and σ_θ to be determined of the type II absolute value distribution to be fitted, in the following manner: Equations (1.14) and (1.16) yield the function: \[ \frac{σ}{\bar{d}} = \Psi_{g2} \left( \frac{σ}{d_N} \right) \frac{1}{\sqrt{2\pi}} e^{-\frac{1}{2} \left( \frac{σ}{d_N} \right)^2} \int_0^{z} v^2 e^{- \frac{1}{2} v^2} \frac{2}{σ} e^{-\frac{z^2}{2}} dα \, dv \tag{2.20} \] where \[ v = \frac{σ}{d_N} \tag{2.21} \] With equation (1.17), this yields the following function: \[ \hat{σ} = \Psi_{g2} \left( \frac{σ}{d_N} \right) \frac{\Psi_{g2} \left( \frac{σ}{d_N} \right)}{\sqrt{2} \left( \frac{σ}{d_N} \right)^2 - \Psi_{g2} \left( \frac{σ}{d_N} \right)} \tag{2.22} \] Equations (1.20) and (1.21) result in the condition: \[ \frac{σ}{\bar{d}} = \frac{\pi}{4 - π} = 1.9131 \tag{2.23} \] Image Analysis: 1. **Localization and Attribution:** - The document contains one image, located in the entirety of the page. It will be referred to as **Image 1**. 2. **Object Detection and Classification:** - **Image 1** contains textual content, mathematical equations, and notations. 3. **Text Analysis:** - **Image 1** contains the following notable text segments: - **Top Header**: "Page 13 / VW 101 30: 2005-02" - **Section Title**: "For direct determination of the statistics μ_N and σ_N... (error related to less than 0.01)" - **Equations**: A total of eight equations, labeled (2.18) to (2.23). - **Subsection Heading**: "Dispersion range limits of the type II absolute value distribution" - **Additional text** discussing the process of determining dispersion range limits and related calculations. - Significant Textual Content: - **Equations (2.18) - (2.23)** present various mathematical models and formulas related to the dispersion range limits and calculations of statistics μ_N and σ_N. - **Contextual Explanation**: Details regarding error approximation and calculations for different scenarios based on the parameter range of ξ/δ. 4. **Diagram and Chart Analysis:** - There are no diagrams or charts in this image. 5. **Product Analysis:** - There are no products depicted in this image. 6. **Anomaly Detection:** - No noticeable anomalies or unusual elements are present in the textual and mathematical content. 7. **Color Analysis:** - The image is in black and white, adding a professional and formal look. 8. **Perspective and Composition:** - The perspective is a straight-on view typical for document scans. - The composition is methodical and neatly organized with headings, subheadings, and equations in sequential order. 9. **Contextual Significance:** - The text and equations are part of a technical document concerning statistical methods and distribution calculations. It contributes to explaining complex statistical procedures and their precise determination, likely intended for an audience with a background in statistics or related fields. 10. **Graph and Trend Analysis:** - No graphs are present in this image. 11. **Tables:** - There are no tables included in this image. 12. **Additional Aspects:** - **Ablaufprozesse (Process Flows)**: The process described involves calculating statistical parameters and dispersion limits. - **Prozessbeschreibungen (Process Descriptions)**: Detailed steps for determining statistics μ_N and σ_N and dispersion range limits are provided. - **Typen Bezeichnung (Type Designations)**: The document references "type II absolute value distribution," indicating a particular statistical distribution type. - **Trend and Interpretation**: No specific trends are described, but the detailed equations and explanations suggest a robust theoretical approach to statistical analysis. #################### File: VW%2010130_EN%281%29.pdf Page: 14 Context: # Page 14 VW 101 30: 2005-02 Under the condition (2.23), the parameter values to be determined of the type II absolute value distribution can be estimated using $$ d_N = \bar{d} \cdot \left[ 1 + \frac{z^2}{2 \left( \frac{\sigma}{\bar{d}} \right)^2} \right] $$ (2.24) $$ \bar{z} = \frac{\sigma}{\bar{d}} \cdot d_N $$ (2.25) where $$ \epsilon_{Z2} \left( \frac{\bar{z}}{\bar{d}} \right) : \text{inverse function of (2.22)} $$ In the case where the ratio $\frac{\bar{z}}{d}$ is lower than the limit value 1.9131 from condition (2.23) because of random deviations of the random sample statistics, the ratio $\frac{\bar{z}}{d}$ is set to this limit value, at which the following parameter values result: $$ \bar{z} = 0 \quad \text{and according to formula (1.21)} $$ $$ d_N = \frac{2}{\sqrt{4 - \pi}} \cdot \bar{d} = 1.526 \cdot \bar{d} $$ (2.26) The connection between the parameter values $z$ and $d_N$ of the type II absolute value distribution and the statistics $\mu$ and $\sigma$ is shown graphically in Figure 7, related to $\sigma$. ![Figure 7 - Relative parameter values of the type II absolute value distribution in relationship to the relative location](figure7.png) 1) Illustrations, graphics, photographs, and flow charts were adopted from the original German standard, and the numerical notation may therefore differ from the English practice. A comma corresponds to a decimal point, and a period or a blank is used as the thousands separator. Image Analysis: ### Comprehensive Examination of the Provided Visual Content #### 1. Localization and Attribution - **Page:** Single page (Page 14) - **Image Numbering:** - **Image 1:** Positioned at the bottom of the page #### 3. Scene and Activity Analysis - **Text Analysis:** - The page contains mathematical equations and explanations related to statistical distributions. - The text explains conditions, parameter values, and formulas concerning the type II absolute value distribution. #### 4. Text Analysis - **Extracted Text:** - The text includes formulas, explanations, and theoretical derivations. - Key extracted formulae: - \(\sigma_N = \bar{\sigma} \cdot \left(1 + \left(\frac{\hat{z}}{\bar{\sigma}}\right)^2\right) \cdot \frac{1}{\sqrt{2 + \left(\xi_{BZ} \left(\frac{\hat{z}}{\bar{\sigma}}\right)\right)^2}}\) (2.24) - \(\hat{z} = \xi_{BZ} \left(\frac{\hat{\sigma}}{\bar{\sigma}}\right)^2 \cdot \sigma_N\) (2.25) - **Significance:** - The equations detail statistical methods to determine parameters of the type II absolute value distribution. The definitions and derived values are significant for statisticians and researchers analyzing random samples. #### 5. Diagram and Chart Analysis - **Image 1 (Figure 7):** - **Description:** - Title: "Relative parameter values of the type II absolute value distribution in relationship to the relative location." - **Axes:** - **X-axis:** Labeled as "Relative location μ / σ" with a range from 1.5 to 6.0 - **Y-axis:** Labeled as "Relative distribution parameter" with a range from 1 to 7 - **Graph Features:** - Two curves representing \( \sigma_N / \sigma \) and \( Z / \sigma \) - From the legend, \( Z / \sigma \) increases more steeply compared to \( \sigma_N / \sigma \) - **Insights:** - The graph visualizes the relationship between parameter values Z and σN of type II absolute value distributions related to the ratio μ / σ. - The curves indicate how these relative parameters change with varying values of relative location. #### 7. Anomaly Detection - **Anomalies:** - None detected. #### 8. Color Analysis - **Dominant Colors:** - The page predominantly uses black and white, common for academic and technical documents. - The graph lines and labels maintain a simple, clear distinction to ensure readability. #### 9. Perspective and Composition - **Perspective:** - The perspective is straightforward, primarily for academic review purposes. - **Composition:** - The composition aligns text explanations with corresponding visual aids (graph) to facilitate understanding. - The mathematical text is structured in paragraphs with referenced equations for logical flow. #### 12. Graph and Trend Analysis - **Trends in Figure 7:** - The parameter \( \sigma_N / \sigma \) remains above 1 and increases slightly as \( μ / σ \) increases. - The parameter \( Z / \sigma \) shows a steeper linear growth with increasing \( μ / σ \). - **Interpretations:** - Both parameters suggest increasing trends as the relative location parameter grows, indicating a relationship between statistical dispersion and location metrics. #### 13. Graph Numbers - **Data Points:** - Specific values are not tagged along the curves. The data interpretation relies on visual inference. #### Additional Aspects - **Process Flows, Process Descriptions, Type Designations, and Tables:** - Not applicable or absent in this visual content. ### Summary The provided visual content primarily revolves around statistical analysis and parameter determination for the type II absolute value distribution. The equations and graph presented target academic and research-oriented audiences, providing insights into the behavior of certain statistical parameters in relation to location metrics. The clear structure and detailed equations ensure the content's usability for educational purposes. #################### File: VW%2010130_EN%281%29.pdf Page: 15 Context: # Relative Dispersion Range Limits of the Type II Absolute Value Distribution For the fitted type II absolute value distribution, the dispersion range limits can then be determined numerically, and their relationships with the relative location are shown in Figure 8. ![Figure 8 - Relative dispersion range limits of the type II absolute value distribution in relationship to the relative location](path/to/image) ## Direct Determination of Statistics For direct determination of the statistics \( z \) and \( \sigma_v \), from the statistics \( \mu \) and \( \sigma \), for \( 1.9131 \leq \frac{\sigma}{\sigma} \leq 6 \), the following approximation can also be used as an inverse function of (2.22) with adequate precision (error related to \( o \) less than 0.02): \[ \xi_{82} \left( \frac{\sigma}{\sigma} \right) \geq 2.1 \left( \frac{\sigma}{\sigma} - 1.9131 \right)^{0.913} + 0.466 \left( \frac{\sigma}{\sigma} - 1.9131 \right)^{1.22} \tag{2.27} \] In addition, the determination of the dispersion range limits for \( 1.9131 \leq \frac{\sigma}{\sigma} \leq 6 \) is carried out directly with the use of the following approximation (error related to \( o \) less than 0.03): \[ \xi_{89.8656} = -1.64 \left( \frac{\sigma}{\sigma} - 1.9131 \right)^{0.62} + 2.075 \left( \frac{\sigma}{\sigma} - 1.9131 \right)^{0.9} + 5.5485 \tag{2.28} \] \[ \xi_{X0.1356} = 2.6 \cdot \exp\left( -\left( \frac{\sigma}{\sigma} - 1.7031 \right)^{0.8} \right) + 1.425 \left( \frac{\sigma}{\sigma} - 1.9131 \right)^{0.9} - 2.1206 \] For \( \frac{\sigma}{\sigma} \geq 6 \), the calculation of the dispersion range limits is carried out according to formula (2.11). --- **Footnotes:** 1. Illustrations, graphics, photographs, and flow charts were adopted from the original German standard, and the numerical notation may therefore differ from the English practice. A comma corresponds to a decimal point, and a period or a blank is used as the thousands separator. Image Analysis: ### Analysis of the Attached Visual Content #### 1. Localization and Attribution: - **Image Number**: Image 1 - **Location on Page**: Center of the page #### 2. Object Detection and Classification: - **Objects Detected**: - **Graph**: Chart displaying a relationship between "Relative location μ/σ" and "Relative scatter range limit". - **Text**: Mathematical equations, descriptive text, footnotes. #### 3. Scene and Activity Analysis: - **Scene Description**: The page contains a graph illustrating relative dispersion range limits for a type II absolute value distribution. Below the graph, there are mathematical equations and explanations regarding the calculations. - **Main Actions**: The graph visualization, mathematical formulations, and explanatory text. #### 4. Text Analysis: - **Detected Text**: - Title: "Figure 8 - Relative dispersion range limits of the type II absolute value distribution in relationship to the relative location" - Various mathematical equations and descriptions detailed below the graph. - Footnotes explaining the notation specifics. - **Content Significance**: - The text provides detailed theoretical explanations and formulas necessary to understand the dispersion range limits for a type II absolute value distribution. The approximations and error precisions are also explained. #### 5. Diagram and Chart Analysis: - **Graph Analysis**: - **Axes**: - X-axis: Labeled as "Relative location μ/σ", ranging from 1.5 to 6.0. - Y-axis: Labeled as "Relative scatter range limit", ranging from 0 to 9. - **Data Trends**: - Two curves are depicted: - \( X_{99.865\%} / σ \) - \( X_{0.135\%} / σ \) - The graph shows increasing trends for both curves as the relative location μ/σ increases. - **Key Insights**: - The relationship between the relative location and the relative scatter range limit is non-linear. - The upper bound \( X_{99.865\%} / σ \) increases at a different rate compared to the lower bound \( X_{0.135\%} / σ \). #### 12. Graph and Trend Analysis: - **Data Points and Trends**: - From 1.5 to 6.0 on the x-axis, the particular scatter range limits increase, suggesting an increasing relationship between the relative location and scatter range limits. - Highlighting the non-linear growth of the variable scatter range limits based on the given equations. #### 13. Graph Numbers: - **Data Points**: - Specific numeric data points aren’t provided in the graph apart from the general trend lines (curves). #### Additional Aspects: - **Ablaufprozesse (Process Flows)**: - The process flow is described for determining the statistics z and σy using given formulas, highlighting sequential steps in the determination and approximation process. - **Prozessbeschreibungen (Process Descriptions)**: - Detailed process descriptions are provided for determining dispersion range limits and the use of approximations for error precision. - **Typen Bezeichnung (Type Designations)**: - The type designation mentioned refers to the "type II absolute value distribution". #### Text Equations: - **Equation (2.27)**: \[ \xi_{2} \left(\frac{\hat{z}}{\hat{\sigma}}\right) \approx 2.1 \left(\frac{\hat{z}}{\hat{\sigma}} - 1.9131\right)^{0.913} + 0.466 \left(\frac{\hat{z}}{\hat{\sigma}} - 1.9131\right)^{1.22} \] - **Equation (2.28)**: \[ \hat{z}_{99.865\%} \approx \frac{\hat{\sigma}}{e} \left(-1.64 \cdot \left(\frac{\hat{z}}{\hat{\sigma}} - 1.9131\right)^{0.62} + 2.075 \cdot \left(\frac{\hat{z}}{\hat{\sigma}} - 1.9131\right)^{0.89} + 5.5485\right) \] \[ \hat{z}_{0.135\%} \approx \frac{\hat{\sigma}}{e} \left[2.6 \cdot \exp \left(\left(\frac{\hat{z}}{\hat{\sigma}} - 1.7031\right) \cdot 0.8\right) + 1.425 \cdot \left(\frac{\hat{z}}{\hat{\sigma}} - 1.9131\right)^{0.9} - 2.1206\right] \] This comprehensive examination encapsulates the intricate details regarding the graph, related calculations, and underlying mathematical explanations present in the visual content. #################### File: VW%2010130_EN%281%29.pdf Page: 16 Context: # 3.2.2 Determination of Capability for Undefined Distribution Models If no fitting distribution model can be assigned to a production characteristic or the measured values from the random samples contradict the assumed distribution model, a distribution-free estimate of the capability indexes is carried out according to the range method, in the following modified form under consideration of the random sample size (see also example 3 in Section 5): ## Capability Indexes for Characteristics with Two-Sided Tolerance Zones \[ \hat{c}_{m} = \frac{G_{o} - \hat{G}_{u}}{\hat{x}_{o} - \hat{x}_{u}} \tag{2.29} \] \[ \hat{c}_{m} = \min \left\{ \frac{G_{o} - \hat{x}_{o,95\%} - \hat{G}_{l}}{\hat{x}_{o} - \hat{x}_{o,95\%} \, \hat{x}_{o,95\%} - \hat{x}_{u}} \right\} \tag{2.30} \] ## Capability Indexes for Characteristics with Upper Limited Tolerance Zone and Natural Limit Zero \[ \hat{c}_{m} = \frac{G_{o}}{\hat{x}_{o} - \hat{x}_{u}} \tag{2.31} \] \[ \hat{c}_{m} = \frac{G_{o} - \hat{x}_{o,95\%}}{\hat{x}_{o} - \hat{x}_{o,95\%}} \tag{2.32} \] ## Capability Indexes for Characteristics with Lower Limited Tolerance Zone Only \[ \hat{c}_{m,k} = \frac{\hat{x}_{o,95\%} - \hat{G}_{l}}{\hat{x}_{o,95\%} - \hat{x}_{u}} \tag{2.33} \] where - \(\hat{x}_{o}\), \(\hat{x}_{u}\): estimated values of the upper and lower dispersion range limits - \(\hat{x}_{o,95\%}\): estimated value of the **50% quantile** In the case of **single values**: \[ \hat{x}_{o,95\%} = \bar{x} \tag{2.34} \] where - \(\bar{x}\): median value, the value that lies in the middle of an ordered sequence of measurements The dispersion range limits are estimated with: \[ \hat{x}_{o} = x_{c} - k \cdot \frac{R}{2} \tag{2.35} \] where - \(x_{c}\): center of the interval - \(k\): constant related to the desired confidence level - \(R\): range of the data Image Analysis: ### Detailed Analysis of the Provided Document: The document appears to be a technical text likely excerpted from a manual or guide. #### 1. Localization and Attribution: - **Image Position**: Single page is displayed. - **Image Number**: Image 1 #### 4. Text Analysis: - **Extracted Text**: - **Page Information**: - "Page 16" - "VW 101 30: 2005-02" - **Section Heading**: - "3.2.2 Determination of capability for undefined distribution models" - **Main Content**: - The text describes statistical methods for determining capability indexes for characteristics with various tolerance zones. - There are several mathematical formulas provided for different scenarios: - Two-sided tolerance zones (Formulas 2.29, 2.30) - Upper limited tolerance zone and natural lower limit zero (Formulas 2.31, 2.32) - Lower limited tolerance zone only (Formula 2.33) - **Variables and Notations**: - \( \tilde{c}_m \), \( \tilde{c}_{mk} \), \( \tilde{x}_M \), \( \tilde{x}_u \), \( \tilde{x}_{50\%}\), \( \tilde{x} \) - \( G_o, G_u, k, R \) - **Additional Notes**: - Definition of single values and median value. - Final formulas provide estimations for dispersion range limits (Formula 2.35). - **Contextual Significance**: - The extracted formulas and methodologies are essential for determining statistical capabilities without predefined distribution models, which is critical in quality control and manufacturing processes. #### 5. Diagram and Chart Analysis: - **Absence of Diagrams or Charts**: - The page contains purely textual and mathematical content with no diagrams or charts to analyze. #### 10. Contextual Significance: - **Contribution to Overall Document**: - This text is likely part of a larger technical manual or guide that provides methodologies for determining statistical capability. It focuses on cases where typical distribution models do not apply, indicating an advanced level of statistical quality control. #### Ablufprozesse (Process Flows) / Prozessbeschreibungen (Process Descriptions): - **None Depicted**: - There are no process flows or detailed process descriptions within the content of this page. #### Typen Bezeichnung (Type Designations): - **Identification**: - This section is part of a larger document ("VW 101 30: 2005-02") and specifically deals with undefined distribution models in statistical analysis. ### Summary: This page provides detailed methodological instructions for calculating capability indexes for manufacturing characteristics without predefined distribution models. It includes specific formulas and conditions for their application, making it a critical reference for professionals in quality control and manufacturing processes. #################### File: VW%2010130_EN%281%29.pdf Page: 17 Context: ```markdown x_c = \frac{x_{\text{max}} + x_{\text{min}}}{2} (2.36) R = x_{\text{max}} - x_{\text{min}} : \text{ range} (2.37) x_{\text{max}}, x_{\text{min}} : \text{ maximum and minimum measured value, respectively, of the effective total random sample} By the correction factor k = \frac{6}{d_n} (2.38) the effective random sample size n_e is taken into consideration, where d_n : \text{ expected value of the } w \text{ distribution } ^{5} The value d_n is given in Table 1 for a few random sample sizes n_e. | n_e | d_n | |-----|------| | 20 | 3.74 | | 25 | 3.93 | | 30 | 4.09 | | 35 | 4.21 | | 40 | 4.32 | | 45 | 4.42 | | 50 | 4.50 | For random sample sizes that are greater than 20, the expected values of the w distribution can be determined according to the following approximation formula: d_n \equiv 1.748 \cdot \ln(n_e)^{6.63} (2.39) In the case of a frequency distribution of classified measured values \hat{x}_0, \hat{x}_d \text{ are the upper limit, lower limit, respectively, for the top/bottom occupied class} and \hat{x}_{90\%} = \hat{x}_k + \frac{n/2 - A_k}{a_k} \cdot \Delta x \text{ for } A_k < \frac{n}{2} \leq A_k + a_k (2.40) where x_k : \text{ lower limit of the } k^{th} \text{ class} \Delta x : \text{ class width} a_k : \text{ absolute frequency of the measured values in the } k^{th} \text{ class} A_k : \text{ absolute cumulative frequency of the measured values to the lower limit of the } k^{th} \text{ class} ``` Image Analysis: ### Analysis of the Visual Content #### 1. Localization and Attribution: - **Image Identification:** - Single image on the page identified as **Image 1**. #### 4. Text Analysis: - **Text Detected:** - Page details: "Page 17, VW 101 30: 2005-02". - Mathematical notations and formulae. - Table titled "Expected value of the w distribution in relationship to nₑ". - Linguistic content explaining how to interpret the values in the table. - **Mathematical Formulae and Content:** - Several mathematical expressions are presented: - \( x_c = \frac{x_{\max} + x_{\min}}{2} \) - \( R = x_{\max} - x_{\min} \) - \( \frac{6}{d_n} \) - Description explaining the different symbols: - \( x_{\max}, x_{\min} \): Maximum and minimum measured values. - \( R \): Range. - \( k = \frac{6}{d_n} \): A correction factor involving expected value of the \( w \) distribution \((d_n)\). #### 5. Diagram and Chart Analysis: - **Table Content Analysis:** - Title: "Expected value of the w distribution in relationship to nₑ". - Columns: - \( nₑ \): Represents the effective random sample size. - \( d_n \): Represents the expected value of the \( w \) distribution. - Data presented in the table: - \( nₑ = 20, d_n = 3.74 \) - \( nₑ = 25, d_n = 3.93 \) - \( nₑ = 30, d_n = 4.09 \) - \( nₑ = 35, d_n = 4.21 \) - \( nₑ = 40, d_n = 4.32 \) - \( nₑ = 45, d_n = 4.42 \) - \( nₑ = 50, d_n = 4.50 \) #### 12. Graph and Trend Analysis: - **Formulae and Trends:** - For \( nₑ > 20 \), the expected value of the \( w \) distribution is calculated with the formula: - \( d_n \approx 1.748 - (\ln(n_e))^{0.602} \) - Additional formula for frequency distribution of classified measured values: - Upper limit and lower limit represented as \( x_{0}, x_{u} \), respectively. - The formula for the highest value in frequency distribution involves additional parameters including class width, frequency, and cumulative frequency. #### 13. Graph Numbers: - **Numerical Data points:** - For \( nₑ \): - 20 - 25 - 30 - 35 - 40 - 45 - 50 - For \( d_n \): - 3.74 - 3.93 - 4.09 - 4.21 - 4.32 - 4.42 - 4.50 ### Summary: - **Content Overview:** - The page seems to discuss statistical measures for sample sizes. - Provides mathematical formulas and a table to understand the expected value of a specific w distribution. - Detailed descriptions and formulae help in calculating these values for different sample sizes. - **Significance:** - The information is crucial for statistical analysis and understanding distribution expectations for various sample sizes. - Helps in making informed decisions based on statistical data. #################### File: VW%2010130_EN%281%29.pdf Page: 18 Context: # 3.3 Limit values of machine capability To obtain the machine capability for a considered characteristic, the capability indexes determined must fulfill the following requirement with respect to the specified limit values \( C_{mk, \text{green}} \) and \( C_{mk, \text{red}} \): ## Characteristics with two-sided tolerance zones: \[ \hat{C}_{mk} \geq C_{mk, \text{limit}} \tag{3.1} \] ## Characteristics with one-sided tolerance zone only6: \[ \hat{C}_{mk} \geq C_{k, \text{limit}} \tag{3.2} \] with an effective random sample size of \( n_e \geq 50 \) Unless otherwise agreed, the following capability limit values apply: \[ C_{k, \text{limit}} = 2.0 \] \[ C_{mk, \text{limit}} = 1.67 \] In cases where, with reasonable effort, an examination can only be carried out with an effective random sample size less than 50, the resulting uncertainty of the capability indexes determined must be taken into consideration by applying correspondingly higher limit values as follows. The determination of limit values for effective random sample sizes smaller than 50 is related here to limit values that comply with the requirement from (3.1) or (3.2) for the population to be investigated with 95% probability (lower confidence range limits). With the assumption of a normally distributed population, these result from the upper confidence range limit of the standard deviation: \[ \sigma_e = \hat{\sigma} \cdot \frac{49}{\sqrt{2 \cdot n_e}} \tag{3.3} \] and the statistical percentage range for the production dispersion: \[ X_{99.865\%} = X_{0.135\%} \pm \hat{z}_{99.865\%} \left( \frac{1 + \frac{1}{2 \cdot 50}}{\sqrt{49}} \right) \tag{3.4} \] where - \( z_{99.865\%} = 3.0 \): quantile of the standardized normal distribution - \( \chi^{2}_{49\%} = 33.9 \): quantile of the chi-square distribution with a degree of freedom of \( f = 49 \) (see also [1]) 6 Although no limit value for \( C_m \) is specified for characteristics with upper limited tolerance zone only, a \( C_m \) value is to be determined and specified, since from the comparison of this value to the \( C_m \) value, it is possible to recognize whether an undesirable situation shift exists. For example, if the \( C_{mk} \) value is higher than the \( C_{m} \) value, the distribution lies closer to the natural limit value zero than to the upper limiting value. Image Analysis: Here is a comprehensive analysis of the visual content provided, addressing the relevant aspects: ### Localization and Attribution - **Image Position:** This image appears to be a single page, numbered as **Image 1** based on its position. ### Text Analysis **Extracted Text:** - **Main Title:** "Limit values of machine capability" - **Section:** "3.3 Limit values of machine capability" - **Content:** - Requirements for machine capability indexes. - Formulas and conditions with respect to specified limit values. - Commentary on the effectiveness and sample sizes. - Confidence range limits and statistical percentage range for production dispersion. - Definitions and essential concepts like quantiles and degrees of freedom. **Analysis:** - **Formulas and Conditions:** The text includes mathematical formulas (e.g., \( \hat{c}_{m} \geq c_{m,\text{limit}} \)) to determine machine capability, addressing one and two-sided tolerance zones. - **Context:** Used in engineering or quality assurance for defining machine capability limits. - **Significance:** Ensures machinery operates within specified parameters, which is crucial for maintaining product quality and operational efficiency. ### Diagram and Chart Analysis **Mathematical Expressions and Data:** - **Formulas:** - Two-sided tolerance zones: \( \hat{c}_{m} \geq c_{m,\text{limit}} \) and \( \hat{c}_{mk} \geq c_{mk,\text{limit}} \) - One-sided tolerance zone: \( \hat{c}_{mk} \geq c_{mk,\text{limit}} \) - Effective random sample size: \( n_{B} \geq 50 \) - Standard deviation upper confidence range limit: \( \sigma_{o} = \sigma \cdot \sqrt{\frac{49}{\chi^2_{5\%/49}}} \) - Statistical percentage range: \( x_{99.865\%} = \bar{x} \pm t_{99.865\%} \cdot \left( 1 + \frac{1}{2 \cdot 50} \right) \cdot \sqrt{\frac{49}{\chi^2_{5\%/49}}} \cdot \sigma \) - **Values:** - Capability limit values: \( c_{n,\text{limit}} = 2.0 \) and \( c_{nk,\text{limit}} = 1.67 \) - Quantiles: \( t_{99.865\%} = 3.0 \) - Chi-square distribution: \( \chi^2_{5\%/49} = 33.9 \) ### Process Descriptions **Requisite Conditions:** - Machine capability indexes must fulfill specified limit values and be examined with effective random samples for accuracy. - Adjustments for sample sizes smaller than 50 are provided, ensuring the results maintain statistical validity. ### Contextual Significance **Overall Document Context:** - This page is from a technical document or standard, likely related to engineering, production quality control, or machinery maintenance. - **Page Number:** "Page 18" - **Document Title:** "VW 101 30: 2005-02" signifies the document originates from a specific set of standards or guidelines relevant to the Volkswagen group or a similar entity. ### Metadata Analysis **Implied Information:** - **Date:** February 2005 (as part of the document title). - **Context:** Standards or guidelines relevant to a specific period, highlighting how machine capability limits were defined and analyzed during that time. ### Anomaly Detection - **Noticeable Elements:** None detected that deviate from the technical and formulaic structure of the document. ### Perspective and Composition **Image Perspective:** - The image is scanned or captured from a directly overhead perspective, ensuring the text is legible and formatted correctly for analysis. ### Conclusion The page provides detailed guidelines on determining and validating machine capability through statistical measures, ensuring machinery adheres to specific performance standards. The content, heavy with formulas and statistical values, underscores its technical and formal nature, playing a critical role in quality assurance and operational efficiency within a production setting. #################### File: VW%2010130_EN%281%29.pdf Page: 19 Context: By transformation and substitution in the evaluation formulas (2.1) and (2.2), this results in the **capability limit values for the population** \[ c_r \geq c_{r,\text{limit}} \cdot \sqrt{\frac{X_{r,\text{max}}}{49}} = 0.832 \cdot c_{\text{limit}} \tag{3.5} \] \[ c_{mk} \geq c_{k,\text{limit}} \cdot \frac{1}{1 + \sqrt{100}} \cdot \sqrt{\frac{X_{k,\text{max}}}{49}} = 0.824 \cdot c_{k,\text{limit}} \tag{3.6} \] For effective random sample sizes \( n_e < 50 \), this results in the following **fitted capability limit values**: \[ \hat{c}_r \geq c_{r,\text{limit}} \cdot 0.832 \cdot \sqrt{\frac{f}{X_{r,k}}} \tag{3.7} \] \[ \hat{c}_{mk} \geq c_{k,\text{limit}} \cdot 0.824 \cdot \left(1 + \frac{1}{2 n_e}\right) \cdot \sqrt{\frac{f}{X_{k,m}}} \tag{3.8} \] with the degree of freedom \[ f = n_e - 1 \tag{3.9} \] **Example:** For specified capability limit values of \( c_{r,\text{limit}} = 2.0 \), \( c_{k,\text{limit}} = 1.67 \) and an effective random sample size of \( n_e = 20 \), according to the formulas (3.7) to (3.9) the following fitted limit values result for characteristics with two-sided tolerance zones: \[ \hat{c}_r \geq 2.0 \cdot 0.832 \cdot \sqrt{\frac{20 - 1}{10.1}} = 2.28 \] \[ \hat{c}_{mk} \geq 1.67 \cdot 0.824 \cdot \left(1 + \frac{1}{2 \cdot 20}\right) \cdot \sqrt{\frac{20 - 1}{10.1}} = 1.93 \] --- 7. The determination of the adapted capability limit values using formulas (4.7) to (4.9) is also used for populations without normal distribution, since there are no other methods for these at this time and thus at least a usable consideration of a random sample size that is less than 50 is carried out. Image Analysis: ### Analysis of the Attached Visual Content #### Localization and Attribution: - **Single Image**: - The document contains only one image. - **Image Number**: Image 1 #### Text Analysis (Image 1): - **Extracted Text**: The content includes well-structured mathematical formulas and a textual description explaining capability limit values for the population and effective random sample sizes. **Text Content**: - **Page Header**: - Page 19 - VW 101 30:2005-02 - **Main Text**: ``` By transformation and substitution in the evaluation formulas (2.1) and (2.2), this results in the capability limit values for the population. Equation 3.5: c_{m)>=c{mk,limit}\sqrt{\frac{K_{l,\delta}{2}}{49}} =0,832 * c_{mk,limit} Equation 3.6: c_{mk}>c_{mk,\limt}\frac(1)(1+\frac{1}{100}) * \sqrt{\frac{K^2_{l,delta}}{49}} = 0,824 * c_{mk,limit} For effective random sample sizes n-.... <50, the results in the following fitted capability limit values Equation 3.6: ĉ_{m)>=c{mk,limit} 0,832 * \sqrt{\frac(f}{K^2_{l, delta}} Equation 3.7: ĉ_{mk}>{cap,limit} \cdot 0,.824 * \sqrt{\frac{l+\frac{1}{2}\cdot l){*f}{K_{l,delta}}l{\sqrt{f}{n-1}} .... As relative random size for n = <... \cdot Example: For specific cap limit value of c_{cm,limit}=2,0 c_{m\=limit = 1,67} and effective random joint sample size of \cdot n_{e} = 2.... according to form... Equation 4.9-.....Given the following fitted .... C_{m}=2',03 * C) .....[complex formulay] \sqrt(20-1)(cm200)= (m=1,67c incurred indicated \sqrt{\frac(f}{K^2_{4...osure followable '' **Footnote**: The determination of the adapded capability limit values using formula f={ 1 to 0.1th is also used for populations without normal attributes #### Scene and Activity Analysis (Image 1): - **Scene Description**: The entire image is a page from a technical or academic text. It primarily features complex mathematical content related to capability limit evaluation formulas. - **Activities**: The primary activities involve mathematical transformations, substitutions, and evaluations of capability limit values. #### Color Analysis (Image 1): - **Dominant Colors**: Predominantly black text on a white background. - **Impact on Perception**: The contrast between black text and white background makes the text highly readable and professional, suitable for academic and technical documentation. #### Perspective and Composition (Image 1): - **Perspective**: The image is a scanned or photographed page from a document, seen from a top-down or direct perspective. - **Composition**: The layout is similar to a standard academic page, with header, main content, numbered formulas, and a footnote. - **Elements Arrangement**: Clear hierarchical structuring of formulas and supporting text for easy understanding and reference. #### Contextual Significance (Image 1): - **Document Context**: Given the technical and formulaic content, it is likely part of a larger document on statistical analysis or quality control. - **Contribution to Message**: The page contributes to explaining the methodology for calculating capability limits within a given statistical context. ### Conclusion: The image analyzed is a page from a technical document related to statistical evaluation formulas for capability limits. It involves detailed mathematical expressions aimed at professionals or academics in fields such as quality control, statistics, or engineering. The text is well-organized, with clear structuring and notation to facilitate understanding of the complex formulas presented. The page is designed to be informative and easily readable, using a simple black-and-white color scheme. #################### File: VW%2010130_EN%281%29.pdf Page: 20 Context: # 3.4 Statistical Tests Generally, the measurements of a machine capability investigation shall not exhibit any: - unexpectedly great deviation of single measured values (outliers) in comparison to the dispersion of other measured values, - significant change of the production location during the sampling, and - significant deviation from the expected distribution model. Otherwise, additional systematic influences on production have to be taken into consideration. The causes should then be known for this behavior and their effect should be acceptable in order to fulfill the requirement of a secure manufacturing process. Therefore, to test the above mentioned criteria, the appropriate statistical tests shall be used during a machine capability investigation. Since these tests are described in detail in standards and standard statistics references, they will only be indicated by the following references: The following tests are to be carried out in the scope of a machine capability investigation: - **Test for outliers** using the distribution-free test according to Hampel in modified form (see VDA 4 standard VW 10133) - **Test for change of the production location** using the distribution-free Run-Test according to Swed-Eisenhart (see [1]) - **Test for deviation from the normal distribution** according to Epps-Pulley (see ISO 5479) - **Test for deviation from any specified distribution model** using the chi-square test (see [1]) The statistical tests all proceed according to the following system: 1. Setting up the **null hypothesis** \(H_0\) and the **alternative hypothesis** \(H_a\), e.g., - \(H_0\): The population of the measured values of the characteristic considered has normal distribution - \(H_a\): The population of the measured values of the characteristic considered does not have normal distribution 2. Specification of the **confidence level** \(\alpha = 1 - \alpha\) or **probability of error** \( \alpha\) 3. Setting up the formula for the **test variable** 4. Calculating the **test value** from the random sample values according to the test variable formula 5. Determining the **threshold value** of the test distribution 6. Comparison of the test value to the threshold value for decision of whether a contradiction to the null hypothesis exists and thus the alternative hypothesis is valid. It should be noted that in a statistical test with the specified confidence level \( \alpha \), contradiction to the null hypothesis can be proven, e.g., that a significant deviation of the measured values from a normally distributed population exists. If no contradiction to the null hypothesis results from the test result, this is not a confirmation of the validity of the null hypothesis. In this case, it cannot be proven that the defined confidence level that a normally distributed population exists, for example. Then, analogously to the legal principle "if in doubt, find for the defendant," a decision is simply made for assumption of the null hypothesis. The probability of error \( \alpha \) indicates the risk of rejecting the null hypothesis on the basis of the test result, although it applies (as risk). However, not just any small value can be specified for the probability of error, since that would increase, e.g., the risk of not discovering an actual deviation from a normal distribution (as risk). Image Analysis: ## Analysis of Image 1 ### 1. Localization and Attribution: - **Image Identifier**: Image 1 - **Location**: The image appears to be a standalone page from a document. ### 4. Text Analysis: - **Extracted Text**: ``` Page 20 VW 101 30: 2005-02 3.4 Statistical tests Generally, the measurements of a machine capability investigation shall not exhibit any – unexpectedly great deviation of single measured values (outliers) in comparison to the dispersion of other measured values, – significant change of the production location during the sampling and – significant deviation from the expected distribution model. Otherwise additional systematic influences on production have to be taken into consideration. The causes should then be known for this behavior and their effect should be acceptable in order to fulfill the requirement of a secure manufacturing process. Therefore, to test the above mentioned criteria the appropriate statistical tests shall be used during a machine capability investigation. Since these tests are described in detail in standards and standard statistics references, they will only be indicated by the following references: The following tests are to be carried out in the scope of a machine capability investigation: – Test for outliers using the distribution-free test according to Hampel in modified form (see Volkswagen standard VW 10133) – Test for change of the production location using the distribution-free Run-Test according to Swed-Eisenhard (see [1]) – Test for deviation from the normal distribution according to Epps-Polley (see ISO 5479 – Test for deviation from any specified distribution model using the chi-square test (see [1]) The statistical tests all proceed according to the following system: – Setting up the null hypothesis H0 and the alternative hypothesis H1, e.g. H0: The population of the measured values of the characteristic considered has normal distribution H1: The population of the measured values of the characteristic considered does not have normal distribution – Specification of the confidence level γ = 1-α or probability of error α – Setting up the formula for the test variable – Calculating the test value from the random sample values according to the test variable formula – Determining the threshold value of the test distribution – Comparison of the test value to the threshold value for decision of whether a contradiction to the null hypothesis exists and thus the alternative hypothesis is valid It should be noted that in a statistical test with the specified confidence level γ possibly only a contradiction to the null hypothesis can be proven, e.g. that a significant deviation of the measured values from a normally distributed population exists. If no contradiction to the null hypothesis results from the test result, this is not a confirmation of the validity of the null hypothesis. In this case, it cannot be proven within the defined confidence level that a normally distributed population exists, for example. Then, analogously to the legal principle “if in doubt, find for the defendant,” a decision is simply made for assumption of the null hypothesis. The probability of error α indicates the risk of rejecting the null hypothesis on the basis of the test result, although it applies (α risk). However, not just any small value can be specified for the probability of error, since that would increase, e.g., the risk of not discovering an actual deviation from a normal distribution (β risk). ``` - **Content Analysis**: - **Title and Section**: "3.4 Statistical tests" is the section title, indicating the focus is on statistical testing within machine capability investigations. - **Key Points**: - Discusses statistical tests to ensure consistency and lack of deviation in machine capability measurements. - Specifies conditions and systematic influences that must be considered. - Tests mentioned: - Outliers (Hampel test) - Change in production location (Run-Test) - Normal distribution deviation (Epps-Polley test) - Chi-square test for specified distribution model. - Describes setting up hypotheses (null and alternative), confidence levels, test variable formulas, calculating test values, threshold values, and decision making. ### 12. Diagram and Chart Analysis: - There are no diagrams or charts in the image. ### 13. Graph Numbers: - Since no graphs are present, numerical data points analysis isn't applicable. ### 15. Tables: - There are no tables in the image. ### 8. Color Analysis: - **Color Composition**: - Dominantly black text on a white background, providing high contrast and readability. ### 9. Perspective and Composition: - **Perspective**: - Front-facing view of a text document. - **Composition**: - The document is well-structured with clear headings, subheadings, and bullet points for clarity and ease of reading. ### 10. Contextual Significance: - **Context and Contribution**: - Likely part of a larger technical manual or guidelines document related to machine capability and statistical analysis. - Contributes valuable information on how to conduct and interpret statistical tests in manufacturing processes. ## Summary: Image 1 is a clearly structured and detailed section from a technical manual focused on statistical tests relevant to machine capability investigations. It outlines key tests, procedural steps for hypothesis testing, and considerations for secure manufacturing processes. The content is technical and highly relevant for professionals involved in machine capability and quality assurance. #################### File: VW%2010130_EN%281%29.pdf Page: 21 Context: # 4 Carrying out a machine capability investigation A machine capability investigation (MFI) is carried out according to the sequence shown in Figures 9 to 11. ## Flowchart of Machine Capability Investigation 1. Start 2. **4.1 Test equipment use** 3. **4.2 Sampling** - Conditions for MFI fulfilled? - **Yes** → **4.4 Data analysis** - **No** → **4.3 Special regulation for restricted MFI** 4. **4.5 Documentation** 5. **4.6 Results evaluation** - Evaluation repeat? - **Yes** → Back to **4.5 Documentation** - **No** → Is the machine capable? - **Yes** → **4.7 Machine optimization** - **No** → Feasible machine optimization? - **Yes** → **4.8 Handling of incapable machines** - **No** → End --- **Figure 9 - Sequence of a machine capability investigation** Image Analysis: ### Image Analysis **Image Number: Image 1** #### Object Detection and Classification - **Objects Detected:** - Text content - Flowchart elements including shapes like ovals, rectangles, and diamonds. - Arrows indicating process flow. - **Key Features of Detected Objects:** - The flowchart begins with a start point indicated by an oval shape. - It includes various process steps, decisions, and conditions. - Arrows show the direction of the process flow from one step to another. #### Scene and Activity Analysis - **Entire Scene Description:** - The image is a flowchart illustrating the sequence of a machine capability investigation. - It is divided into different steps starting from "Test equipment use" and including steps like "Sampling," "Data analysis," and "Results evaluation." - **Activities Taking Place:** - The flowchart delineates various activities carried out during a machine capability investigation. - Decision points lead to different actions based on the results of each step. #### Text Analysis - **Text Content:** - "Page 21 VW 101 30: 2005-02" - "4 Carrying out a machine capability investigation" - "Start" - "4.1 Test equipment use" - "4.2 Sampling" - "Conditions for MFI fulfilled" - "No" - "4.3 Special regulation for restricted MFI" - "Yes" - "4.4 Data analysis" - "4.5 Documentation" - "4.6 Results evaluation" - "Evaluation repeat" - "Machine capable" - "No" - "Feasible machine optimization" - "Yes" - "No" - "4.7 Machine optimization" - "4.8 Handling of incapable machines" - "Yes" - "End" - "Figure 9 - Sequence of a machine capability investigation" - **Content Significance:** - The text describes different stages in a machine capability investigation process. - It provides specific instructions and decision points for undertaking various actions depending on the results at each stage. #### Diagram and Chart Analysis - **Axes, Scales, and Legends:** - Not applicable. This is a flowchart without any axes, scales, or legends. - **Key Insights:** - The flowchart offers a structured methodology for conducting a machine capability investigation. - It identifies critical decision points that determine the subsequent steps, facilitating systematic evaluation and optimization of machine capability. #### Ablaufprozesse (Process Flows) - **Process Flow Description:** - The flowchart starts with equipment testing, proceeds through sampling, and assesses whether MFI (Machine Functional Index) conditions are met. - If conditions are not met, it refers to special regulations. - Further steps involve data analysis and documentation, results evaluation, and machine optimization. - Final steps determine whether the machine is capable or if further actions like handling incapable machines are necessary. #### Prozessbeschreibungen (Process Descriptions) - **Detailed Process Description:** - The process begins with testing the equipment (4.1). - Followed by sampling (4.2). - A decision is made whether conditions for MFI are fulfilled. - Based on conditions, different steps such as data analysis (4.4), documentation (4.5), and results evaluation (4.6) are followed. - Machine optimization (4.7) or handling of incapable machines (4.8) concludes the process. #### Trend and Interpretation - **Trends Identified:** - The process emphasizes systematic data collection, analysis, and decision-making. - A focus is placed on optimization and proper handling of incapable machines based on evaluation results. #### Perspective and Composition - **Image Perspective:** - The image is taken from a straightforward, eye-level perspective, providing clear visibility of all flowchart elements in a top-down manner. - **Image Composition:** - The elements are arranged sequentially, with arrows guiding the viewer through the process from start to finish. - Decision points and action steps are clearly delineated to ensure a logical flow of information. ### Summary The image provides a comprehensive flowchart outlining the sequence of conducting a machine capability investigation. Through a series of steps involving testing, sampling, analysis, and decision-making, the chart presents a systematic approach to achieving machine optimization or handling incapable machines. #################### File: VW%2010130_EN%281%29.pdf Page: 22 Context: # 4.4 Data Analysis ## 4.4.1 Selection of the Expected Distribution Model ## 4.4.2 Test for Outliers - **Outliers present?** - Yes: - **4.4.3** Take outliers out of the calculation of statistics - No: - **4.4.4** Test for change of the production location - **4.4.5** Test for deviation from the specified distribution model ## 4.4.4 Test for Change of the Production Location ## 4.4.5 Test for Deviation from the Specified Distribution Model - **Deviation from distribution model?** - Yes: - **Distribution-free evaluation** - No: - **Normal distribution?** - Yes: - **4.4.6** Evaluation according to normal distribution - No: - **4.4.7** Evaluation according to specified model ## Continued at 4 --- **Figure 10 - Sequence of Data Analysis** Image Analysis: ### Analysis of the Attached Visual Content **1. Localization and Attribution:** - **Identification and Location:** There is a single image on the page containing a flowchart. - **Numbering:** Image 1. **2. Object Detection and Classification:** - **Objects Identified:** - Flowchart components including flowchart shapes such as ovals, rectangles, diamonds, and arrows. - **Key Features:** - The flowchart outlines a process with decision points and actions. **4. Text Analysis:** - **Detected Text:** - Page 22 - VW 101 30: 2005-02 - 4.4 Data analysis - 4.4.1 Selection of the expected distribution model - 4.4.2 Test for outliers - Outliers present - 4.4.3 Take outliers out of the calculation of statistics - no - 4.4.4 Test for change of the production location - 4.4.5 Test for deviation from the specified distribution model - Deviation from distribution model - yes - 4.4.6 Evaluation according to normal distribution - 4.4.7 Evaluation according to specified model - no - normal distribution - Continued at 4 - Distribution-free evaluation - Figure 10 - Sequence of data analysis - **Content Analysis:** - The text describes the steps and decision points involved in the process of data analysis. It begins with selecting an expected distribution model and tests for outliers, followed by actions based on whether outliers are present. The flowchart includes various decision paths based on the results, including the possible need for a change in the production location, evaluation according to a normal distribution, or a distribution-free evaluation. The text conveys a systematic approach to analyzing data and handling deviations. **5. Diagram and Chart Analysis:** - **Data and Trends Identified:** - The diagram is a process flowchart depicting the sequence of steps and decision points in data analysis. - **Axes, Scales, and Legends:** - Not applicable. - **Key Insights:** - The flowchart provides a structured methodology for data analysis, highlighting critical points where decisions are to be made regarding the statistical treatment of data. **8. Color Analysis:** - **Color Composition:** - The image is primarily in black and white, using text and shapes to convey the flow of the process. - Dominant Colors: Black text and lines on a white background. **9. Perspective and Composition:** - **Perspective:** - The image is presented from a standard, straight-on view typical for diagrams and charts. - **Composition:** - The flowchart is vertically aligned, with each step or decision point connected by arrows to indicate the flow of the process. **12. Graph and Trend Analysis:** - **Trends and Interpretation:** - The flowchart indicates a flow from generalized data analysis to specific actions based on statistical testing outcomes. Every potential path has been delineated with steps designed to handle variations in data distributions and outlier management. - **Detailed Breakdown:** - The flowchart starts with a broad step of "4.4 Data analysis," which then branches into: - Selection of the expected distribution model - A test for outliers - If outliers are present, they are taken out of the calculation - Tests for change of production location and deviations from the expected distribution model - If deviations are present, evaluation processes are outlined based on normal distribution or specified model. By analyzing this diagram, users can follow a structured approach to data analysis, considering outliers, production changes, and deviations in distribution models to ensure accurate evaluation. #################### File: VW%2010130_EN%281%29.pdf Page: 23 Context: # 4.6 Results Evaluation ```mermaid flowchart TD A[Outliers present?] -->|yes| B[Outliers due to incorrect measurements?] A -->|no| C[Change of production location?] B -->|yes| D[Evaluation repeat
Continued at 4] B -->|no| E[Cause known and effect acceptable?] C -->|yes| F[Deviation from distribution model?] C -->|no| E F -->|yes| G[Other distribution model possible?] F -->|no| E G -->|yes| D G -->|no| E E -->|yes| H[Capability indexes less than limit values?] E -->|no| I[Machine incapable
Continued at 4] H -->|yes| J[Machine capable
Continued at 4] H -->|no| I ``` **Figure 11 - Sequence of the results evaluation** Image Analysis: ### Image Analysis #### 1. Localization and Attribution - **Image Position**: Only one image is present on the page. - **Image Number**: Image 1 #### 3. Scene and Activity Analysis - **Scene Description**: The image is a flowchart depicting the process flow for the sequence of results evaluation. - **Activity Description**: It shows the decision-making steps in evaluating results, starting from checking for outliers, changes in production location, deviations from distribution models, and evaluating machine capability. #### 4. Text Analysis - **Detected Text**: - "4.6 Results evaluation" - "Outliers present" - "Outliers due to incorrect measurements" - "Change of production location" - "Deviation from distribution model" - "Other distribution model possible" - "Evaluation repeat Continued at 4" - "Cause known and effect acceptable" - "Capability indexes less than limit values" - "Machine capable Continued at 4" - "Machine incapable Continued at 4" - "Figure 11 - Sequence of the results evaluation" - "Page 23" - "VW 101 30: 2005-02" - **Text Analysis**: This text defines the steps and decisions needed to evaluate results systematically. #### 6. Product Analysis - **Product Description**: Not applicable as the image does not depict a product but a flowchart. #### 7. Anomaly Detection - **Anomalies**: No noticeable anomalies. The flowchart appears to be standard and designed correctly without any unusual or unexpected elements. #### 8. Color Analysis - **Color Composition**: The flowchart is in black and white. - **Dominant Colors**: Black and white. - **Impact on Perception**: The use of black and white is conventional for technical diagrams, ensuring clarity and readability. #### 9. Perspective and Composition - **Perspective**: The image is viewed from a straight, eye-level perspective typical for diagrams. - **Composition**: The elements are arranged logically from the top to the bottom, with decision points leading to different paths, indicating a structured process flow. #### 10. Contextual Significance - **Context Analysis**: This image likely belongs to a technical or procedural document related to evaluating machine capabilities or production processes. - **Contribution to Overall Message**: The flowchart helps the reader or user understand the sequence and decision points involved in result evaluation, contributing to a methodical approach. #### 12. Graph and Trend Analysis - **Graph Description**: The flowchart represents decision branches and corresponding actions based on specific evaluation criteria. - **Trend Interpretation**: The flow suggests a structured approach to handling deviations and ensuring machine capabilities are within acceptable limits. #### Additional Aspects #### Ablaufprozesse (Process Flows) - **Process Flow Description**: - **Step 1**: Check for outliers. - **Step 2**: If outliers are present, determine if due to incorrect measurements. - **Step 3**: If no incorrect measurements, check for change in production location. - **Step 4**: If no change in production location, check for deviation from distribution model. - **Step 5**: If deviation exists, evaluate if other distribution models are possible. - **Step 6**: Repeat evaluation if needed. - **Step 7**: If cause of deviation is known and acceptable, and capability indexes are within limits, the machine is capable. If not, the machine is deemed incapable. #### Prozessbeschreibungen (Process Descriptions) - **Process Description**: The process involves several decision points at which specific actions are taken based on the data evaluation, ensuring a systematic and comprehensive approach to result evaluation. #### Typen Bezeichnung (Type Designations) - **Type Designations**: Not explicitly mentioned but implied types include result status (outliers, correct measurements), process elements (distribution models, capability indexes), and outcomes (machine capable/incapable). #### Tables - **Table Analysis**: Not applicable as no tables are included in the image. This comprehensive examination identifies the logical flow and decision points crucial for evaluating results in a systematic manner. #################### File: VW%2010130_EN%281%29.pdf Page: 24 Context: # 4.1 Test Equipment Use Test equipment shall only be used for the MFI that has been released by the responsible department for the planned test process. ## 4.2 Sampling An MFI relates to only one production characteristic or one machine parameter. Generally, the single measurements of the random samples are recorded for evaluation. In the case of minimally recorded measurements in a class subdivision of the value range (tally), the frequency distribution of the classified measurements can also be recorded instead. So, essentially only the machine influence is recorded in an MFI, the following conditions shall be complied with in the production of random sample parts: - A uniform blank batch and a uniform preparation (supplier, material) shall be ensured during the investigation. During the MFI, the machine or system shall always be operated by the same operator. - The premanaging quality of the characteristics to be evaluated must correspond to the required production specifications. - The number of parts to be produced (random sample size) should generally be 50. If this random sample size is difficult to obtain for economic or technical reasons, a smaller one is also permissible. Then the corresponding higher limit values according to Table 3 or the formulas (3.7) and (3.8) have to be complied with. However, the random sample size (i.e. without outliers) must be at least 20. - The parts shall be produced immediately after each other and numbered according to the manufacturing sequence. All specified characteristics shall be tested on each part. - The MFI shall only be carried out with the machine at operating temperature. "Operating temperature" is to be defined for each use case. - The test parts are to be produced under the standard production conditions required for the machine (i.e. with the cycle time and the machine adjustment parameters as in standard production). - Depending on the project, special specifications shall be set so that at the beginning of the MFI, it is ensured that, e.g., the tooling is broken in and that the end of the tooling lifetime does not lie within the MFI. - Tooling change, manual tooling adjustments or other changes of machine parameters shall not be carried out during the MFI. Automatic tooling corrections due to integrated measuring controls are excepted from this. - If there are machine malfunctions during the MFI that influence the characteristic to be investigated, the MFI must be started over again. - The measuring method must be specified before the investigation and agreed upon between supplier and customer. During the production of different parts (different part numbers, e.g., steel shaft / cast iron shaft) on one machine that can additionally have different characteristics, MFIs are to be carried out for all these parts. Image Analysis: ## Comprehensive Examination of the Attached Visual Content ### 1. Localization and Attribution: - The document comprises a single page containing textual content divided into sections with headings and paragraphs. ### 2. Text Analysis: - The document contains text in English and is structured into sections. - **Heading:** "4.1 Test equipment use" and "4.2 Sampling" - **Subsections:** Bulleted and numbered lists describing processes and conditions. - **Footnote:** A small section at the bottom of the page with additional information. #### Detailed Breakdown of Text Content: - **Section 4.1: Test equipment use** - **Content:** - The test equipment is specified for use only with the MFI (Machine Function Investigation) that has been approved by the responsible department for the planned test process. - **Section 4.2: Sampling** - **Content:** - AMFI relates to only one production characteristic or machine parameter. Measurements of random samples are recorded. - Specific conditions for the production of random sample parts are detailed. - Uniform blank batch and preparation must be ensured. - The premachining quality must meet production specifications. - Number of parts, random sample size should be 50 (with exceptions and minimums). - The parts must be produced immediately and numbered according to the manufacturing sequence. - Tests must be carried out with the machine at operating temperature defined for each use case. - Test parts are to be produced under standard production conditions. - Special specifications if tooling is broken in, ensuring tooling lifetime. - Tooling change and other adjustments during MFI are not allowed unless integrated automatic corrections are involved. - Handling machine malfunctions during MFI, which requires restarting the test. - Specifying the measuring method before investigation, agreed upon by supplier and customer. - Conducting MFI during the production of different parts which may have different characteristics. - **Footnote:** - Indicates the consideration of manual data recording forms' occurrence in practice, mentioning the limitations in such procedures. ### 8. Color Analysis: - The document comprises black text on a white background, facilitating ease of reading with no additional colors present. ### 9. Perspective and Composition: - The layout consists of a standard document format with headings and sections aligned in a readable manner. The information is broken down into sub-sections with clear headings and bullet points for better readability. ### 10. Contextual Significance: - This document likely serves as part of a larger set of guidelines or a standard manual, possibly related to the operation and quality assurance in manufacturing processes. #### Summary: The document provides guidelines for the use of test equipment and sampling procedures in a manufacturing or production quality control setting. Sections are clearly outlined to ensure that all steps and conditions are understandably documented and enforceable. The main content emphasizes the precision, consistency, and specified methodologies necessary for maintaining high production standards. #################### File: VW%2010130_EN%281%29.pdf Page: 25 Context: # 4.3 Special regulation for restricted MFI If the conditions named in 4.2 cannot be met completely, in justified cases a restricted MFI can be carried out, for which special regulations are to be agreed upon between supplier and customer and documented under the note "Restricted MFI." # 4.4 Data analysis ## 4.4.1 Selection of the expected distribution model The expected distribution model depends on the characteristic type. For the most important types of characteristics (see also VW 01056), the assigned distribution models are to be taken from Table 2. ## Table 2 - Assignment of characteristic types and distribution models | Characteristic Type | Distribution Model | |------------------------------|--------------------| | Length dimensions | N | | Diameter, radius | N | | Straightness | B1 | | Flatness | B1 | | Roundness | B1 | | Cylindricity | B1 | | Profile of any line | B1 | | Profile of any surface | B1 | | Parallelism | B1 | | Squareness | B1 | | Slope (angularity) | B1 | | Position | B2 | | Coaxiality/concentricity | B2 | | Symmetry | B1 | | Radial runout | B2 | | Axial runout | B2 | | Roughness | B1 | | Unbalance | B2 | | Torque | N | **Legend:** - N: Normal distribution - B1: Type I absolute value distribution - B2: Type II absolute value distribution (Rayleigh distribution) For characteristic types not listed, in most cases an assignment of a distribution can be carried out according to the following rules: - A normal distribution for characteristics with two-sided tolerance zones or one-sided tolerance zone only - And a type I or II absolute value distribution for characteristics with one-sided tolerance zone only Image Analysis: ### Image Analysis **Image 1** #### Localization and Attribution - **Image:** Page 25 of a document labeled "VW 101 30: 2005-02". #### Text Analysis 1. **Headers and Subheaders:** - **4.3 Special regulation for restricted MFI:** Describes conditions under which a restricted MFI can be carried out when certain criteria cannot be met, requiring agreed-upon regulations between supplier and customer. - **4.4 Data analysis:** Introduces processes related to data analysis. - **4.4.1 Selection of the expected distribution model:** Provides guidelines on choosing the appropriate distribution model for characteristic types. 2. **Body Text:** - **Special regulation for restricted MFI:** If conditions named in 4.2 cannot be met, justified cases allow for a restricted MFI, agreed upon between supplier and customer under the note "Restricted MFI." - **Selection of the expected distribution model:** Assigned distribution models based on characteristic type are to be taken from Table 2 and depend on the characteristic type. #### Diagram and Chart Analysis 1. **Table 2: Assignment of characteristic types and distribution models:** - **Characteristic Types:** - Length dimensions - Diameter, radius - Straightness - Flatness - Roundness - Cylindricity - Profile of any line - Profile of any surface - Parallelism - Squareness - Slope (angularity) - Position - Coaxiality/concentricity - Symmetry - Radial runout - Axial runout - Roughness - Unbalance - Torque - **Distribution Models:** - N: Normal distribution - B1: Type I absolute value distribution - B2: Type II absolute value distribution (Rayleigh distribution) 2. **Legend Explanation:** - **N:** Normal distribution - **B1:** Type I absolute value distribution - **B2:** Type II absolute value distribution (Rayleigh distribution) #### Contextual Significance - **Overall Document:** This page is part of a technical document, likely a standards or protocol document for automotive manufacturing or engineering. - **Purpose:** Provides guidance on special regulations and expected distribution models for various characteristic types important for mechanical or manufacturing quality control. #### Perspective and Composition - **Perspective:** The image appears to be a straight-on snapshot of a document page. - **Composition:** Text is organized into sections with clear headings, subheadings, and a table for visual clarity. ### Summary The analyzed visual content consists of a documented page detailing regulations and data analysis related to characteristic types in the context of a manufacturing or engineering standard. The page discusses restricted MFI conditions, the selection of expected distribution models, and the assignment of characteristic types according to their distribution model in a structured and clear manner. The table and legend enhance understanding by providing specific classifications and explanations. #################### File: VW%2010130_EN%281%29.pdf Page: 26 Context: # 4.4.2 Test for outliers First, a determination of whether the measured values recorded contain outliers is made using the distribution-free detector test according to VW 101 33. Outliers are measured values that lie so far from the other measured values that it is highly probable that they do not come from the same population as the remaining values, e.g., erroneous measurements. The outlier test shall be carried out with a confidence level of 99%. ## 4.4.3 Take outliers out of the calculation of statistics If outliers are identified, these are not considered in the calculation of the statistics. However, the outliers shall not be deleted. Rather, they shall be marked accordingly in the graphic representation of the single value curve and their number shall be indicated in the documentation. ### 4.4.4 Test for change of the production location Using the distribution-free Run Test according to Swed-Eisenhard (see [1]), a determination shall be made of whether the production location has changed systematically during the sampling. A systematic change of the production location can occur, e.g., due to the influence of temperature or due to tooling wear (trend curve). This test shall be carried out with a confidence level of 95%. If only the frequency distribution of classified measured values was recorded, this test cannot be used. #### 4.4.5 Test for deviation from the specified distribution model The recorded measured values are to be tested to see whether they exhibit a significant deviation from the distribution model that was defined for the characteristic involved. To do this, in the case of a specified normal distribution, the Epps-Pulley test (see ISO 5479) shall be used and in the case of a different specified model, e.g., with a type I or II absolute value distribution, the chi-square test (see [1]) shall be used with a confidence level of 95%. A deviation from the specified distribution model can occur, e.g., due to different material batches during the sampling (mixed distribution, see example 3 in Section 5). A deviation from the specified distribution model can occur, e.g., due to sampling from different tools (mixed distribution, see also Section 3, in Figure 5). ##### 4.4.6 Evaluation according to normal distribution In the case of a specified normal distribution or one that is approximated according to criteria (1.13), (1.22), in which the measured values do not exhibit any significant deviation from the distribution model, the calculation of the capability indices is carried out according to formulas (2.1) to (2.5), depending on the tolerancing, whereby the dispersion range limits are determined according to (2.6). ###### 4.4.7 Evaluation according to specified model In the case of a different specified distribution model, e.g., type I or II absolute value distribution, in which the measured values do not exhibit any significant deviation from the distribution model, the calculation of the capability indexes are carried out according to formulas (2.1) to (2.5), whereby the statistics of the distribution to be fitted are determined according to formulas (2.15) and (2.16) or (2.24) and (2.25) respectively with the use of the approximated function (2.18) or (2.27) respectively and the dispersion range limits can be calculated according to the approximated functions (2.19) or (2.28) respectively. Image Analysis: ### Analysis of the Visual Content **Aspect 1: Localization and Attribution** - The provided content appears to be a page from a document, labeled as "Page 26," and originates from "VW 101 30: 2005-02." **Aspect 4: Text Analysis** - The document includes several textual sections, each elaborating on different aspects of statistical tests relevant to quality assessments in manufacturing or engineering contexts. The identified sections are: 1. **Test for outliers (4.4.2):** - Discusses how to determine if measured values contain outliers using a distribution-free test method according to VW 101 33. - Outliers are measured values that significantly differ from others, indicating possible errors. 2. **Take outliers out of the calculation of statistics (4.4.3):** - States that outliers should not be removed but marked accordingly in graphic representations. 3. **Test for change of the production location (4.4.4):** - Indicates the use of the distribution-free Run Test to determine if the production location has changed systematically due to sampling. - The test checks for changes due to various factors like tooling wear or temperature influence. 4. **Test for deviation from the specified distribution model (4.4.5):** - Describes a process to test if values deviate significantly from a specified distribution model. - Different methodologies are noted, such as the Epps-Pulley test for normal distribution and the chi-square test for other models. 5. **Evaluation according to normal distribution (4.4.6):** - Specifies the evaluation of capability indexes when values don't significantly deviate from a specified normal distribution. 6. **Evaluation according to specified model (4.4.7):** - Details on evaluating capability indexes when values don't significantly deviate from a specified model different from the normal distribution. **Aspect 11: Metadata Analysis** - The metadata reveals the document type and standardized reference, indicating it is likely part of a technical or industrial standard specific to VW (Volkswagen) for quality assessment or testing procedures, dated 2005-02. **Aspect 12: Graph and Trend Analysis** - Although the page analyzed does not contain any graphical elements or data trends, it provides a detailed explanation of how such analyses should be carried out per the described methods. **Aspect 13: Graph Numbers** - There are references to various formulas and sections that seem to contain mathematical formulations/details about the mentioned tests: - Formulas (2.1) to (2.5), (2.15), (2.16), (2.18), (2.19), (2.24), (2.25), (2.27) and (2.28). - Example references can be found in sections 3 and 5, as well as Figure 5. **Aspect: Ablaufprozesse (Process Flows)** - The document describes specific statistical testing flows: - Identification of outliers. - Inclusion/exclusion in statistical calculations. - Testing for production location changes. - Assessing deviations from distribution models. - Evaluation based on normal distribution and specific models. **Aspect: Prozessbeschreibungen (Process Descriptions)** - **Test for outliers:** Process of identifying outliers using VW standard methods. - **Run Test for production location:** A statistical test to identify systematic changes in production settings. - **Epps-Pulley/Chi-square Tests:** Specific statistical tests to identify deviations from distribution models. - **Evaluation Processes:** Methods for evaluating using normal distribution models and specified non-normal distribution models. **Conclusion** The provided text is highly technical, focusing on methods for identifying and analyzing statistical anomalies and testing in the production and manufacturing context. The detailed descriptions and references to specific statistical processes imply its usage for quality control and ensuring product consistency. #################### File: VW%2010130_EN%281%29.pdf Page: 27 Context: # 4.4.8 Distribution-free evaluation If the statistical test results in a contradiction between the recorded measured values and the specified distribution model, or if not fitting distribution model can be found for the considered production characteristic, a distribution-free calculation of the capability indexes is carried out according to formulas (2.29) to (2.40). # 4.5 Documentation The documentation of an MFI regarding a characteristic must contain the following information and representations: ## Header data: - Department, coordinator and preparation date - Information regarding the part - Designation, nominal dimension and tolerance of the characteristic - Machine data - Test equipment data - Production time period ## Results: - Graphical representation of the single value curve with the random sample mean values with limit lines of the tolerance zone (as long as single values were recorded) - Histogram with a fitted distribution model, limit lines of the tolerance zone and dispersion range, as well as mean value and/or median value line - Representation in the probability grid with the fitted distribution model, limit lines of the tolerance zone and dispersion range, as well as mean value and/or median value line (see [2]) - Number of measured values - Number of measured values evaluated or outliers found - Estimated value of the production location - Estimated values of the dispersion range limits or the estimated value of the dispersion range - The distribution model used - The result of the test for change of the production location - The result of the test for deviation from the specified distribution model - Calculated capability indexes Cm and Cmk (to two digits after the decimal) - Required limit values for Cm and Cmk ## References and notes: - If necessary, reference to restricted MFI - If necessary, special agreements between supplier and customer - If necessary, special events during the sampling Image Analysis: ### 1. Localization and Attribution: - Document consists of a single page numbered Page 27. - No images to be numbered or located; text-based document. ### 4. Text Analysis: - **Heading:** The main heading is "4.4.8 Distribution-free evaluation" followed by a subheading "4.5 Documentation." - **Content:** - **4.4.8 Distribution-free evaluation:** Describes the process when statistical test results contradict recorded measured values or specified distribution models and calls for a distribution-free calculation of capability indexes. - **4.5 Documentation:** Outlines the required documentation for an MFI regarding a characteristic, detailing various types of required information and representations. - **Header Data:** Mention of several required details including department, coordinator, preparation date, and machine data. - **Results:** List of results that need to be documented, such as graphical representations, number of measured values, and calculated capability indexes. - **References and notes:** Highlights special considerations such as referencing restricted MFI and agreements between supplier and customer. **Significance:** - This section defines comprehensive criteria for evaluating statistical data and documenting it in a manufacturing or production environment. The text’s emphasis on detailed documentation ensures consistency, accuracy, and accountability in reporting measurements and test results. ### 9. Perspective and Composition: - **Perspective:** The document is presented from a standard top-down viewpoint, typical for technical manuals or guidelines. - **Composition:** The text is formatted in a structured manner with headings and subheadings to separate sections clearly. Bullet points are used to enumerate required data and results, making the information easily scannable and organized. ### 10. Contextual Significance: - **Context in Document:** This text serves as a guideline for documenting measurement data and test results in detail to facilitate quality control and process validation. - **Overall Message:** Ensures the accuracy and reliability of production data reporting, critical for maintaining and improving product quality and manufacturing efficiency. ### 14. Prozessbeschreibungen (Process Descriptions): - **Documentation of Measurement Data:** - Record fixed header data like department, coordinator, preparation date, machine data, etc. - Document results including graphical representations and statistical data points such as mean values, tolerance ranges, etc. - Note special considerations and required references as needed. - Purpose is to create a thorough record for quality assurance and validation. This document serves as a technical procedural guide to manage and document measurement data and its evaluation systematically. #################### File: VW%2010130_EN%281%29.pdf Page: 28 Context: # 4.6 Results Evaluation Whether a machine can be evaluated capable with respect to production of a considered characteristic depends on the following result evaluation: - If outliers occur during an evaluation, their cause has to be clarified. Outliers shall only be caused by incorrect measurements or be wrongly identified as such using the outlier test based on the specified probability of error of 1%. Otherwise, the machine shall be evaluated as incapable. If more than 5% of the recorded measured values or more than 2 values are identified as outliers, there shall be a test of whether the test process is faulty. Then the MFI is to be repeated if necessary. - If the production location has changed significantly during the sampling, generally its cause has to be known and the effect has to be acceptable in order to meet the requirement for machine capability (see last paragraph of this section for exception). - If a distribution-free evaluation exists due to a significant deviation from the specified distribution model and if no other distribution model can be assigned to the considered characteristic without contradiction, the cause must be known and the effect must be acceptable³, in order to meet the requirement for machine capability (see last paragraph of this section for exception). Unless otherwise agreed, the capability indexes determined with an effective random sample size of \( n_e \geq 50 \) (i.e. without outliers) must meet the requirement: \[ \bar{C}_m \geq 2.0 \quad \text{and} \quad \bar{C}_{pk} \geq 1.67 \quad \text{for a characteristic with two-sided tolerance zones} \] \[ \bar{C}_{pk} \geq 1.67 \quad \text{for a characteristic with one-sided tolerance zone only} \] in order for the machine to be evaluated as capable. In this case, for comparison to the limit values, the capability indexes determined are to be rounded to two digits after the decimal so that, e.g., a determined value of \( \bar{C}_{pk} = 1.66545 \) will still meet the requirement after the resulting rounding to 1.67. With an effective random sample size of \( 20 \leq n < 50 \), correspondingly higher limit values shall be complied with. The fitted limit values are given in Table 3 for a few random sample sizes. If there is agreement on other limit values on the basis of \( n_e \geq 50 \), the corresponding fitted limit values are to be determined according to formulas (3.7) to (3.9). ### Table 3 - Limit Values for Machine Capability for \( 20 \leq n \leq 50 \) | \( n_e \) | \( \bar{C}_m \geq \) | \( \bar{C}_{pk} \geq \) | |-----------|----------------------|--------------------------| | 20 | 2.28 | 1.93 | | 25 | 2.19 | 1.85 | | 30 | 2.13 | 1.79 | | 35 | 2.08 | 1.75 | | 40 | 2.05 | 1.72 | | 45 | 2.02 | 1.69 | | 50 | 2.00 | 1.67 | If a capability index results that is lower than the corresponding limit value, the machine is to be evaluated as incapable. Image Analysis: ### Comprehensive Examination of Visual Content #### Localization and Attribution: 1. **Image Location**: The entire content is contained within a single continuous page. 2. **Image Number**: Image 1. #### Text Analysis: 1. **Extracted Text**: - **Title**: "4.6 Results evaluation" - Detailed explanation discussing the evaluation of machine capability, the handling of outliers, and the conditions under which a machine can be considered capable. - Conditions for outliers and distribution-free evaluation. - Requirements for effective random sample sizes, specified capability indexes, and tolerance zones. - **Table**: "Table 3 - Limit values for machine capability for 20 ≤ ne ≤ 50" - **Table Values**: - For [nₑ = 20]: ĉₚ ≥ 2.28, ĉₚₖ ≥ 1.93 - For [nₑ = 25]: ĉₚ ≥ 2.19, ĉₚₖ ≥ 1.85 - For [nₑ = 30]: ĉₚ ≥ 2.13, ĉₚₖ ≥ 1.79 - For [nₑ = 35]: ĉₚ ≥ 2.08, ĉₚₖ ≥ 1.75 - For [nₑ = 40]: ĉₚ ≥ 2.05, ĉₚₖ ≥ 1.72 - For [nₑ = 45]: ĉₚ ≥ 2.02, ĉₚₖ ≥ 1.69 - For [nₑ = 50]: ĉₚ ≥ 2.00, ĉₚₖ ≥ 1.67 - Footnotes and references to formulas and paragraphs. #### Diagram and Chart Analysis: 1. **Table Analysis**: - **Title**: "Table 3 - Limit values for machine capability for 20 ≤ nₑ ≤ 50" - Presents the fitted limit values for machine capability indexes (ĉₚ and ĉₚₖ) for different effective sample sizes (nₑ). - **Axes**: No graphical axes as it is a table. - **Key Insights**: - For smaller sample sizes, the required capability indexes are higher. - As the sample size increases, the limit values for ĉₚ and ĉₚₖ decrease. #### Ablaufsprozesse (Process Flows): 1. **Process Flow Description**: - The process flow involves evaluating a machine's production capability considering specific criteria (outliers, production location changes, distribution-free evaluation). - The overall flow hinges on monitoring capability indexes and ensuring that the system meets requirements defined by fit limit values based on sample size. #### Prozessbeschreibungen (Process Descriptions): 1. **Description**: - **Outliers Evaluation**: Clarify causes and ensure correct measurements. - **Production Location Changes**: Identify and accept changes if they significantly alter the sampling. - **Distribution-free Evaluation**: Address significant deviations and maintain acceptable fit limit values. - **Capability Indexes Determination**: Calculate and evaluate by rounding to two decimal digits under specified conditions. #### Typen Bezeichnung (Type Designations): 1. **Types/Categories**: - **Two-sided Tolerance Zones**: Capability index values ĉₚ ≥ 2.20, ĉₚₖ ≥ 1.67 required. - **One-sided Tolerance Zones**: Capability index value ĉₚₖ ≥ 1.67 required. #### Trend and Interpretation: 1. **Identified Trends**: - Higher sample sizes result in slightly relaxed capability index values. 2. **Interpretation**: - Ensuring machine capability through rigorous distribution and outlier checks indicates a gradually stable and reliable production setup with increased sample sizes, leading to relaxation in capability indexes. #### Contextual Significance: 1. **Analysis in Document Context**: - This section is likely part of a larger technical standard (VW 101 30: 2005-02) and provides crucial guidelines for evaluating machine capability. - It ensures uniformity and reliability in production by adhering to the defined capability indexes. #### Anomaly Detection: 1. **Identified Anomalies**: None detected within the provided content. #### Perspective and Composition: 1. **Description**: - The page is laid out in a standard technical document format, with headers, paragraphs, and a table that outlines detailed specifications and guidelines. By analyzing these various aspects of the visual content, the document provides thorough guidelines on evaluating machine capability, emphasizing the importance of outlier analysis, impact of production changes, and maintaining acceptable capability indexes across specific sample sizes. #################### File: VW%2010130_EN%281%29.pdf Page: 29 Context: With a determined capability index of \( c_{mk} \geq 2.33 \) (corresponds to 14 σ) and additionally \( c_{p} \geq 2.67 \) (corresponds to 16 σ) for characteristics with two-sided tolerance zones, the machine can be evaluated as capable with respect to the considered characteristic, even independent of a significant location change or deviation from the specified distribution model. ## 4.7 Machine Optimization For the case where the machine capability cannot be documented with respect to the tested characteristic, measures for machine optimization are necessary. To do this, the corresponding influences are to be identified (e.g., using ODE statistical test methodology) and eliminated. ## 4.8 Handling Incapable Machines If it is not possible to achieve machine capability with machine optimizations that are economically reasonable, there shall first be an investigation using statistical tolerance calculation according to VW 01057 of whether a tolerance extension is possible to achieve the machine capability. If machine capability cannot be achieved using these measures, a decision is to be made whether the machine will be accepted according to special regulations agreed upon in writing or not. These special regulations shall contain the following points: - Reasons for the acceptance - Risk and cost considerations - If necessary, restricting production and additional test conditions - Specification of the responsibility Image Analysis: ### Comprehensive Examination of the Visual Content **Image 1:** 1. **Localization and Attribution:** - This document is a single-page text. - Identified as Image 1. 2. **Text Analysis:** - Title: "VW 101 30: 2005-02" - The main body text includes sections titled "4.7 Machine optimization" and "4.8 Handling incapable machines." **Section: 4.7 Machine optimization** - Content: Discusses measures necessary for machine optimization if the machine capability cannot be documented with respect to the tested characteristic. - Significance: Emphasizes the importance of identifying and eliminating influences to achieve machine optimization. **Section: 4.8 Handling incapable machines** - Content: Discusses steps to take if machine capability cannot be achieved through optimization. It outlines the need for statistical tolerance calculation and lists the points to be included in special regulations. - Significance: Highlights the procedural steps for dealing with incapable machines, ensuring compliance with VW standards and guidelines. - Bulleted points: - Reasons for the acceptance - Risk and cost considerations - If necessary, restricting production and additional test conditions - Specification of the responsibility The content in these sections is focused on maintaining and ensuring the capability of machines within specified tolerance zones. **Contextual Significance:** - This page is likely part of a technical or operational manual, possibly a standard document specifying procedures and standards for machine capability and optimization. - It contributes to the overall theme of maintaining stringent quality and operational standards. **Perspective and Composition:** - The document has a standard text-based format typical of technical guidelines or standards. - The composition is straightforward, with headings and bullet points for ease of understanding and reference. This concludes the analysis of Image 1. The visual and textual content provides detailed procedural information regarding machine optimization and handling incapable machines, following VW standards. #################### File: VW%2010130_EN%281%29.pdf Page: 30 Context: # 5 Examples ## Example 1: Shaft diameter with a nominal dimension of 20 mm, a lower limiting value of \( G_{u} = 19.7 \) mm and an upper limiting value of \( G_{l} = 20.3 \) mm. Using the statistical tests, no outliers resulted, no significant change of the production location occurred and there was no significant deviation from an expected normal distribution from \( n = 50 \) measured values of the random sample. The following random sample statistics are determined: \[ \bar{x} = 20.05 \quad \text{and} \quad \bar{s} = 0.05 \] Therefore, according to formula (2.11), the following estimated values of the dispersion range limits result for the normally distributed populations: \[ \hat{x}_{0.135\%} = \bar{x} - 3 \cdot \bar{s} = (20.05 - 3 \cdot 0.05) \text{ mm} = 19.9 \text{ mm} \] \[ \hat{x}_{99.865\%} = \bar{x} + 3 \cdot \bar{s} = (20.05 + 3 \cdot 0.05) \text{ mm} = 20.2 \text{ mm} \] And from that, ultimately, the following capability indexes result: \[ \bar{c}_{m} = \frac{G_{u} - G_{l}}{\hat{x}_{99.865\%} - \hat{x}_{0.135\%}} = \frac{20.3 - 19.7}{20.2 - 19.9} = \frac{0.6}{0.3} = 2.0 \] \[ \bar{c}_{k} = \min \left( \frac{G_{u} - \bar{x}}{\hat{x}_{99.865\%} - \bar{x}} , \frac{\bar{x} - G_{l}}{\bar{x} - \hat{x}_{0.135\%}} \right) = \min \left( \frac{20.3 - 20.05}{20.2 - 20.05}, \frac{20.05 - 19.7}{20.05 - 19.9} \right) = \min \left( \frac{0.25}{0.15}, \frac{0.35}{0.15} \right) = \frac{20.3 - 20.05}{20.2 - 20.05} = 1.67 \] Because of the capability indexes, it is thus verified that the machine just meets the capability requirements with respect to the considered shaft diameters. Figure 12 shows the evaluation result: ![Figure 12 - Example of a production with the model of a normal distribution and the capability indexes \( c_{m} = 2.0 \) and \( c_{k} = 1.67 \)](url) Image Analysis: ### Analysis of the Visual Content #### 1. **Localization and Attribution:** - The single image located on the page can be referred to as **Image 1**. #### 2. **Object Detection and Classification:** - **Image 1:** - **Objects Detected:** - Text on the upper portion of the image. - A graph on the lower portion of the image. #### 3. **Scene and Activity Analysis:** - **Image 1:** - **Scene:** - The image presents an example related to statistical measurements for production consistency, specifically focusing on shaft diameter. - **Activities:** - The image illustrates the process of calculating and evaluating statistical metrics to verify production quality, including capability indices. #### 4. **Text Analysis:** - **Image 1:** - **Text Extracted:** - "Page 30 VW 101 30: 2005-02" - "5 Examples Example 1: Shaft diameter with a nominal dimension of 20 mm, a lower limiting value of GL = 19.7 mm and an upper limiting value of GU = 20.3 mm Using the statistical tests, no outliers resulted, no significant change of the production location occurred and there was no significant deviation from an expected normal distribution from n = 50 measured values of the random sample. The following random sample statistics are determined: z̄ = z̄ = 20,05 and d = s = 0,05 ... etc." - **Significance:** - The text provides a detailed description of a statistical analysis example for the production of shafts, describing the calculation of capability indices and their importance in quality control. #### 5. **Diagram and Chart Analysis:** - **Image 1:** - **Graph:** - **Axes:** - X-axis: Measured value (ranges from 19.70 to 20.30) - Y-axis: Frequency (no specific scale values provided) - **Data:** - Plot shows a distribution of measured shaft diameters with a mean value around 20.05. - Indicated points on the horizontal axis: x̂0.135% and x̂99.865% - **Legend:** - GL: 19.7 mm - GU: 20.3 mm - **Key Insights:** - The graph demonstrates a normal distribution of measured shaft diameters, with calculated indices \(c_m\) and \(c_{mk}\) to validate compliance with production standards. #### 6. **Product Analysis:** - **Image 1:** - **Product:** Shaft with a nominal diameter of 20 mm. - **Key Features:** - Measurement range: 19.7 mm to 20.3 mm. - Mean value: 20.05 mm. - Standard deviation: 0.05 mm. #### 7. **Anomaly Detection:** - **Image 1:** - **Anomalies:** - No anomalies detected in the data or presentation. #### 8. **Color Analysis:** - **Image 1:** - **Dominant Colors:** - The image utilizes shades of black, grey, and white. - **Impact:** - The neutral color scheme emphasizes clarity and professionalism, appropriate for a technical document. #### 9. **Perspective and Composition:** - **Image 1:** - **Perspective:** - The text is presented in a straightforward, document-style format. - The graph is shown from a straight-on perspective, typical of technical visualizations. - **Composition:** - Structured into two main sections: descriptive text above and an illustrative graph below. #### 10. **Contextual Significance:** - **Image 1:** - **Overall Context:** - The image is part of a technical document, likely related to quality control in manufacturing. - **Contribution:** - The image offers practical examples of statistical quality assessment methods, enhancing understanding of the theoretical concepts discussed in the document. #### 12. **Graph and Trend Analysis:** - **Image 1:** - **Trend Analysis:** - The normal distribution curve indicates that the production process is consistent and within specified limits. - **Interpretation:** - Capability indices \(c_m\) and \(c_{mk}\) confirm that the process meets the required quality standards. #### 14. **Tables:** - **Image 1:** - No tables are included in the image. #### 15. **Ablaufprozesse (Process Flows):** - **Image 1:** - Describes the process of calculating and verifying statistical capability indices. #### 16. **Prozessbeschreibungen (Process Descriptions):** - **Image 1:** - Detailed process for statistical evaluation of shaft diameters involving calculating dispersal limits and capability indices using specific formulas. #### 18. **Trend and Interpretation:** - **Image 1:** - **Trend:** - The production process is stable and meets quality requirements as demonstrated by capability indices. - **Interpretation:** - The normal distribution of data suggests a well-controlled production process. In summary, the image provides a clear example of using statistical methods to ensure manufacturing quality, supported by detailed textual explanations and an illustrative graph. #################### File: VW%2010130_EN%281%29.pdf Page: 31 Context: # Example 2 **Hole with a maximum permissible position deviation of \( G_o = 0.2 \, \text{mm} \)** From the \( n = 50 \) measurements of the random sample, the statistical tests did not result in any outliers, no significant location change, and no significant deviation from an expected type II absolute value distribution. The following random sample statistics were determined: \[ \hat{x} = 0.038 \, \text{mm} \quad \text{and} \quad s = 0.02 \, \text{mm} \] The random sample statistics result in the ratio: \[ \frac{\hat{x} - G_o}{s} = \frac{0.038 - 0.02}{0.02} = 1.9 \] Since, because of the random dispersion of the random sample statistics, this value is lower than the limit value 1.9131 according to condition (2.23), the ratio is set to this limit value, which in turn results in an eccentricity of \( z = 0 \). In this way, the second parameter value of the type II absolute value distribution to be fitted is calculated according to special case (2.26) as follows: \[ \sigma_{N_{99.865}} = 1.526 - \hat{x} = 1.526 - 0.038 = 0.305 \, \text{mm} \] The estimated values of the dispersion range limits result from formula (2.27): \[ \hat{x}_{0.135} = 0.0773 - \sigma \cdot 0.0773 \cdot 0.02 \, \text{mm} = 0.0016 \, \text{mm} \] Finally, according to formulas (2.3) and (2.4), the following capability indexes result: \[ \hat{C}_{p} = \frac{G_o}{s} = \frac{0.2}{0.111 - 0.0016} = 1.83 \] \[ \hat{C}_{mk} = \frac{G_o - \hat{x}}{s} = \frac{0.2 - 0.038}{0.111 - 0.038} = 2.22 \] Figure 13 illustrates the evaluation result. ## Figure 13 - Example of a production with the model of a type II absolute value distribution and the capability indexes \( \hat{C}_{p} = 1.83 \) and \( \hat{C}_{mk} = 2.22 \) Because of the determined statistic \( C_{mk} \), it is verified that the machine meets the requirement well with respect to the position deviation of a hole. Although no limit value is specified for statistic \( C_{mk} \) in the case with an upper limited tolerance zone, comparison to the \( C_{mk} \) value provides information on the production location and the smaller \( C_{mk} \) value indicates that the location lies closer to the natural limit zero than to the upper limiting value. Image Analysis: ### Analysis of the Visual Content in Detail: --- #### 1. **Localization and Attribution:** - **Image 1:** - Present on the lower part of the page. - Referred to as "Figure 13" in the document. #### 3. **Scene and Activity Analysis:** - **Image 1:** - The scene depicts a graph titled "Figure 13 - Example of a production with the model of a type II absolute value distribution and the capability indexes \( \hat{c}_{m} = 1.83 \) and \( \hat{c}_{mk} = 2.22 \)". - The graph shows the measured values on the x-axis and the frequency on the y-axis, illustrating the statistical distribution of a production process. #### 4. **Text Analysis:** - The text describes a statistical analysis conducted on a sample with a maximum permissible position deviation of \( G_0 = 0.2 \) mm. - Key excerpts: - "Hole with a maximum permissible position deviation of \( G_0 = 0.2 \) mm." - "From the n = 50 measurements of the random sample, the statistical tests did not result in any outliers, no significant location change and no significant deviation from an expected type II absolute value distribution. The following random sample statistics were determined:..." - Detailed calculations and results about second parameter values, dispersion range limits, and capability indexes \( \hat{c}_{m} \) and \( \hat{c}_{mk} \). - Significance: These details explain the statistical validation of the production process, ensuring that it meets the specified tolerances and quality requirements. #### 5. **Diagram and Chart Analysis:** - **Image 1:** - The graph shows the distribution of measured values of a production sample. - **Axes and Scales:** - X-axis (Measured Value): 0 to 0.20 with intervals marked at every 0.02. - Y-axis (Frequency): Represents the frequency of measurements within each interval. - **Legend and Key Insights:** - Dispersion range limits \( \hat{x}_{0.135} \) and \( \hat{x}_{0.865} \) are marked. - The peak of the distribution is around \( 0.03 \), indicating the most frequent measurement intervals. - The graph illustrates that the majority of measurements fall within the acceptable range defined by the capability indexes, validating the production quality. #### 6. **Product Analysis:** - The document details the statistical quality control process for a production sample, emphasizing how the measurements conform to specified tolerances. #### 8. **Color Analysis:** - **Image 1:** - Dominant Colors: Black and shades of grey. - Impact: The use of monochrome colors, with black lines and grey shading, adds to the formal and technical appearance, emphasizing the accuracy and precision of the information presented. #### 9. **Perspective and Composition:** - **Image 1:** - Perspective: The graph uses a standard front-facing view. - Composition: The elements are neatly arranged with clearly labeled axes, ensuring the data is easily interpretable. The key points such as \( \hat{x}_{0.135} \), \( G_0 \), and \( \hat{x}_{0.865} \) are highlighted for clarity. #### 13. **Graph Numbers:** - **Image 1:** - **Data Points:** - \( 0.021 \), \( 0.036 \), \( 0.053 \), \( 0.065 \), etc., on the X-axis representing the measured values. - Frequency corresponding to each interval is depicted by the height of the bars on the Y-axis. #### **Ablaufprozesse (Process Flows):** - The text details the process flow of statistical measurement and evaluation for the production quality control, including the determination of capability indexes and deviation limits. #### **Prozessbeschreibungen (Process Descriptions):** - Describes the statistical methods used for evaluating a production process, including formulas and results for dispersion range limits and capability indexes. #### **Trend and Interpretation:** - The measurements show a consistent trend within the defined acceptable range, with few outliers, demonstrating a stable and controlled production process that meets specified quality standards. #### **Tables:** - Although there is no distinct table, the textual content and diagram combine to present detailed statistical data about the production sample. This visual content provides a thorough statistical analysis of a production process, confirming the quality and consistency of the manufacturing outcomes. #################### File: VW%2010130_EN%281%29.pdf Page: 32 Context: # Example 3: Shaft diameter with a nominal dimension of 20 mm, a lower limiting value of \( G_e = 19.7 \) mm and an upper limiting value of \( G_u = 20.3 \) mm. From \( n = 50 \) measured values of the random sample, due to the statistical tests, no outliers resulted and no significant location change resulted, but a significant deviation from an expected normal distribution did. Therefore, a distribution-free evaluation is carried out according to Section 3.22. To do so, the following random sample statistics were determined: \[ \bar{x}_{50\%} = \bar{x} = 20.02 \, \text{mm}, \, x_{max} = 20.19 \, \text{mm} \, \text{and} \, x_{min} = 19.85 \, \text{mm} \] Correction factor according to formula (2.38) and Table 1: \[ k = \frac{6}{d_d} = \frac{6}{4.5} = 1.33 \] Range according to formula (2.37): \[ R = x_{max} - x_{min} = 20.19 - 19.85 = 0.34 \, \text{mm} \] According to formula (2.36): \[ x_c = \frac{x_{max} + x_{min}}{2} = \frac{20.19 + 19.85}{2} = 20.02 \, \text{mm} \] Estimated values for dispersion range limits according to formula (2.35): \[ \begin{align*} \hat{x}_{L} &= x_c - k \frac{R}{2} = 20.02 - 1.33 \frac{0.34}{2} = \frac{20.246}{19.794} \, \text{mm} \\ \hat{x}_{U} &= x_c + k \frac{R}{2} = 20.02 + 1.33 \frac{0.34}{2} = \frac{20.246}{19.794} \, \text{mm} \end{align*} \] Thus the formulas (2.29) and (2.30) resulted in the capability indexes: \[ \bar{c}_m = \frac{G_u - G_L}{\bar{x} - \hat{x}_{L}} = \frac{20.3 - 19.7}{20.02 - 20.246} = 1.33 \] \[ \bar{c}_{mk} = \min \left( \frac{G_u - \bar{x}_{50\%}}{\bar{x}_{50\%} - \hat{x}_{L}}, \frac{G_L - \bar{x}_{50\%}}{\bar{x}_{50\%} - \hat{x}_{U}} \right) = \frac{20.3 - 20.02}{20.246 - 20.02} = 1.24 \] Figure 14 illustrates the evaluation result. ## Example 14 - Example of a production without defined distribution model with the capability indexes \( c_{m} = 1.33 \) and \( c_{mk} = 1.24 \) From the capability indexes determined, it can be seen that the machine does not meet the capability requirement with respect to the considered characteristic. The significant deviation from an expected normal distribution supplies interesting information in this context. Because of this, an optimization potential can be recognized, in this case through mixed distribution. Image Analysis: ### Visual Content Analysis #### Image Details: 1. **Localization and Attribution:** - **Image 1**: There is only one image present on the page. 2. **Object Detection and Classification:** - The image features a histogram chart, several numerical calculations, and statistical data. Key elements include text, a bar graph, and mathematical formulas. 3. **Scene and Activity Analysis:** - The scene depicts a technical/engineering document with a focus on statistical analysis and capability evaluation. The activities involve mathematical and statistical examination related to production measures. 4. **Text Analysis:** - The text in the image provides a detailed explanation of statistical calculations for a shaft diameter. Key excerpts include: - "Example 3:" At the beginning, it describes a problem statement involving various measures and statistical tolerance limits. - Several formulas and calculations are displayed. - Example 14 provides an evaluation result and showcases the graph/histogram. - Annotated text at the bottom explains the significance of capability indexes c_m and c_mk, and provides conclusions based on the analysis. 5. **Chart Analysis:** - The image features a bar graph (Histogram) representing the frequency distribution of measured values. - **Axes**: - X-axis: "Measured value" with intervals ranging from 19.75 to 20.25. - Y-axis: "Frequency". - **Data**: The bar heights represent the frequency of occurrence for each range of measured values. - **Insight**: The chart indicates a normal distribution of measured values around the central value, detailing an evaluation on production capability. 6. **Product Analysis:** - The products in discussion are shaft diameters with specific measurements and tolerance limits. - The primary focus is on the production consistency and statistical evaluation of the shaft dimensions. 7. **Anomaly Detection:** - The statistical analysis shows a deviation from the expected normal distribution, suggesting an area for potential optimization, even indicating mixed distribution as a noticeable anomaly. 8. **Color Analysis:** - The document uses monochrome (black and white), a typical color scheme for technical documents to emphasize on clarity and readability of text and graphs. 9. **Perspective and Composition:** - The document is presented from a straightforward, eye-level perspective, typical for technical manuscripts. The composition is logical, with text leading into formulas and culminating in the graphical representation. 10. **Contextual Significance:** - The image and text collectively contribute to the technical evaluation of production quality and highlight the importance of statistical analysis in assessing manufacturing processes. 11. **Graph and Trend Analysis:** - The provided graph emphasizes the distribution of measured shaft diameters. The trend suggests a central tendency but with visible deviations, important for evaluating the machining process capability. 12. **Process Descriptions:** - Detailed process descriptions include calculating correction factors, range, and estimated values for dispersion based on statistical formulas. 13. **Typen Bezeichnung (Type Designations):** - Designations like c_m (Process Capability Index) and c_mk (Corrected Capability Index) are particularly highlighted. Their values denote the precision of the manufacturing process. 14. **Trend and Interpretation:** - The general trend in the analysis shows that while the process is centered around the target measurement, there are variations indicating mixed distributions, a critical point for further quality improvement. ### Summary: This page provides an elaborate statistical analysis related to manufacturing shaft diameters, presenting calculated tolerance limits and capability indexes. The supporting histogram visually complements the textual and numerical analysis, reinforcing the critical need for precision in manufacturing processes. Overall, the document embodies a thorough approach to understanding and optimizing production quality. #################### File: VW%2010130_EN%281%29.pdf Page: 33 Context: # 6 Referenced standards | Standard Code | Description | |---------------|-----------------------------------------------------------------------------------------| | VW 010 56 | Drawings; Form and Position Tolerances | | VW 010 57 | Statistical Tolerance Calculation of Dimension Chains | | VW 101 33 | Test auf Ausreißer (Test for Outliers – currently only available in German) | | DIN 55319 | Quality Capability Statistics (QCS) | | ISO 5479 | Statistical Interpretation of Data - Tests for Departure from the Normal Distribution | # 7 Referenced literature 1. Graf, Henning, Stange, Willich. *Formeln und Tabellen der angewandten mathematischen Statistik*. Springer Publishing Group, third edition, 1987. 2. Küh Meyer, M.. *Statistische Auswertungsmethoden für Ingenieure*. Springer Publishing Group, 2001. 10) In this Section, terminological inconsistencies may occur as the original titles are used. Image Analysis: ### Analysis of the Visual Content: #### Localization and Attribution: - **Image Location and Numbering:** - There is only one image on the page. #### Text Analysis: - **Detected Text:** - The main headings on the page are "6 Referenced standards" and "7 Referenced literature." - The standards listed include: - VW 010 56: Drawings; Form and Position Tolerances - VW 010 57: Statistical Tolerance Calculation of Dimension Chains - VW 101 33: Test auf Ausreißer (Test for Outliers – currently only available in German) - DIN 55319: Quality Capability Statistics (QCS) - ISO 5479: Statistical Interpretation of Data - Tests for Departure from the Normal Distribution - The referenced literature includes: - [1] Graf, Henning, Stange, Willrich, Formeln und Tabellen der angewandten mathematischen Statistik, Springer publishing group, third edition 1987 - [2] Kühlmeyer M., Statistische Auswertungsmethoden für Ingenieure, Springer publishing group, 2001 #### Contextual Significance: - **Overall Document Theme:** - This page seems to be from a technical document related to statistical methods and standards used in engineering or quality management. - The referenced standards and literature indicate a focus on statistical analyses and procedures relevant to precise measurements and quality control in engineering contexts. #### Additional Aspects: - **Ablaufprozesse (Process Flows):** - No process flows depicted. - **Prozessbeschreibungen (Process Descriptions):** - This page does not provide detailed process descriptions but references standards and literature that likely contain relevant processes. - **Typen Bezeichnung (Type Designations):** - The types or categories mentioned are statistical standards and quality control methods (e.g., methods for tolerance calculation, outliers testing). ### Conclusion: This image contains information about standards and literature references relevant to engineering statistical methods and quality control. Specifically, it lists recognized standards and foundational literature that could be pertinent to professionals in the field seeking guidance on measurement tolerances, statistical analyses, and data interpretation. #################### File: VW%2010130_EN%281%29.pdf Page: 34 Context: # 8 Keyword index | Key word | Page | |---------------------------------------|----------| | A | | | Absolute frequency α | 10, 17 | | Absolute cumulative frequency A | 17 | | α-Risk | 20 | | Alternative hypothesis | 20 | | Fitted capability limit values | 19, 28 | | Outlier | 20, 26 | | Confidence level γ | 20, 26 | | B | | | Conditions for the machine capability investigation | 24 | | β-Risk | 20 | | Absolute value distribution, type I | 5, 11 | | Absolute value distribution, type II | 7, 13 | | Machine at operating temperature | 24 | | C | | | Capability | 3 | | Chi-square distribution | 18 | | D | | | Data analysis | 25 | | Density function f(x) | 4 | | Documentation | 27 | | E | | | Restricted machine capability investigation | 25 | | Effective random sample size nₑ | 10, 24 | | Epps-Pulley test | 20, 26 | | Results evaluation | 28 | | Expected value for the w-distribution dₕ | 17 | | Eccentricity z | 7 | | F | | | Determination of capability | 8 | | Capability indexes cₘ and cₜₖ | 3, 9 | | Capability limit values | 18, 28 | | Production location | 3, 28 | | Production variation | 3, 8 | | Production sequence | 24 | | Degree of freedom | 18 | | G | | | Limit values of machine capability | 18, 28 | | H | | | Hampel test | 20 | | Frequency distribution | 10, 17 | | Upper limiting value G₀ | 3, 9 | | I | | | Probability of error α | 20 | Image Analysis: ### Image Analysis **Localization and Attribution:** - **Image Position:** Image 1 - **Image Description:** A page from a document titled "Keyword Index." The document appears to be a technical or academic resource with key terms and their corresponding page numbers. **Text Analysis:** - The text is organized into two main columns: - **Key Word:** Lists specific terms or keywords. - **Page:** Indicates the page numbers where each keyword can be found. **Detected Text:** - **Title and Sections:** - "Page 34" - "VW 101 30: 2005-02" - "8 Keyword index" - **Columns:** - Column 1: "Keyword | Page" - Column 2: Lists of key terms and page numbers. - **Keywords and Page Numbers:** - **A:** - Absolute frequency α: 10, 17 - Absolute cumulative frequency A: 17 - α-Risk: 20 - Alternative hypothesis: 20 - Fitted capability limit values: 19, 28 - Outlier: 20, 26 - Confidence level γ: 20, 26 - **B:** - Conditions for the machine capability investigation: 24 - β-Risk: 20 - Absolute value distribution, type I: 5, 11 - Absolute value distribution, type II: 7, 13 - Machine at operating temperature: 24 - **C:** - Capability: 3 - Chi-square distribution: 18 - **D:** - Data analysis: 25 - Density function f(x): 4 - Documentation: 27 - **E:** - Restricted machine capability investigation: 25 - Effective random sample size nₑ: 10, 24 - Epps-Pulley test: 20, 26 - Results evaluation: 28 - Expected value for the w-distribution dn: 17 - Eccentricity z: 7 - **F:** - Determination of capability: 8 - Capability indexes Cm and Cmk: 3, 9 - Capability limit values: 18, 28 - Production location: 3, 28 - Production variation: 3, 8 - Production sequence: 24 - Degree of freedom: 18 - **G:** - Limit values of machine capability: 18, 28 - **H:** - Hampel test: 20 - Frequency distribution: 10, 17 - Upper limiting value Go: 3, 9 - **I:** - Probability of error α: 20 **Color Analysis:** - **Color Composition:** - The image consists of black text on a white background. - This high contrast makes the text easily readable. **Perspective and Composition:** - **Perspective:** - The image is scanned or photographed from a top-down perspective, showing a flat view of a single page. - The text is well-centered and uniformly spaced. - **Composition:** - The page is laid out in a structured format with two main columns. - The header section indicates the page number and a title. - Keywords on the left are aligned flush, with corresponding page numbers uniformly placed on the right. **Contextual Significance:** - **Overall Context:** - This page appears to be part of a larger technical document or manual. - The keyword index serves as a reference guide, allowing readers to quickly locate specific topics within the document. **Conclusion:** The image is a page from a technical document titled "Keyword Index," which serves as a glossary or reference guide. It is well-organized with keyword terms and their corresponding page numbers, aiding the reader in navigating the document. The monochromatic color scheme, primarily black text on a white background, enhances readability, and the structured layout ensures easy information retrieval. #################### File: VW%2010130_EN%281%29.pdf Page: 35 Context: # Key Word Index | Key Word | Page | |-----------------------------------------------|------| | K | | | Class width Δx | 17 | | Classified measured values | 10, 17 | | Correction factor k | 17 | | L | | | Location | 3 | | M | | | Machine optimization | 29 | | Machine malfunctions | 24 | | Median value | 16 | | Characteristic type | 4, 25 | | Characteristic value | 3 | | Measuring method | 24 | | Lower limiting value Gu | 3, 9 | | Mixed distribution | 26, 32 | | Mean value µ | 4, 10 | | N | | | Normal distribution | 4, 10 | | Null hypothesis | 20 | | Zero offset | 6 | | P | | | Parameter of a distribution | 3 | | Test variable | 20 | | Test value | 20 | | Test equipment use | 24 | | Q | | | Quantile | 9 | | - of the standardized normal distribution | 18 | | - of the chi-square distribution | 18 | | R | | | Rayleigh distribution | 7 | | Radial deviation r | 7 | | Blank batch | 24 | | Rounding of capability values | 28 | | Run test | 20 | | S | | | Estimation / estimated value | 8, 9 | | Threshold value | 20 | | Standard production conditions | 24 | | Significant change / deviations | 20 | | Range R | 17 | | Standard deviation σ | 4, 10 | | Standardized normal distribution | 5 | | - U Transformation | 5 | | - Distribution function Φ(μ₁) | 5 | | - Probability density function φ(u) | 5 | | Statistical tests | 20 | | Statistical tolerance calculation | 29 | Image Analysis: ### Analysis of Visual Content #### **1. Localization and Attribution:** - The provided visual content is a single page (Page 35) from a document titled "VW 101 30: 2005-02." - Since there is only one image on the page, we'll denote it as **Image 1**. #### **2. Object Detection and Classification:** - **Image 1** includes a textual index with keywords and corresponding page numbers. #### **3. Scene and Activity Analysis:** - **Image 1** is a textual scene showing an index list for a document. It lists various keywords in alphabetical order (K, L, M, N, P, Q, R, S) with corresponding page numbers. This page forms part of an index section used for quickly locating specific topics within the document. #### **4. Text Analysis:** - **Image 1** contains text organized into two columns: 'Key word' and 'Page.' - Key points: - **Keywords:** Terms related to statistical and machine-related concepts like "Class width Δx", "Correction factor k", "Machine optimization", "Measuring method," etc. - **Page Numbers:** Indicating where to find these topics within the document, aiding navigation and quick reference. #### **5. Diagram and Chart Analysis:** - There are no diagrams or charts in **Image 1**. #### **6. Product Analysis:** - No products are depicted. #### **7. Anomaly Detection:** - There are no visible anomalies or unusual elements in **Image 1**. #### **8. Color Analysis:** - The page is predominantly black and white text. #### **9. Perspective and Composition:** - **Image 1** is a straightforward flat view of a textual document page. The text is well-aligned and organized into columns, making it easy to navigate. #### **10. Contextual Significance:** - **Image 1** serves as an index page in a document. Indexes are crucial for quickly locating information within lengthy documents, enhancing user experience and navigation. #### **12. Graph and Trend Analysis:** - No graphs are included in **Image 1**. #### **14. Ablaufprozesse (Process Flows):** - There are no specific process flows shown; the document references various topics and terms. #### **16. Typen Bezeichnung (Type Designations):** - **Image 1** includes type designations and classifications such as "normal distribution," "standard deviation σ," "quantile," etc., crucial for statistical references and studies. #### **14. Text and Table Analysis:** - **Image 1** comprises a table of contents-style format with categorized keywords and their respective page numbers. - **K:** e.g., "Class width Δx" - Page 17; "Correction factor k" - Page 17. - **M:** e.g., "Machine optimization" - Page 29; "Measuring method" - Page 24. - ...and so forth for the other letters. The keywords listed represent technical terms and concepts typically used in quality management, statistical analysis, and machine operation documentation. This detailed breakdown will aid in understanding the structure and purpose of the content within the provided page from the document. #################### File: VW%2010130_EN%281%29.pdf Page: 36 Context: # Key word | Keyword | Page | |--------------------------------------------|------| | Statistical percentage range | 18 | | Sampling | 24 | | Random sample range | 24 | | Dispersion range limits | 3, 10| | Swed-Eisenhard test | 20 | ## T | Term | Page | |-------------------------------------------|------| | Test - for outliers | 20, 26| | Test - for specified distribution model | 20, 26| | Test - for change of production location | 20, 26| | Tolerance expansion | 29 | | Tolerance zone | 3, 8 | | Toleranced characteristic | 4 | | Tolerance - on one side, upward | 9, 16| | Tolerance - on one side, downward | 9, 16| | Tolerance - on two sides | 9, 16| | Trend curve | 26 | ## V | Term | Page | |-------------------------------------------|------| | Variance σ² | 4 | | Distribution | 4 | | Distribution-free estimate | 16, 27| | Distribution function F(x) | 5 | | Distribution model | 4 | | Confidence range limit | 18 | | Premachining quality | 24 | ## W | Term | Page | |-------------------------------------------|------| | Probability p | 5 | | Probability density function f(x) | 4 | | Probability grid | 27 | | Weibull distribution | 8 | | Tooling change / adjustment | 24 | | w-Distribution | 17 | ## Z | Term | Page | |-------------------------------------------|------| | Random influences | 3 | Image Analysis: ### Text Analysis: **Image 1:** **Detected Text:** ``` Page 36 VW 101 30: 2005-02 Key word Page Statistical percentage range 18 Sampling 24 Random sample range 24 Dispersion range limits 3, 10 Swed-Eisenhard test 20 T Test - for outliers 20, 26 - for specified distribution model 20, 26 - for change of distribution location 20, 26 Tolerance expansion 29 Tolerance zone 3, 8 Toleranced characteristic 4 - on one side, upward 9, 16 - on one side, downward 9, 16 - on two sides 9, 16 Trend curve 26 V Variance σ Distribution Distribution-free estimate 16, 27 Distribution function f(x) 5 Distribution model 4 Confidence range limit 18 Premachining quality 24 W Probability p 5 Probability density function f(x) 4 Probability grid 27 Weibull distribution 8 Tooling change / adjustment 24 w-Distribution 17 Z Random influences 3 ``` **Analysis:** - The text is mainly a table of contents from section "Key word" to keywords starting with "Z". - This table of contents is designed to guide readers to specific sections and pages where defined terms or concepts are discussed within the document. - Each keyword is associated with a page number or numbers, indicating where the information can be found. - This structured layout suggests it is part of a manual, guide, or technical document, facilitating ease of navigation for the reader. ### Localization and Attribution: **Image 1:** - This image appears to be a single page, possibly from a larger document, identified at the top as "Page 36". ### Metadata Analysis: - No metadata is available from the image itself to provide further context or technical details about the capture conditions or date. ### Contextual Significance: - Given that the text is a table of contents/page index, it is crucial for navigating the document effectively. - The inclusion of page numbers suggests a well-organized document aimed at technical professionals who require quick access to specific sections. ### Perspective and Composition: **Image 1:** - The image is captured from a straight-on, eye-level perspective, making the text easy to read and uniformly aligned. - The layout is typical for a contents page, likely taken from a technical document or manual, suggesting an organized and methodical composition. ### Color Analysis: - The image is in black and white, which is typical for textual documents to maintain clarity and minimize distractions. - Dominant color: Black text on white background, providing high contrast for optimal readability. ### Diagram and Chart Analysis: - There are no diagrams or charts to analyze in this image. ### Object Detection and Classification: - The image consists purely of text, with no other objects detected. This comprehensive analysis covers all relevant aspects that can be derived from the provided image content. #################### File: Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf Page: 1 Context: # Škoda Auto a.s. ## Směrnice pro sjednocení prvků **Projekt Obnova výrobních zařízení provozu PKG** **Datum vydání:** 28.01.2020 **PSZ/I - Metodika a standardizace** **1 - H - 20 CZ** Tato směrnice neruší platnost dříve vydaných směrnic, norem, požadavků zadání a ITS ŠkodaAuto. Pro komponenty, u kterých je povoleno několik dodavatelů, bude při zadání dodávky zařízení ve vztahu k projektu smluvně stanoven vždy jen jeden dodavatel. Potenciální dodavatelé jsou dodavatelé, kteří uvolnění pro projekt již mají, nebo je předpoklad, že po vykoušení a splnění koncernových standardů uvolnění do projektu mohou ještě dosat. ### Zpracoval: - Martin Janata, PSZ/I/12, tel.: +420 732 294 691 - Milan Výparnický, PKG/4, tel.: +420 732 294 226 ### Schválil: - Aleš Ivanovič, PSZ/I, tel.: +420 730 869 870 - Ing. Ladislav Treml, PKG/4, tel.: +420 732 294 945 - Ing. Roman Taneček, PPK/2, tel.: +420 604 292 729 ### Přehled změn: | Datum | Strana | Poznámky | |------------|------------------|-----------------------| | 28.01.2020 | První vydání | | **Podpisy, razítka** *Stránka 1 z 5* Image Analysis: ### Comprehensive Examination of the Attached Visual Content **Image 1 (Positioned centrally on the page):** --- **1. **Localization and Attribution:** - Single image located centrally on the page. - Numbered as Image 1. **2. **Object Detection and Classification:** - A document with text, tables, and several stamps. - Visible elements include Škoda Auto a.s. logo, text content, signatures, stamps, and a small table at the bottom. **3. **Text Analysis:** - **Header Text:** - “Škoda Auto a.s.” - “Směrnice pro sjednocení prvků” - “Projekt Obnova výrobních zařízení provozu PKG” - “PSZ/1 - Metodika a standardizace” - “Datum vydání: 28.01.2020” - **Main Body Text:** - Describes the guidelines for orders involving multiple suppliers and details regarding supplier selection for the project. - Contact information and responsible persons are provided. - **Table Content:** - A table with columns “Datum,” “Strana,” and “Poznámky.” - Entries include “28.01.2020” under Datum, “První vydání” under Poznámky, and an empty space under Strana. - **Signatures and Stamps:** - Includes names and signatures for approval, as well as various approval stamps indicating different departments and authorities. **6. **Product Analysis:** - No specific products depicted, but the overall document structure resembles official documentation for project guidelines, approvals, and standardizations. **9. **Perspective and Composition:** - Perspective: Direct front-facing view. - Composition: Standard document layout with a header, body text, contact details, signatures, stamps, and a table at the bottom. Elements are arranged logically and clearly for easy comprehension. **10. **Contextual Significance:** - The document seems to be an official guideline for the unification of project elements and standardization methodology at Škoda Auto a.s. - It is likely part of a larger report or collection of guidelines, as indicated by “Stránka 1 z 5” (Page 1 of 5). **11. **Metadata Analysis:** - The capture date is “28.01.2020.” - Contains official signatures and stamps indicating the document is authentic and reviewed by authorized personnel. **13. **Graph Numbers:** - The entry in the table: “28.01.2020” in Datum, and “První vydání” in Poznámky. --- ### Abbreviations and Acronyms Analyzed: - **PSZ/1**: Likely refers to a particular section or department in Škoda Auto. - **PKG**: Another department or section, possibly related to production. - **Telecommunication Numbers**: Provided for contact. --- In summary, this image contains an official Škoda Auto a.s. document detailing some standardization and methodological guidelines. The document is structured with clear headers, tabulated data, and necessary signatures for authentication. It appears to be a formal and critical piece of company documentation with procedural guidelines likely used in project management and supplier interaction at Škoda Auto a.s. #################### File: Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf Page: 2 Context: # Škoda Auto a.s. **Směrnice pro sjednocení prvků** Projekt Obnova výrobních zařízení provozu PKG **Datum vydání:** 28.01.2020 **PSZ/1 - Metodika a standardizace** **1 - h - 20 CZ** ## I. Část: Standardy výrobních zařízení a komponentů Závazné jsou níže uvedené standardy v oblasti výroby agregátů koncernu VW: 1. Lastenhět Mechanik (dále jen KLH Mechanik) 2. Lastenhět Elektrik (dále jen KLH Elektrik) 3. ITS ŠkodaAuto, viz.: - [CZ verze](#) - [DE version](#) | **Poř.** | **Výrobní zařízení/komponenty** | **Uvolnění dodavatelé** | **Potenciální dodavatelé** | **Poznámky** | |----------|------------------------------------------------|---------------------------------|----------------------------|---------------------------------| | 1. | Elektrika | Viz. část elektro, str.3-4 | ITS: 1.11, 5.13 | | 0.1 | Dokumentace elektrika a řídící technika | Eplan P8 ver. 2.2 nebo vyšší | | | | 2. | Mechanika | Festo, SMC | ITS: 1.10 | | 3. | Pneumatika | Norgren | ITS: 1.13 | | 4. | Mazání | SKF Lubrikation | ITS: 1.17 | | 5. | Hydraulika | Bosch Rexroth, Parker | ITS: 1.12 | | 6. | Filtrační technika | Hydac, Mahle, Bosch Rexroth | ITS: 1.12 | | 0.6 | Čerpadla | KSB, Knoll, Grundfos | Viz KLH Mechanik | | 7. | Šroubová technika | Bosch Rexroth | Bosch Rexroth systém BS350 | ## II. Část: Elektrika, řídicí systémy Image Analysis: ### Detailed Analysis of the Attached Visual Content #### 1. **Localization and Attribution:** **Image Position:** The image is taken from a document, likely a PDF, and is positioned as a standalone page. #### 2. **Object Detection and Classification:** - **Objects Detected:** - Company Logo of Škoda Auto. - Text blocks and headings. - Table containing data on manufacturing standards and suppliers. - Hyperlinks (CZ verze, DE version). **Categories:** - Corporate branding (logos, headers) - Text content (document text) - Tabular data (industrial standards and suppliers) #### 3. **Scene and Activity Analysis:** The image appears to be a page from a professional document related to manufacturing standards for a project by Škoda Auto. It focuses on the methods and standardizations of manufacturing processes, specifically for the machinery and electrical components used in production. #### 4. **Text Analysis:** **Text Extracted:** - Document title and date issued: "Škoda Auto a.s., PSZ/1 - Metodika a standardizace, Datum vydání: 28.01.2020." - Section headers: "I. Část: Standardy výrobních zařízení a komponentů" - Important points: 1. Lastenheft Mechanik 2. Lastenheft Elektrik 3. ITS ŠkodaAuto - Table with standards and suppliers, including: - Elektrika, Mechanika, Pneumatika, Hydraulika, Filtrační technika, etc. - Relevant standards, suppliers, and notes. **Significance:** This text outlines the components and standards required for the production processes at Škoda Auto, listing approved suppliers and potential alternative suppliers. The inclusion of hyperlinks suggests available versions of the standards in Czech and German. #### 5. **Diagram and Chart Analysis:** The table presented is an essential tool. It highlights the necessary standards and component suppliers for the project. Key columns include: - **Výrobní zařízení/komponenty:** Types of components or devices involved. - **Uvolnění dodavatele:** Approved suppliers. - **Potenciální dodavatelé:** Potential suppliers. - **Poznámky:** Notes or additional comments. #### 7. **Anomaly Detection:** There are no obvious anomalies in the document. It is structured and formatted logically according to professional standards. #### 8. **Color Analysis:** The dominant colors in the document are black text on a white background, with a distinctive green color used in the table for headers. The green is likely to highlight important sections, drawing attention to the key areas. Yellow is used for highlighting the 'Poznámky' (Notes) column. #### 9. **Perspective and Composition:** The image is a scan or screenshot of a document page, viewed from a straight-on perspective, providing a clear and direct view of the text and table. The composition is balanced, with the logo and headers at the top and the table centered. #### 10. **Contextual Significance:** This page likely forms part of a larger manual or guideline document (as indicated by "Stránka 2 z 5"), which sets the standards for Škoda Auto’s manufacturing processes. The detailed listing of components and suppliers suggests its use as a technical and operational reference. ### **Conclusion:** This image is from a detailed technical document used by Škoda Auto to standardize and outline the necessary manufacturing components and approved suppliers. It forms part of their methodological and standardized approach to production, with a clear and concise table listing essential standards and notes. #################### File: Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf Page: 3 Context: # Škoda Auto a.s. **PSZ/21 - Metodika a standardizace** **Datum vydání:** 28.01.2020 | Poř. | Výrobní zařízení/komponenty | Uvolnění dodavatelé | Potenciální dodavatelé | Poznámky | |------|----------------------------------------------------|-----------------------------------------|------------------------------------------|-------------------------------| | 1 | Řídicí systém SPS(PLC) | Siemens | Siemens Simatic S7 řada 1500 - TIA V14 a vyšší | | | 2 | CNC Řízení | Siemens | Siemens (Sinumeric 840D sl.) | | | 3 | Řídicí systém na bázi PC a panelové PC | Siemens | Systém - Simatic S7 (HW SPS) Profinet | | | 4 | Vizualizace | Siemens WinCC Flexible | WinCC Flexible 2008 | | | 5 | Ovládací panely | Siemens | | | | 6 | Decentrální sběrnice | Profinet | Profibus, IO-link | | | 6.1 | Konektorové pasivní slučovače (snímače,ventily) | Balluff, Murrelektronik | Balluff, IO-link | | | 7 | Decentrální periferie | Siemens | | | | 8 | Robot | ABB | Kuka (Kuka s řízením VRKC 4) | Turck BL67 | | 9 | Elektrické frekvenční pohony - měniče | SEW Eurodrive | Siemens | VW Konzern Freigabe | | 10 | Elektrické servo pohony | Siemens, Bosch Rexroth | Siemens | VW Konzern Freigabe | | 11 | Ovládací prvky - tlačítka, kontroly | Schneider Electric | Schneider Electric | Specifikace Škoda Auto a.s. | | 12 | Dvouručný ovladač | Schneider Electric | Schmersal-Elan | Specifikace Škoda Auto a.s. | | 13 | Elektro skrín | Rittal | Rittal | VW Konzern Freigabe | | 14 | Svrchní skříň | Rittal | Plannenberg | VW Konzern Freigabe | | 15 | Chalzení rozvádzačových skříní (klimatizace) | Rittal | Sick | Specifikace Škoda Auto a.s. | | 16 | Svételení zovránící/scanner | ASO - Contra, Pilz, Schneider Electric | Cognex, Keyence, Balluff | Specifikace Škoda Auto a.s. | | 17 | Čtecí zařízení čárového a DMC kódu | IOSS | Balluff, Turck-Banner | Specifikace Škoda Auto a.s. | | 18 | Identifikační systém a jistič prýky | Schneider Electric | Pepperl+Fuchs, Turck-Banner | Specifikace Škoda Auto a.s. | | 19 | Optický senzor | Sick, IFM Electronic, Balluff | | | Image Analysis: ### Localization and Attribution **Context:** - The image appears to be a document page from Škoda Auto a.s. - The document is titled "PSZ/1 - Metodika a standardizace" and relates to "Projekt Obnova výrobních zařízení provozu PKG". - The document is dated 28.01.2020 and is labeled as "1 - H - 20 CZ". ### Scene and Activity Analysis - The scene shows a structured table detailing manufacturing or industrial equipment/components. - Each row identifies a specific type of equipment along with associated columns indicating different manufacturers, potential suppliers, and notes. ### Text Analysis - **Header and Title:** - "Škoda Auto a.s." - "PSZ/1 - Metodika a standardizace" - "Projekt Obnova výrobních zařízení provozu PKG" - "Datum vydání: 28.01.2020" - "1 - H - 20 CZ" - "Stránka 3 z 5" (Page 3 of 5) - **Table Headers:** - "Poř." (No.) - "Výrobní zařízení/komponenty" (Manufacturing Equipment/Component) - "Uvolnění dodavatele" (Approved Suppliers) - "Potencionální dodavatelé" (Potential Suppliers) - "Poznámky" (Notes) - **Table Contents:** - Enumerates 20 various pieces of manufacturing or control equipment, listing suppliers and notes for each. - Each row lists manufacturers, potential suppliers, and relevant notes. For example: - "Řídicí systémy SPS/PLC" (Control Systems SPS/PLC) - Siemens - Notes: "Siemens Simatic S7 řada 1500 - TIA V14 a výšší". - "CNC Řízení" (CNC Control) - Siemens - Notes: "Siemens (Sinumerik 840D sl.)". ### Color Analysis - The color scheme comprises mainly white, black text, and a light green highlight for certain rows, primarily spanning suppliers and potential suppliers columns. - The use of green highlights certain aspects, enhancing readability and making it easier to differentiate sections. ### Diagram and Chart Analysis - No diagrams or charts are presented in the image. ### Product Analysis - **Types of Equipment Listed:** - Control systems (SPS/PLC, CNC Control) - Visual systems (Siemens WinCC Flexible) - Robots (e.g., ABB) - Electrical drives and controls - Safety and protection equipment - **Main Features:** - Emphasis on systems and controls primarily from Siemens, with alternative manufacturers and models mentioned. - Notes column often specifies versions or features, e.g., "Sistema Simatic S7" or "WinCC Flexible 2008". ### Tables - The table efficiently organizes different types of industrial equipment, providing clear information on approved and potential suppliers along with additional notes. - It is structured in a way that prioritizes quick reference and decision-making facilitated by the notes. ### Perspective and Composition - The image is a direct, high-angle view, providing a clean, readable presentation of the table. - The information is neatly ordered and segmented, making it easy to navigate section by section. ### Contextual Significance - This document appears to be part of a larger document set (page 3 of 5). - The organization and type of information suggest it’s meant for stakeholders involved in the procurement or standardization process within Škoda Auto’s manufacturing operations. ### Anomaly Detection - No anomalies are detectable in this structured document. The design and layout are standard for industrial documentation. ### Summary The image is a well-structured and standardized industrial document from Škoda Auto detailing manufacturing equipment and components. It emphasizes control systems, various types of equipment, their approved and potential suppliers, and related notes. The document uses a clear table format with color highlights to enhance readability and facilitate efficient decision-making in procurement or standardization processes. #################### File: Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf Page: 4 Context: # Škoda Auto a.s. **Směrnice pro sjednocení prvků** **Projekt Obnova výrobních zařízení provozu PKG** **Datum vydán: 28.01.2020** **1 - H - 20 CZ** | Poř. | Výrobní zařízení/komponenty | Uvolněný dodavatelé | Potenciální dodavatelé | Poznámky | |------|----------------------------------------------------|-------------------------------------------|------------------------------------------|--------------------------------------| | 21 | Indukční senzory, polohové spínače a koncové spínače | Balluff, IFM Electronic | Sick | Specifikace Škoda Auto a.s. | | 22 | Svorky a svorkové příslušenství | Phoenix Contact, Wago | Siemens | Specifikace Škoda Auto a.s. | | 23 | Průtokoměry a teploměry | IFM Electronic, Hydac | Parker, Bosch Rexroth | Specifikace Škoda Auto a.s. | | 24 | Instalace senzorů a koncových spínačů | Balluff - Lumberg | Pepperl+Fuchs | Specifikace Škoda Auto a.s. | | | kabely, konektory a příslušenství snímačů | Mur elektronki | | | | 25 | Konektory - těžké a lehké | Harting, Phoenix Contact, Weidmüller | Murrelektronik | | | 26 | Světelná signalizace - majáky a signální světla | Murrelektronik | Siemens | | | 27 | Výsoké bezpečnostní spínače | Schmersal | Balluff | | | 28 | Bezpečnostní spínače - ochranných zařízení, okén, atd. | Pilz, Schmersal | Euchner | | | 29 | Bezpečnostní systém a bezp. moduly | Pilz, Siemens | Schneider Electric | Pilz (PNOZsigma) | | 30 | Mechanické koncové spínače | Balluff, Siemens | Euchner | Specifikace Škoda Auto a.s. | | 31 | Instalční kabely | LAPP Kabel | Hellu kabel | | | 32 | Vysoké flexibilní kabely | LAPP Kabel | Hellu kabel | | | 33 | Přepínací obvody | Hakel | ABB | | | 34 | Kabelové kanály a žlaby | OBO-Betterman, Niedax | Kopos Kolin | | | 35 | Energetické případy kabelové trasy | Murphysit, Brevett | Kableschlepp | | | 36 | Optické snímače | IFM, Keyence | Sick | Specifikace Škoda Auto a.s. | | 37 | Kamejnzové svítilny, údržba | Cognex, Keyence, Sick | Specifikace Škoda Auto a.s. | | 38 | HEIDENHAIN | | | | **Stránka 4 z 5** Image Analysis: **Text Analysis:** 1. **Primary Header:** - Text: "Škoda Auto a.s." - Context: Indicates the branding of the document, relating to Škoda Auto. 2. **Sub-headers:** - Text: "PSZ/1 - Metodika a standardizace" and "Směrnice pro sjednocení prvků Projekt Obnova výrobních zařízení provozu PKG" - Context: Details the methodology and standardization for an element unification project for the renovation of production facilities in PKG. 3. **Date Information:** - Text: "Datum vydání: 28.01.2020" - Context: Shows the issue date of the document, important for version control and relevance. 4. **Column Headers and Table Content:** - Column 1: "Poř." - Item number in the list, providing a sequence. - Column 2: "Výrobní zařízení/komponenty" - Manufacturing equipment/components, listing various technical items. - Column 3: "Uvolnění dodavatelé" - Released suppliers, listing approved suppliers for each item. - Column 4: "Potenciální dodavatelé" - Potential suppliers, listing additional suppliers that could be considered. - Column 5: "Poznámky" - Notes, providing additional information or specifications for each item. 5. **Rows from 21 to 38:** - The table includes specific components such as "Indukční senzory, polohové spínače a koncové spínače" (Inductive sensors, position switches, and limit switches). - Indicates approved suppliers like "Balluff, IFM Electronic" and potential suppliers like "Sick." - Notes specify adherence to "Specificace Škoda Auto a.s." for many items, ensuring they meet Škoda's standards. **Structure and Layout Analysis:** 1. **Document Layout:** - The visual content is organized as a structured table spanning rows 21 to 38, with clear column headers and slight coloring for rows to enhance readability. 2. **Branding and Design:** - Contains the Škoda logo, reinforcing the brand. - Consistent use of fonts and colors within the table for professional appearance. **Table Analysis:** 1. **Contents Overview:** - Lists various industrial components and equipment essential for manufacturing. - Specifies suppliers both currently approved ("Uvolnění dodavatelé") and potential options ("Potenciální dodavatelé"). 2. **Detailed Data:** - Each row provides comprehensive details about a specific component, emphasizing compatibility and standards specific to Škoda Auto. - Notes offer insightful commentary enabling quick understanding of compliance requirements. **Anomaly Detection:** - **Uniformity and Structure:** - No evident anomalies; the table follows a consistent structure and presents data clearly. **Color Analysis:** - **Dominant Colors:** - Predominantly white background with black text for readability. - Light yellow and gray shades highlight alternate rows, aiding in differentiating between lines. **Conclusion:** The provided visual content is a well-organized table from Škoda Auto detailing component suppliers and specifications. It primarily serves as a reference for standardizing equipment and components in their manufacturing processes. #################### File: Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf Page: 5 Context: # Škoda Auto a.s. **Směrnice pro sjednocení prvků** **Projekt Obnova výrobních zařízení provozu PKG** **Datum vydání:** 28.01.2020 | PSZ/1 - Metodika a standardizace | 1 - H - 20 CZ | |-----------------------------------|---------------| | 39. Záložní zdroje napájení | Siemens, APC, Murrelektronik | Phoenix Contact | | 40. Tlakové snímače | Rexroth, Parker, IFM | Hydac | | | | Specifikace Škoda Auto a.s. | **Stránka 5 z 5** Image Analysis: ### Localization and Attribution 1. **Localization and Attribution:** - There is only one image located on the page. - This image will be referred to as **Image 1**. ### Object Detection and Classification 2. **Object Detection and Classification:** - The image contains a table embedded within a document. - Key features include text rows, columns, logos, and boxed sections. ### Text Analysis 4. **Text Analysis:** - **Title:** "Škoda Auto a.s." - **Sub-Title:** "PSZ/1 - Metodika a standardizace" - **Additional Text:** - "Směrnice pro sjednocení prvků" - "Projekt Obnova výrobních zařízení provozu PKG" - **Date:** "Datum vydání: 28.01.2020" - **Table Content:** - **Header:** "1 - H - 20 CZ" - **Row 1:** - Column 1: "39. Záložní zdroje napájení" - Column 2: "Siemens, APC, Murrelektronik" - Column 3: "Phoenix Contact" - **Row 2:** - Column 1: "40. Tlakové snímače" - Column 2: "Rexroth, Parker, IFM" - Column 3: "Hydac" - **Additional Note:** "Specifikace Škoda Auto a.s." ### Color and Composition Analysis 8. **Color Analysis:** - The dominant colors are white and black with teal (a shade of green) used in the logo and the header. - The simplicity of the color scheme lends itself to a clean and professional look, suitable for official corporate documentation. 9. **Perspective and Composition:** - The image is a head-on view of the document, captured from a standard 'document scan' perspective. - The composition is structured with clear horizontal and vertical delineations defining the sections and rows of the table. ### Contextual Significance 10. **Contextual Significance:** - This document appears to be a technical specification or directive for standardized procedures and components related to Škoda Auto a.s. - It suggests a focus on unifying parts and procedures within the company’s operations, likely aimed at consistency and efficiency in production. ### Tables 13. **Tables:** - The table outlines specific components and their respective suppliers for two different categories: - **Row 1 (Záložní zdroje napájení):** Siemens, APC, Murrelektronik with Phoenix Contact as an additional note. - **Row 2 (Tlakové snímače):** Rexroth, Parker, IFM with Hydac as an additional note. ### Key Insights - The document is likely a page out of a technical or procedural manual from Škoda Auto a.s. focused on guiding the standardization of various components used within their operations. The table lists essential components and their recommended suppliers, providing specific information crucial for maintaining uniformity in production. The detailed breakdown into categories and specific supplier lists indicates a well-organized approach to procurement and standardization. This analysis covers the requested aspects: localization, object detection, text analysis, color analysis, perspective and composition, contextual significance, and the tables provided in the document. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE%281%29.pdf Page: 2 Context: # Škoda Auto a.s. **Richtlinie für die Vereinheitlichung von Elementen** **Projekt Erneuerung der Produktionsanlagen im Bereich PKG** **Ausgabedatum: 28.01.2020** **PSZ/1 - Methodik und Standardisierung** ## I. Teil: Standards für Produktionsanlagen und Komponenten Die untenstehenden Standards für den Bereich der Aggregaterfertigung im VW-Konzern sind verbindlich: 1. Lastenheft Mechanik (im Weiteren KLH Mechanik) 2. Lastenheft Elektrik (im Weiteren KLH Elektrik) 3. ITS ŠkodaAuto, viz.: [CZ version](#) | [DE version](#) | Nr. | Produktionsanlagen/Komponenten | Freigegebene Lieferanten | Potentielle Lieferanten | Anmerkungen | |-----|----------------------------------|-------------------------------------|-------------------------------------|------------------------------------| | 1 | Elektrik, Steuerungstechnik | s. Teile Elektro, S. 3-4 | ITS: 1.11, 5.13 | | 0.1 | Dokumentation Elektrik und Steuerungstechnik | Eplan P8 ver. 2.2 oder höher | | | | 2 | Mechanik | Festo, SMC | Norgren | ITS: 1.10 | | 3 | Pneumatik | | | ITS: 1.13 | | 4 | Schmieren | SKF Lubrikation | | ITS: 1.17 | | 5 | Hydraulik | Bosch Rexroth, Parker | | ITS: 1.12 | | 6 | Filtertechnik | Hydac, Mahle, Bosch Rexroth | | ITS: 1.12 | | 0.6 | Pumpen | KSB, Knoll, Grundfos | Viz KLH Mechanik | | | 7 | Schraubtechnik | Bosch Rexroth | | Bosch Rexroth system BS350 | ## II. Teil: Elektrik, Steuerungssysteme Seite 2 von 4 Image Analysis: ### Localization and Attribution: - **Image Position**: Single image on the page. - **Image Number**: Image 1. ### Text Analysis: - **Header Text**: "Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG." - **Translation**: "Guideline for the Standardization of Elements Project Renewal of Production Plants in the PKG Area." - **Issued Date**: "Ausgabedatum: 28.01.2020" - **Translation**: "Issue Date: 28.01.2020" - **Publisher**: "Škoda Auto a.s. PSZ/1 - Methodik und Standardisierung" - **Translation**: "Škoda Auto a.s. PSZ/1 - Methodology and Standardization" - **Title**: "Standards für Produktionsanlagen und Komponenten" - **Translation**: "Standards for Production Plants and Components." #### Section I: - **Main Title**: "Die untenstehenden Standards für den Bereich der Aggregatfertigung im VW-Konzern sind verbindlich:" - **Translation**: "The following standards for the area of aggregate production in the VW Group are binding:" - **Subsections**: 1. "Lastenheft Mechanik (im Weiteren KLH Mechanik)" - "Mechanical Specifications (hereinafter KLH Mechanik)" 2. "Lastenheft Elektrik (im Weiteren KLH Elektrik)" - "Electrical Specifications (hereinafter KLH Elektrik)" 3. "ITS ŠkodaAuto, viz.:" - "ITS ŠkodaAuto, namely:" - Links: "CZ version" and "DE version" #### Table: - **Table Content**: - **Headers**: - **Columns**: Nr., Produktionsanlagen/Komponenten (Production Plants/Components), Freigegebene Lieferanten (Approved Suppliers), Potentielle Lieferanten (Potential Suppliers), Anmerkungen (Remarks). - **Table Data**: - **Rows**: 1. Elektrik, Steuerungstechnik - **Freigegebene Lieferanten**: s. Teile Elektro, S. 3-4 - **Anmerkungen**: ITS: 1.11, 5.13 2. Dokumentation Elektrik und Steuerungstechnik - **Freigegebene Lieferanten**: Eplan P8 ver. 2.2 oder höher - **Anmerkungen**: ITS: 1.10 3. Mechanik - **Freigegebene Lieferanten**: Festo, SMC - **Potentielle Lieferanten**: Norgren - **Anmerkungen**: ITS: 1.13 4. Pneumatik - **Freigegebene Lieferanten**: SKF Lubrikation - **Anmerkungen**: ITS: 1.17 5. Hydraulik - **Freigegebene Lieferanten**: Bosch Rexroth, Parker - **Anmerkungen**: ITS: 1.12 6. Filtertechnik - **Freigegebene Lieferanten**: Hydac, Mahle, Bosch Rexroth - **Anmerkungen**: ITS: 1.12 7. Pumpen - **Freigegebene Lieferanten**: KSB, Knoll, Grundfos - **Anmerkungen**: Viz KLH Mechanik 8. Schraubtechnik - **Freigegebene Lieferanten**: Bosch Rexroth - **Potentielle Lieferanten**: Bosch Rexroth system BS350 #### Footer: - **Section II Title**: "II. Teil: Elektrik, Steuerungssysteme" - **Translation**: "Part II: Electrical, Control Systems." - **Page Number**: "Seite 2 von 4" - **Translation**: "Page 2 of 4." ### Object Detection and Classification: - **Document Type**: This is a technical document outlining standards for production plants and components. - **Logo**: The Škoda logo is present in the top-right corner of the document. ### Scene and Activity Analysis: - **Activity**: The document is a guideline for the standardization of elements in the production plants of Škoda Auto, detailing approved suppliers, potential suppliers, and relevant remarks for various components and systems. ### Color Analysis: - **Color Composition**: - Dominant colors are white (background) and black (text). - The Škoda logo is green. - The table headers are shaded in green. ### Perspective and Composition: - **Perspective**: The document seems to be a scanned image of a printed page, taken from a top-down perspective. - **Composition**: The text is organized in a standard document layout with headers, body text, and tables for clear and easy reading. ### Contextual Significance: - **Significance**: - The document provides important standards and guidelines necessary for ensuring consistency and quality in the production processes within the VW Group, specifically for Škoda Auto. ### Metadata Analysis: - **Available Metadata**: Issued date, authoring body, document type, and page number. - **Contributing Information**: Helps in understanding the document's official nature, issuance context, and page indexing for reference. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE%281%29.pdf Page: 3 Context: # Škoda Auto a.s. Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG Ausgabedatum: 28.01.2020 ## PSZ/1 - Methodik und Standardisierung 1 - H - 20 DE | Nr. | Produktionsanlagen/Komponenten | Lieferantenfreigabe | Potentielle Lieferanten | Anmerkungen | |-----|-------------------------------------------|--------------------------|-------------------------------|-----------------------------------| | 1 | Steuerungssysteme SPS(PLC) | Siemens | Siemens Simatic S7 Baureihe | 1500 - TIA V14 und höher | | 2 | NC - Steuerung | Siemens | Siemens (Sinumerik 840D sl.) | | | 3 | PC- und Panel-PC-basierte Steuerungs- | Siemens | System - Simatic S7 (HW SPS) | Profinet | | 4 | Visualisierung | Siemens WinCC Flexible | WinCC Flexible 2008 | | | 5 | Steuerungspanels | Siemens | | | | 6 | Dezentrale Sammlung | Profinet | Profibus, IO-link | | | 6.1 | Passiver Stecker-Injektoren (Sensoren, Ventile) | Balluff, Murrelektronik | | IO-link | | 7 | Zentraler Peripherie | Siemens | ABB | Kuka (K istin VKR 4) | | 8 | Roboter | ABB | | | | 9 | Elektrische Frequenzantriebe – Umrichter | SEW Eurodrive | Siemens | VW Konzern Freigabe | | 10 | Elektrische Servo-Antriebe | Siemens, Bosch Rexroth | Siemens | Spezifikation Škoda Auto a.s. | | 11 | Steuerungselemente – Tasten, Kontrollleuchte | Schneider Electric | Siemens | Spezifikation Škoda Auto a.s. | | 12 | Zweihändige Bedienung | Schneider Electric | Schmersal-Eilan | Spezifikation Škoda Auto a.s. | | 13 | Elektroschränke (Verteiler) | Rittal | VW Konzern Freigabe | | | 14 | Klemmenkästen | Rittal | VW Konzern Freigabe | | | 15 | Kühlung Verteilerstraße (Klimanalage) | Sick | Spezifikation Škoda Auto a.s. | | 16 | Lichtschranken / Vorhänge / Scanner | ASO - Contra, Pilz, Schneider Electric | | Spezifikation Škoda Auto a.s. | | 17 | DMC- und Strichcode-Lesegerät | IOSS | Cognex, Keyence, Balluff | Spezifikation Škoda Auto a.s. | | 18 | Erkennungssysteme | Balluff, Turck-Banner | Siemens | Spezifikation Škoda Auto a.s. | | 19 | Schalt- und Sicherungselemente | Siemens, Murrelektronik | Schneider Electric | Spezifikation Škoda Auto a.s. | | 20 | Optische Sensoren | Sick, IFM Electronic, Balluff | | Spezifikation Škoda Auto a.s. | **Seite 3 von 4** Image Analysis: ### Image Analysis --- #### 1. **Image Localization and Attribution** - **Image Number**: Image 1 - **Location**: The image occupies the entire page. #### 4. **Text Analysis** - **Detected Text**: - **Headers and Titles**: - "Škoda Auto a.s." - "Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG" - "Ausgabedatum: 28.01.2020" - "PSZ/1 - Methodik und Standardisierung" - "1 - H - 20 DE" - **Table Contents**: - **Header Row**: - "Nr." - "Produktionsanlagen/Komponenten" - "Lieferantenfreigabe" - "Potentielle Lieferanten" - "Anmerkungen" - **Rows 1-20**: Contains various production components, their suppliers, potential suppliers, and comments/notes about each component. - **Text Analysis**: - The text appears to be a part of a standardization document detailing approved and potential suppliers for different production components used by Škoda Auto a.s. - **Table Headers** are used to categorize and systematically present the information for easy reference. - **Column Headers**: - "Nr.": Item number. - "Produktionsanlagen/Komponenten": Production systems/components. - "Lieferantenfreigabe": Approved supplier. - "Potentielle Lieferanten": Potential suppliers. - "Anmerkungen": Comments/notes. - **Significance**: - This table is likely part of an internal audit or standardization guideline to ensure consistency in the supplier selection process. - The issue date "28.01.2020" suggests the date of the document’s release, which may indicate when the information was verified or updated. #### 12. **Tables** - **Table Content Detail**: - The table lists 20 items, each representing a specific component or production system used by Škoda Auto a.s. - **nr** ranges from 1 to 20, providing a serial order for components. - **Produktionsanlagen/Komponenten** includes items like "Steuerungssysteme SPS/PLC" and "NC - Steuerungen". - **Lieferantenfreigabe** usually indicates the primary supplier (most entries list "Siemens"). - **Potentielle Lieferanten** presents alternative suppliers. - **Anmerkungen** column provides additional details about compatibility, standards, specifications, etc. #### 13. **Graph Numbers** - **Data Points for Each Row**: - Example for Row 1: - Nr: 1 - Produktionsanlagen/Komponenten: Steuerungssysteme SPS/PLC - Lieferantenfreigabe: Siemens - Potentielle Lieferanten: (Blank) - Anmerkungen: Siemens Simatic S7 Baureihe 1500 - TIA V14 und höher - Full list omissible for brevity but follows a similar structure. #### 9. **Perspective and Composition** - **Perspective**: - The information is presented in a straightforward, top-down view, making it easily readable. - **Composition**: - The image has a balanced layout with the table taking the central focus. - Branding elements such as the Skoda logo and headers are prominent at the top, suggesting the document’s authority and official capacity. --- ### Conclusion The image represents a structured table detailing standardization and supplier information for Škoda Auto a.s.'s production components. This aligns with internal documentation possibly used for auditing or updating supplier compliance. The dominant colors green and white reinforce the brand identity while maintaining clarity and readability. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE%281%29.pdf Page: 4 Context: # Škoda Auto a.s. ## Richtlinie für die Vereinheitlichung von Elementen ### Projekt Erneuerung der Produktionsanlagen im Bereich PKG **Ausgabedatum:** 28.01.2020 **PSZ/1 - Methodik und Standardisierung** **1 - H - 20 DE** | Nr. | Produktionsanlagen/Komponenten | Lieferanteneinfreigabe | Potenzielle Lieferanten | Anmerkungen | |-----|------------------------------------------------------------|-------------------------------|-------------------------------------------|---------------------------------------| | 21 | Induktionssensoren, Positionsschalter und | Balluff, IFM Electronic | Sick | Spezifikation Škoda Auto a.s. | | 22 | Klemme und Klemmenzubehör | Phoenix Contact, Wago | Siemens | Spezifikation Škoda Auto a.s. | | 23 | Durchflussmesser und Thermometer | IFM Electronic, Hydac | Parker, Bosch Rexroth | Spezifikation Škoda Auto a.s. | | 24 | Sensoren- und Endschaltinstallation | Balluff - Lumberg | Pepper+Fuchs | Spezifikation Škoda Auto a.s. | | | Kabel, Stecker und Sensorenzubehör | Mur elektronik | | | | 25 | Stecker – schwer und leicht | Harting, Phoenix Contact, Weidmüller | Murrelektronik | | | 26 | Lichtsignaliserung – Blau­leuchte und | Murrelektronik | Siemens | | | 27 | Nockensicherheits-schalter | Schmersal | Balluff | | | 28 | Sicherheitsschalter an Schutzzäunen, Fenster usw. | Pilz, Schmersal | | Spezifikation Škoda Auto a.s. | | 29 | Sicherheitssysteme und Sicherheitsmodule | Pilz, Siemens | Schneider Electric | Pilz (PNOZsigma), Siemens (S7 3xxF) | | 30 | Mechanisches Ende­schalter | Balluff, Siemens | Euchner | Spezifikation Škoda Auto a.s. | | 31 | Installationskabel | LAPP Kabel | Hellukabel | | | 32 | Hochfrequenzkabel | LAPP Kabel | Hellukabel | | | 33 | Überspannungsschutzelemente | Hakel | ABB | | | 34 | Kabelkanäle und -rinnen | OBO-Bettermann, Niedax | Kopos Kolin | | | 35 | Energieschiene bewegliche Kabelbieten | Murrelektronik | Brevetti | | | 36 | Optische Sensoren | IFM, Keyence | Sick | Spezifikation Škoda Auto a.s. | | 37 | Kamerasysteme, lineare, Winkel | Cognex, Keyence | Sick | | | 38 | Wege­messsysteme, linear, Winkels | HEIDENHAIN | Siemens, APC, Murrelektronik | Phoenix Contact | | 40 | Drucksensoren | Rexroth, Parker, IFM | Hydac | | Seite 4 von 4 Image Analysis: ### Localization and Attribution - **Image Number:** 1. - **Location:** The single image occupies the entire page. ### Text Analysis **Text Detected:** - **Title:** "Škoda Auto a.s." - **Subheading:** "Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG" - **Date:** "Ausgabedatum: 28.01.2020" - **Section:** "PSZ/1 - Methodik und Standardisierung" - **Document Number:** "1 - H - 20 DE" - **Table Header Columns:** - "Nr." - "Produktionsanlagen/Komponenten" - "Lieferantenfreigabe" - "Potentielle Lieferanten" - "Anmerkungen" - **Numbered Entries:** 21 to 40. **Content Analysis:** The document appears to be a standardized guideline for Škoda Auto a.s., relating to the unification of elements in the project for renewing production facilities in the PKG area. The table organizes specific components and systems, listing approved suppliers (Lieferantenfreigabe), potential suppliers (Potentielle Lieferanten), and specific notes or remarks (Anmerkungen). ### Table Analysis **Table Content Description:** - **Table Rows:** The table consists of 20 rows, each representing a different production system or component, numbered from 21 to 40. - **Columns:** - **Nr.:** Number identifier for each row. - **Produktionsanlagen/Komponenten:** Identifies the industrial equipment or component needed. - **Lieferantenfreigabe:** Lists the approved suppliers for each component. - **Potentielle Lieferanten:** Lists potential future suppliers. - **Anmerkungen:** Includes notes or specifications relevant to each component. ### Color Analysis - **Dominant Colors:** - **Green:** Used for highlighting the header row (Nr. 21 column header, and rest of the header row). - **Yellow:** Used for the sub-headers (Lieferantenfreigabe, Potentielle Lieferanten, and Anmerkungen). - **White:** Main background of the table cells. - **Impact on Perception:** The green and yellow highlights make the table more navigable, drawing attention to the different categories of content. ### Perspective and Composition - **Perspective:** The image is taken from a straight-ahead view, ensuring readability and clarity. - **Composition:** The document is neatly structured with a centered table taking the majority of space. Text blocks above and below the table provide context and additional information. ### Contextual Significance - **Document Purpose:** The document’s purpose is to provide a standardized framework for updating and maintaining production systems and elements. - **Contribution to Overall Message:** The table aids in clear communication regarding approved and potential suppliers, ensuring that project stakeholders are aligned on procurement and specification details. ### Metadata Analysis - **Date:** The metadata provides the publication date of the document as 28.01.2020, which is crucial for understanding the timeframe of the guidelines. - **Publisher/Issuer:** Škoda Auto a.s., situating the document within the automotive manufacturing industry. ### Gesamtprozesse (Overall Processes) and Interpretation - **Processes Described:** - The table highlights elements required for production system renewal, traversing various steps from selecting suppliers to ensuring compliance with the specified standards. - **Significance:** Ensuring streamlined, efficient, and standardized processes for renewing production systems, ultimately contributing to operational efficiency and quality control in manufacturing. ### Tables Structured Data Points - **Entries:** - Row 21: Induktionssensoren, Positionsschalter und Lichtschranken. - Row 22: Klemme und Klemmenzubehör. - Row 23: Durchflussmesser und Thermometer. - Row 24: Sensoren- und Endschalterinstallation, Kabel, Stecker und Sensorenzubehör. - Row 25: Stecker - schwer und leicht. - Row 26: Lichtsignalisierung - Baulichter und Signalleuchten. - Row 27: Nockensicherheitsschalter. - Row 28: Sicherheitsschalter an Schutztüren, Fenstern usw. - Row 29: Sicherheitssystem und Sicherheitsmodule. - Row 30: Mechanische Endschalter. - Row 31: Installationskabel. - Row 32: Hochflexible Kabel. - Row 33: Überspannungsschutzelemente. - Row 34: Kabelkanäle und -rinnen. - Row 35: Energiebwegliche Kabelketten. - Row 36: Optische Sensoren. - Row 37: Kamerasysteme. - Row 38: Wegmesssysteme, linear, Winkel. - Row 39: Reserveeinspeisungsquellen. - Row 40: Drucksensoren. This comprehensive analysis provides a detailed look at the structure, content, and significance of the presented document. #################### File: Anfrage%20Mail.pdf Page: 1 Context: # Haas, Ulrich **Von:** Haug, Ralf **Gesendet:** Freitag, 13. September 2024 14:46 **An:** Haas, Ulrich **Cc:** Ruoff, Andreas; Kuck, Winfried; Haas, Sonja **Betreff:** Skoda MB SSP MGH und GGH Hallo Herr Haß, Wie gestern besprochen, anbei vorab unsere Anfrage Skoda MB SSP MGH und GGH: - Angebotspräsentation MAG MGH und GGH - Lastenheft Skoda MGH und GGH - Layout - Lastenheft Automation MAG - folgt [Link zum Dokument](https://netfiles.de/8f8adb200fa835316823b5850a55a7b7beef48d7b34e840feca03b49f6d;K319ImMY) Die besprochenen Punkte: - Traceability/Anbindung an Kundenrechner - Mobile Wartungsbühne mit/ohne elektr. Absicherung Versuchen wir mit dem Kunden zu klären. Freundlich grüßt / Best regards, Ralf Haug Projektleiter Verkauf Project Manager Auxiliary Equipment --- FFG Europe & Americas MAG IAS GmbH Salacher Straße 93 73034 Eislingen Germany tel: +49 71 61 805-1281 mobil: +49 1515 1676628 ralf.haug@mag-ias.com [www.mag-ias.com](http://www.mag-ias.com) Follow us on: [Instagram](https://www.instagram.com) | [LinkedIn](https://www.linkedin.com) | [YouTube](https://www.youtube.com) --- MAG IAS GmbH, Salacher Straße 93, DE-73034 Eislingen/Filis Sitz der Gesellschaft / Registered Seat: Eislingen/Filis Registergericht / Registration Court: AG Ulm HRB 720 186 Geschäftsführung / Managing Directors: Dr. Sebastian Schönning, Bin Sun --- ### Show **Summer 2024** 6–10 June | Coimbatore, India 22–26 July | Farnborough, UK 8 August | Sterling Heights, USA 10–14 September | Stuttgart, Germany [www.ffg-qa.com](http://www.ffg-qa.com) Image Analysis: ## Analysis of the Attached Visual Content ### 1. Localization and Attribution - **Image 1**: The main email content on the page, including the email header, introduction, and body text. - **Image 2**: The section with contact information, company logos, and social media links. - **Image 3**: The footer section, including visit invitations and legal information of the company. ### 2. Text Analysis #### **Image 1** - **Text Detected**: - **Header**: "Haass, Ulrich", "Von: Haup Ralf" - **Main Body**: ``` Hallo Herr Haas, Wie gestern besprochen anbei vorau unsere Anfrage Skoda MB SSP MGH und GGH - Anfragepräsentation MAG MGH und GGH - Lastenheft Skoda MGH und GGH - Layout - Lastenheft Automation MAG - folgt Die besprochenen Punkte: - Traceability/Anbindung an Kundelrecher - Mobile Wartungsbuhne mit/ohne elektr. Absicherung Versuchen wir mit dem Kunden zu klaren Freundlich grusst / Best regards, Ralf Haug Projektleiter Zukauf Project Manager Auxiliary Equipment ``` **Significance**: The email details a business communication, likely concerning project proposals and specific requirements for Skoda. It includes a presentation and various project deliverables such as a "lastenheft" (requirements specification). #### **Image 2** - **Text Detected**: ``` FFG Europe & Americas MAG IAS GmbH Salacher Straße 93 73054 Eislingen Germany Tel: +49 71 61 805-1281 Mobil: +49 1515 1676628 Follow us on Instagram, Linkedin, Youtube ``` **Significance**: This section provides essential contact details and links to social media channels for further engagement or inquiries. #### **Image 3** - **Text Detected**: ``` Show Summer 2024 Visit us 6-10 June Coimbatore, India 22-26 July Farnborough, UK 8 August Sterling Heights, USA 10-14 September Stuttgart, Germany MAG IAS GmbH, Salacher Straße 93, DE-73054 Eislingen/Fils Sitz der Gesellschaft / Registered Seat: Eislingen/Fils Registergericht / Registration Court: AG Ulm HRB 720 186 Geschäftsführung / Managing Directors: Dr. Sebastian Schöning, Bin Sun ``` **Significance**: This section outlines upcoming events and exhibitions where the company will be present, thus encouraging networking and showcasing opportunities. ### 3. Object Detection and Classification #### **Image 1**: - **Objects Found**: - Email header and body text. - Dates and paragraphs detailing a business proposal and the discussed points. #### **Image 2**: - **Objects Found**: - Company logos and icons for social media platforms. - Contact details (phone number, emails). #### **Image 3**: - **Objects Found**: - Invitation for various events with dates and locations. - Legal information about the company structure. ### 4. Scene and Activity Analysis - **Scene**: The composite scene over these three images represents a professional email and information document targeting business partners or potential customers. - **Activity**: The main activity is the transmission of important business-related information including project specifications, contact details, and event invitations. ### 5. Color Analysis - **Dominant Colors**: - **Email Content (Image 1)**: Primarily black and white, suggesting a focus on readability and professionalism. - **Contact Information Section (Image 2)**: Includes colors from various logos (blue, red, green), indicating brand identification. - **Event Invitation Section (Image 3)**: Uses a combination of green background and white text, making it inviting and attractive. ### 6. Perspective and Composition - **Perspective**: All images are presented in a straight-on view, typical for textual communication and document presentation. - **Composition**: - **Image 1**: Structured as an email with header, body text, and bullet points for clarity. - **Image 2**: Centrally aligned, providing clear and easy access to contact details. - **Image 3**: Designed with a promotional focus, highlighting events and legal information. ### 7. Contextual Significance - The entire visual content aims to convey professional communication regarding a project between MAG IAS GmbH and Skoda. It highlights the importance of networking, project specifications, and following up on discussed points. The inclusion of company contact details and event information further establishes credibility and invites further interaction. By addressing these key aspects, the analysis offers a detailed comprehension of the visual content and its significance. #################### File: Anfrage%20Mail.pdf Page: 2 Context: # Aufsichtsrat / Supervisory Board **Dr. Hans Ulrich Golz (Chairman)** --- Diese E-Mail enthält vertrauliche oder rechtlich geschützte Informationen. Wenn Sie nicht der beabsichtigte Empfänger sind, informieren Sie bitte sofort den Absender und löschen Sie diese E-Mail. Das unbefugte Kopieren dieser E-Mail oder die unbefugte Weitergabe der erhaltenen Informationen ist nicht gestattet. --- The information contained in this message is confidential or protected by law. If you are not the intended recipient, please contact the sender and delete this message. Any unauthorised copying of this message or unauthorised distribution of the information contained herein is prohibited. #################### File: MGH%20Anlage%2014.pdf Page: 1 Context: # Clamping MGH ## OP10 ### General Overview - New geometry that was added by Škoda tool shop - ![Fixed Part Rest](images/fixed_part_rest.png) 🔴 - ![Clamp](images/clamp.png) ➡️ - ![Location Pins](images/location_pins.png) ⚪ - ![2- and 3-Jaw Chucks](images/chucks.png) ⬇️ ### Visual Representation - **Top View** ![Top View](images/top_view.png) - **Side View** ![Side View](images/side_view.png) - **Bottom View** ![Bottom View](images/bottom_view.png) ### Safety Precautions - Always ensure that clamping mechanisms are securely fastened and functional. - Regularly inspect the integrity of the new geometries. ### Additional Notes - Reference document: - **S3 | 05.08.2024 | Clamping MGH | PPK-E | Georgy Komarov** --- _Internal document_ Image Analysis: ### 1. Localization and Attribution: - **Image Structure**: The image contains multiple sections merged into one; hence, it will be analyzed as a single comprehensive image. ### 2. Object Detection and Classification: - **Objects**: - Components of mechanical parts in grey. - Green highlighted areas indicating new geometry added by Skoda tool shop. - Red symbols indicating various fixtures like fixed part rest, clamp, location pins, and chucks. ### 3. Scene and Activity Analysis: - **Scene Description**: - Mechanical parts are shown in three detailed sections with indicators for assembly processes. - **Activities**: - The diagram is illustrating the clamping setup for a part labeled MGH, particularly in operation step OP10, involving multiple mechanical sub-steps. ### 4. Text Analysis: - **Detected Text**: - Titles and Labels: - "Clamping MGH" - "OP10" - "New geometry that was added by Skoda tool shop" - Symbols like "fixed part rest", "clamp", "location pins", "2- and 3-jaw chucks" - Footer Information: - "S3 | 05.08.2024 | Clamping MGH | PPK-E | Georgy Komarov" - "INTERNAL" - "SKODA" - **Text Significance**: - The text provides instructions and details about the clamping procedure, emphasizing the involvement of the Skoda tool shop and the specific operation steps (OP10). ### 5. Diagram and Chart Analysis: - **Diagrams**: - The visual contains mechanical diagrams identifying specific areas relevant to the clamping process. Green areas signify new additions, while red symbols denote various mechanical fixtures. ### 7. Anomaly Detection: - **Anomalies**: - No noticeable anomalies specific to the technical context. ### 8. Color Analysis: - **Color Composition**: - Predominantly grey-scale mechanical parts. - Green highlights indicating new geometric additions. - Red symbols and arrows used for guiding fixtures and processes. - **Impact on Perception**: - The grayscale provides clarity on mechanical part details, while green and red colors highlight essential modifications and operable components, respectively. ### 9. Perspective and Composition: - **Perspective**: - Top and front views are presented for detailed analysis of mechanical parts. - **Composition**: - Central mechanical parts with annotations and color-coded guides placed around the parts to highlight specific components and processes. ### 12. Graph and Trend Analysis: - **Trends**: - The diagram focuses on showcasing areas modified by new geometry and where specific fixtures such as clamps and chucks should be placed. ### 13. Graph Numbers: - **Data Points**: - Not applicable as the image does not contain numerical graph data points. ### Additional Aspects: - **Ablaufprozesse (Process Flows)**: - The image outlines a detailed process flow showing how parts should be positioned and clamped during the OP10 operation step. - **Prozessbeschreibungen (Process Descriptions)**: - Detailed clamping and assembly process described through annotated symbols and highlights. - **Typen Bezeichnung (Type Designations)**: - Fixed part rest, clamp, location pins, and 2- and 3-jaw chucks are identified as specific types of fixtures used in the process. ### Contextual Significance: - **Overall Document Significance**: - The image contributes detailed visual guidance crucial for assembling mechanical parts, likely for internal use within SKODA, as indicated by the "INTERNAL" label at the bottom. ### Summary: - The image provides a thorough guide for a clamping process (OP10) of a mechanical part (MGH). - Annotations include color-coded highlights and symbols to indicate new geometry added and the types of fixtures used. - Text and diagrams collectively help in understanding the detailed assembly procedure in a manufacturing or tool shop context for SKODA. #################### File: MGH%20Anlage%2014.pdf Page: 2 Context: # Clamping MGH ## OP20 and Following One of four part rests can be movable. ### Components - **Fixed part rest** - ![Fixed Part Rest Icon](fixed-part-rest-icon.png) - **Clamp** - ![Clamp Icon](clamp-icon.png) - **Location Pins** - ![Location Pins Icon](location-pins-icon.png) - **2- and 3-Jaw Chucks** - ![Jaw Chuck Icon](jaw-chuck-icon.png) ### New Geometry - New geometry that was added by Skoda tool shop (indicated in green). Image Analysis: ### Analysis of Visual Content #### 1. Localization and Attribution - **Image 1:** The image on the left. - **Image 2:** The image on the right. #### 2. Object Detection and Classification - **Image 1:** - Detected Objects: Fixed part rests, clamps, location pins, and new geometry added by the Skoda tool shop. - Key Features: The fixed part rests are marked with triangular symbols, clamps with downward arrows, location pins with target-like symbols, and new geometry sections highlighted in green. - **Image 2:** - Detected Objects: Fixed part rests, clamps, location pins, 2- and 3-jaw chucks, and new geometry added by the Skoda tool shop. - Key Features: The symbols used to identify different parts are consistent with Image 1. Additional symbols indicate 2- and 3-jaw chucks with upward arrows and circles. #### 3. Scene and Activity Analysis - **Image 1 and Image 2:** - Scene: Both images showcase a mechanical part, likely an engine component, with various annotations indicating locations for clamps, rests, and new geometries. - Activities: The images are likely used for instructional purposes in a manufacturing or machining process, detailing how and where different clamps and fixtures should be applied. #### 4. Text Analysis - **Image 1 and Image 2:** - Detected Text: - "Clamping MGH OP20 and following" - "One of four part rest can be movable" - Symbols indicating fixed part rest, clamp, location pins, and 2- and 3-jaw chucks. - Analysis: The text provides instructions and information about how the component should be clamped during the manufacturing process. The significance lies in guiding operators on the proper use of fixtures and clamps, with flexibility in the usage of one part rest being movable. #### 5. Diagram and Chart Analysis - **Image 1 and Image 2:** - The diagrams illustrate a mechanical component with various annotations regarding part clamping and geometry changes. The visual annotations guide where each clamp, rest, and pin should be placed, supplemented by the color-coded additions in green. #### 6. Product Analysis - **Image 1 and Image 2:** - Products Depicted: Mechanical component, possibly an engine or transmission part. - Main Features: Various resting points, clamping locations, and location pins, with added new geometry sections. - Materials and Colors: Grey-shaded parts indicating the base component and green highlighting new geometry sections. #### 7. Anomaly Detection - No anomalies detected in the context of the technical illustration. All elements seem purposeful and intentional as part of the instructional schematic. #### 8. Color Analysis - **Image 1 and Image 2:** - Dominant Colors: Grey for the main component and green for newly added geometries. - Impact: The color differentiation helps in clearly distinguishing new additions from the existing component structure, enhancing the instructional clarity. #### 9. Perspective and Composition - **Image 1 and Image 2:** - Perspective: Both images are likely technical renders or CAD models showing different angles of the same component. - Composition: The key elements of the diagrams (rests, clamps, pins) are strategically labeled, making it clear for manufacturing purposes. #### 10. Contextual Significance - **Image 1 and Image 2:** - The images serve as part of a technical document detailing the clamping process for a mechanical component. They contribute to the overall theme by providing crucial visual instructions for accurate component handling. ### Additional Aspects: #### Ablaufprozesse (Process Flows) - The diagrams outline the flow of how and where to apply the clamps and rests during the manufacturing process. #### Prozessbeschreibungen (Process Descriptions) - Descriptions involve the methods of clamping and the potential movement of one part rest in the operation. #### Typen Bezeichnung (Type Designations) - The type designations are indicated by symbols for fixed part rests, clamps, location pins, and 2- and 3-jaw chucks. #### Trend and Interpretation - Trends indicate a well-detailed and systematic approach to ensuring precise clamping in the manufacturing process. #### Tables - No tables are present in the provided images. In summary, the attached images are comprehensive technical illustrations meant to guide a precise and systematic clamping process for a mechanical component, with appropriate annotations, detailed text instructions, and clear visual markers to facilitate the manufacturing workflow. #################### File: MGH%20Anlage%2014.pdf Page: 3 Context: # Clamping MGH ## OP20 and Following - **Location Pins** ![location pins](link_to_image) - **2- and 3-Jaw Chucks** ![2- and 3-jaw chucks](link_to_image) - **Fixed Part Rest** ![fixed part rest](link_to_image) - **Clamp** ![clamp](link_to_image) For location orientation, the marked holes with dimension **12H7** will be used. After clamping on the holes, there may be some "optical issues," but dimension **12H7** must be kept. Holes then are used for the positioning of the axle on the assembly line (see description of T, S datums on the drawing – clipping on the next slide). Image Analysis: ### Comprehensive Examination Results #### 1. Localization and Attribution: - **Image 1**: Only one image is present on the page, so labeled as Image 1. #### 2. Object Detection and Classification: - **Image 1**: - **Detected Objects**: - Engine component or machinery part. - Location pins. - 2- and 3-jaw chucks. - Fixed part rests. - Clamps. - **Classification**: - Category: Mechanical Parts and Engine Assembly. - **Key Features**: - Complex mechanical structure with multiple elements for clamping and fixing. #### 3. Scene and Activity Analysis: - **Image 1**: - **Scene Description**: - The image depicts a section of a mechanical part focusing on how it should be clamped for the operational process OP20 and following steps. - **Activities**: - The main focus is on the attachment and orientation of the mechanical part using various clamping and positioning mechanisms. #### 4. Text Analysis: - **Image 1**: - **Detected Text**: - Clamping MGH - OP20 and following - location pins - 2- and 3-jaw chucks - fixed part rest - clamp - For location orientation will be used marked holes with dimension 12H7. After clamping on the holes can stay some "optical issues", but dimension 12H7 must be kept. Holes then are used for the positioning of the axle on the assembly line (see description of T, S datums on the drawing - clipping on the next slide). - SKODA - INTERNAL - **Text Significance**: - Provides instructions and specifications for clamping the mechanical part. - Highlights the dimensions and requirements critical for the assembly process. #### 5. Diagram and Chart Analysis: - **Not Applicable**. #### 6. Product Analysis: - **Image 1**: - **Depicted Products**: - Engine component with multiple clamps and orientation pins. - New geometry added (highlighted in green) by Skoda tool shop. - **Comparison**: - Not applicable, as only one product is depicted. #### 7. Anomaly Detection: - **Not Applicable**. #### 8. Color Analysis: - **Image 1**: - **Color Composition**: - Dominant Colors: Grey (metal part), Red (annotations), Green (new geometry). - **Impact**: - Green highlights the modifications made by the Skoda tool shop. - Red is used to draw attention to key clamping elements. #### 9. Perspective and Composition: - **Image 1**: - **Perspective**: - Side view with some top-down elements of the engine or machinery part. - **Composition**: - The mechanical part is centrally placed with text and annotations around it to explain detailed instructions and specifications. #### 10. Contextual Significance: - **Image 1**: - **Contribution to Document**: - It provides essential information on clamping and positioning a mechanical part for further processing in the production line, which is likely part of an instruction manual or technical document. #### 11. Metadata Analysis: - **Not Applicable**. #### 12. Graph and Trend Analysis: - **Not Applicable**. #### 13. Graph Numbers: - **Not Applicable**. #### Ablaufprozesse (Process Flows): - **Image 1**: - **Depicted Process Flows**: - Clamping process using pins, chucks, and fixed rests. - Ensuring proper orientation with marked holes of dimension 12H7. #### Prozessbeschreibungen (Process Descriptions): - **Image 1**: - Detailed description of clamping and positioning steps for the mechanical part. #### Typen Bezeichnung (Type Designations): - **Image 1**: - **Fixed Locations, Clamps**: Various components for mechanical clamping and positioning. #### Trend and Interpretation: - **Not Applicable**. #### Tables: - **Not Applicable**. #################### File: MGH%20Anlage%2014.pdf Page: 4 Context: # Clamping MGH ## OP20 and following | Index | Description | |-------|------------------------------------------------| | 1 | Anbringeliste Teilnahme Bohrung | | 2 | Rohrflansch Detail Sillflans | | 3 | Gehäuseschraube Routinierung | | 4 | Druckpunktbohrung | | 5 | Öl Dichtungswechsel | | 6 | Beffestigung Rahmeneck | | 7 | Anbringeliste obere Schale | | 8 | Anbringeliste mittlere Schale | | 9 | Außenmutter Zylinderkopf | ### Additional Information - The figures marked as **T** and **S** correspond to specific assembly locations on the component. Image Analysis: **Image Analysis** 1. **Localization and Attribution:** - The image is single and occupies the entire page. - It will be referred to as **Image 1**. 2. **Object Detection and Classification:** - **Object Detected:** An engineering drawing of a mechanical part, likely an automotive component, possibly a gear housing or engine part. - **Classification:** Mechanical/Engineering drawing, highlighting various parts. 3. **Scene and Activity Analysis:** - **Scene Description:** The image depicts an exploded view of a mechanical part with multiple annotations pointing to specific components. - **Activities:** No specific activities are visible as it's a technical drawing. 4. **Text Analysis:** - **Detected Text:** - Title: "Clamping MGH" - Subtitle: "OP20 and following" - Description List (column format with numbers and descriptions): - 1. Rückholfeder Bohrrung - 2. Rollenlager Bolz Stiftaufnahme - 3. Getriebeputzen Drosselklappenaufnahmen - 4. Getriebeputzen Roeachauffnahmen - 5. Öl Rücklauf Getriebeputze - 6. Getriebeputzen Paddelhubung - 7. Achse und Lager Töpfe - 8. Rückhaltfeder Passstift/Führung - 9. Kugellagerbohrung - 10. Kugellager Dichtungsflansch - 11. Druckstift Bohrung - 12. Leerlauf Knopf Lagerbohrung - 13. Drossel Kugellagerbohrung - 14. Ölniveaustand Bolzen - 15. Öl Vettel Aufnahmebrücke - 16. Maximalen Zündblitzlage fest Sitz - **Text Significance:** The text provides detailed descriptions of the components and parts of the mechanical drawing, useful for understanding assembly or maintenance procedures. 5. **Diagram and Chart Analysis:** - **Type of Diagram:** Annotated mechanical drawing - **Components Labeled:** Various parts are labeled with letters and numbers correlating to descriptions in the text box. These include E, F, P, T, S, etc. 6. **Product Analysis:** - **Product Depiction:** The mechanical part likely belongs to an internal component of a vehicle, such as a transmission or engine housing. - **Key Features:** Multiple bolt holes, complex internal pathways for fluids or air, mounting points for bearings or other parts. - **Materials:** Likely metal, typically aluminum or cast iron for such components. 7. **Anomaly Detection:** - **Possible Anomalies:** No apparent anomalies in the technical drawing as it follows standard conventions for mechanical engineering schematics. 8. **Color Analysis:** - **Color Composition:** The image is primarily black and white, typical for technical schematics to ensure clarity. - **Impact:** The monochrome scheme focuses attention on structural details without distraction from colors. 9. **Perspective and Composition:** - **Perspective:** The drawing has a detailed perspective view, showing depth and contours. - **Composition:** The mechanical part is centrally placed with annotations clearly indicating key sections and features on the drawing. 10. **Contextual Significance:** - **Overall Document Context:** Likely part of a technical manual or engineering specifications document, crucial for automotive repair or assembly processes. - **Contribution:** Provides detailed insights into the assembly and components of the mechanical part, essential for technicians or engineers. 11. **Metadata Analysis:** - **Caption Information:** - "S3 | 05.08.2024 | Clamping MGH | PPK-E | Georgy Komarov" - **Significance:** Indicates the version (S3), date (05.08.2024), component type (Clamping MGH), document type (PPK-E), and possibly the creator (Georgy Komarov). 13. **Graph Numbers:** - **Column Breakdown:** - Data rows from 1 to 16, each corresponding to a specific component listed in the text analysis. **Additional Aspects:** - **Ablaufprozesse (Process Flows):** - The text and drawing suggest a sequential clamping or assembly process. - **Prozessbeschreibungen (Process Descriptions):** - Detailed process descriptions are provided in the text beside the numbers, likely for assembly or quality checks. - **Typen Bezeichnung (Type Designations):** - The text provides type designations for various mechanical components such as "Rückholfeder Bohrrung" and "Rollenlager Bolz Stiftaufnahme". - **Tables:** - The text list acts much like a table, matching numbered descriptions to parts on the drawing. Overall, **Image 1** serves as an intricate and detailed guide for understanding and working with a mechanical component, likely aimed at individuals in technical fields such as automotive engineering and maintenance. #################### File: MGH%20Anlage%2014.pdf Page: 5 Context: # Clamping MGH ## Remarks to clamping - Holes on the casting do not have the same axles with final machined holes on the done part. It is also relevant for indexes OP20. - Clamping pads for OP20 need to be milled to be perpendicular to indexes' axles. Image Analysis: ### Localization and Attribution: - **Image 1**: Located on the left side of the page, depicting a CAD model of a component with dimensions highlighted. - **Image 2**: Located below Image 1, showing a section of the same or another component. ### Object Detection and Classification: - **Image 1:** - **Object**: A CAD model of a mechanical component, likely part of a larger assembly, with specific dimensions highlighted in green. - **Features**: The model shows a detailed structure with various protrusions, cavities, and highlighted dimensions of 13.5 and 103.5. - **Image 2:** - **Object**: A smaller section of a mechanical component with one visible hole. - **Features**: The component appears to be a clamping part, with a cyan-colored surface, indicating the area of interest. ### Scene and Activity Analysis: - **Image 1**: - **Scene**: A technical illustration of a mechanical component with dimensions for specific features. - **Activity**: Measurement and precise dimensioning of parts for manufacturing or quality control purposes. - **Image 2**: - **Scene**: A close-up of a component section, likely for detailed analysis or highlighting a critical feature. - **Activity**: Inspection of specific areas of a mechanical part for design or manufacturing adjustments. ### Text Analysis: - **Detected Text**: - Title: "Clamping MGH" - Subtitle: "Remarks to clamping" - Bullet Points: - “Holes on the casting do not have the same axles with final machined holes on the done part. It is also relevant for indexes OP20.” - “Clamping pads for OP20 need to be milled to be perpendicular to indexes' axles.” - Footer Information: - "S3 | 05.08.2024 | Clamping MGH | PPK-E | Georgy Komarov" - "INTERNAL" - **Analysis and Significance**: - The text provides technical notes and remarks related to the clamping (“MGH”) process. - It mentions specific observations such as the misalignment of casting holes with final machined holes and the requirement for milling clamping pads perpendicularly. - These remarks are critical for ensuring the accuracy and precision of the machining and clamping process. ### Diagram and Chart Analysis: - **Image 1**: - **Diagram**: The highlighted dimensions (13.5 and 103.5 mm) in the CAD model serve as a visual guide for machining or inspection. - **Insights**: Highlight specific areas requiring attention for manufacturing or quality checks. ### Product Analysis: - **Products Depicted**: - **Mechanical Components**: Likely part of an automotive or machinery assembly, designed for precision clamping and machining. - **Features**: Detailed CAD models showing specific measurements and structural features for accurate manufacturing. ### Anomaly Detection: - **Possible Anomalies**: - Misalignment of casting holes with final machined holes. - **Impact**: Such anomalies can lead to mechanical issues or failures if not addressed. It stresses the need for precise manufacturing and inspection processes. ### Color Analysis: - **Dominant Colors**: - Green: Highlighting specific dimensions. - Cyan: Highlighting a section in Image 2. - **Impact**: Use of color emphasizes critical features and dimensions, aiding in visual analysis and ensuring focus on important areas. ### Perspective and Composition: - **Perspective**: - **Image 1**: Isometric view providing a clear 3D representation of the component. - **Image 2**: Close-up view for detailed inspection. - **Composition**: - The arrangement facilitates focus on specific technical features, with clear annotations. ### Ablaufsprozesse (Process Flows): - Highlights issues related to the clamping process and necessary steps for milling and adjusting clamping pads for precise alignment. ### Prozessbeschreibungen (Process Descriptions): - Described processes involve identifying and resolving alignment issues in casting and final machining stages, and necessary adjustments to clamping pads. ### Typen Bezeichnung (Type Designations): - **OP20**: Likely refers to a specific operational process or part designation within the manufacturing workflow. #################### File: MGH%20Anlage%2014.pdf Page: 6 Context: # BACK-UP **Document Information:** - **Version:** S3 - **Date:** 06.08.2024 - **Document Type:** Clamping MGH | PPK-E - **Author:** Georgy Komarov **INTERNAL** #################### File: MGH%20Anlage%2014.pdf Page: 7 Context: # Clamping MGH ## Previous clamping points for OP10 ### Clamping surfaces and projections of rest pads | Status | Image | |--------|-------------------------------------| | NOK | ![NOK](image_url_1) | | OK | ![OK](image_url_2) | | NOK | ![NOK](image_url_3) | Note: Replace `image_url_1`, `image_url_2`, and `image_url_3` with the actual URLs of the images. Image Analysis: ### Image Analysis #### 1. Localization and Attribution: - **Image 1**: Positioned on the left side. - **Image 2**: Positioned in the center. - **Image 3**: Positioned on the right side. #### 2. Object Detection and Classification: - **Image 1**: - Detected Object: A section of a mechanical assembly with clamping points. - Key Features: Green clamping surface highlighted with an arrow indicating "Previous." - **Image 2**: - Detected Object: Another section of a mechanical assembly with different clamping points. - Key Features: Green clamping area marked "OK" with the arrow indicating "Previous." - **Image 3**: - Detected Object: Different mechanical assembly area with clamping points. - Key Features: Green clamping surface highlighted as "Previous" with arrow and labeled "NOK." #### 3. Scene and Activity Analysis: - **Image 1**: - Scene: A close-up of a mechanical part showing clamping surfaces. - Main Actor: The clamping surfaces. - Action: Illustration of a previously used clamping method designated as "NOK" (not okay). - **Image 2**: - Scene: Close-up of the same or similar mechanical part with a focus on a different spot. - Main Actor: The clamping surface. - Action: Illustration of a different previously used clamping method designated as "OK." - **Image 3**: - Scene: Close-up on another section of the mechanical part. - Main Actor: Clamping surface. - Action: Illustration of another previously used clamping method designated as "NOK." #### 4. Text Analysis: - **Text Detected**: - "Clamping MGH" - "Previous clamping points for OP10" - "Clamping surfaces and projections of rest pads" - "NOK" (Image 1 and Image 3) - "OK" (Image 2) - "Previous" (inside the images with arrows pointing to specific areas) - "INTERNAL", Date, Image Reference, Author, Company Logo (SKODA) - **Text Significance**: - The text provides titles and labels essential to understanding the context of the images, indicating that these images are used for explaining or comparing different clamping surfaces in a mechanical process. "NOK" signifies non-acceptable clamping points, and "OK" signifies acceptable ones. #### 5. Diagram and Chart Analysis: - No diagrams or charts are present in the images above. #### 6. Product Analysis: - Main Features: Mechanical parts with highlighted clamping surfaces, indicating previous clamping points. - Materials: Likely metallic, typical of automotive or machinery parts. #### 7. Anomaly Detection: - No apparent anomalies are detected in the images as they all show expected close-ups of mechanical parts with highlighted clamping surfaces. #### 8. Color Analysis: - Dominant Colors: - Green: Used to highlight clamping surfaces. - Grey: Background and mechanical components. - Red: Arrows pointing to specific areas. - Impact on Perception: The color scheme effectively directs focus on the clamping points due to the high contrast between the green highlights and the grey mechanical parts. #### 9. Perspective and Composition: - Perspective: Close-up views of mechanical parts with a direct angle focusing on clamping points. - Composition: The clamping surfaces are placed centrally within the frame, highlighted with arrows and text to guide the viewer's focus. #### 10. Contextual Significance: - The images likely form part of a technical document or a presentation addressing clamping methods in a mechanical process, possibly in an automotive setting, as suggested by the SKODA logo. ### Additional Aspects #### Ablaufprozesse (Process Flows): - Depiction of clamping process evaluations and highlighting issues. #### Prozessbeschreibungen (Process Descriptions): - Describes the evaluation of previous clamping points used in the mechanical process and categorizes them into acceptable and non-acceptable clamping methods. #### Typen Bezeichnung (Type Designations): - Categories: "NOK" - non-acceptable areas, "OK" - acceptable area. #### Trend and Interpretation: - The images emphasize a need for reviewing and possibly updating clamping methods to ensure they meet acceptable standards. ### Conclusion The images analyzed provide critical information on the clamping points used in mechanical assemblies. Their clear labeling and color-coding assist in quickly identifying acceptable and non-acceptable methods within a technical context related to the automotive industry. #################### File: MGH%20Anlage%2014.pdf Page: 8 Context: # Clamping MGH ## New clamping points for OP10 ### Clamping surfaces and projections of rest pads | Image | Status | |-------------|--------| | ![Clamping MGH Image 1](path_to_image1) | OK | | ![Clamping MGH Image 2](path_to_image2) | OK | | ![Clamping MGH Image 3](path_to_image3) | OK | **Note:** Replace `path_to_image1`, `path_to_image2`, and `path_to_image3` with the actual image paths. Image Analysis: ### Image Analysis **1. Localization and Attribution:** - **Image Numbering:** - Image 1: First image on the left - Image 2: Middle image - Image 3: First image on the right **2. Object Detection and Classification:** - **Image 1:** - Objects: Car part components, highlighting the clamping points. - Key Features: The clamping points on the car part are highlighted in green with red arrows indicating specific locations. - **Image 2:** - Objects: Similar car part components with additional clamping points. - Key Features: Similar depiction with clamping points highlighted in green and focused areas indicated by red arrows. - **Image 3:** - Objects: Car part components, emphasizing another set of clamping points. - Key Features: The same pattern of highlighting in green and red arrows showing precise points. **3. Scene and Activity Analysis:** - **Overall Scene:** All three images focus on different sections of a car component system, highlighting new clamping points relevant for OP10 (Operation 10). - **Activities:** - Highlighting and verifying new clamping points and rest pad surfaces. - Ensuring the identified points are appropriate for the given operation stage as indicated by “OK.” **4. Text Analysis:** - **Detected Text:** - "Clamping MGH" - "New clamping points for OP10" - "Clamping surfaces and projections of rest pads" - "OK" (under each image) - Additional footer text implying internal use and a specific date and author. - **Text Significance:** - The primary text informs about new clamping points designed for a specific operational code (OP10). - The consistent "OK" under each image suggests verification and approval of the highlighted clamping points. **9. Perspective and Composition:** - **Perspective:** - All images are close-up views, providing detailed insights into particular parts of the car components. - Angled views focusing on non-linear components suggesting a 3-dimensional analysis standard. - **Composition:** - The images are arranged side by side to allow comparison. - Each image has internal highlighting that guides the viewer's attention towards the critical points relevant to the operational process. **10. Contextual Significance:** - The images and text collectively detail a technical update or modification for a car manufacturing/engineering process. - They serve the purpose of demonstrating and verifying new clamping points effectiveness in practical scenarios (Operation 10). **13. Graph Numbers and Additional Aspects:** - **Process Descriptions:** - This is a technical document presenting process improvements, specifically adding new clamping points for operational efficiency. - **Type Designations:** - OP10 refers to a specific task or operation in the assembly or manufacturing process. ### Summary In the analyzed visuals, we focused on the technical aspects of incorporating new clamping points in car components for a designated operation (OP10). The consistent use of highlighting and arrow indicators draws attention towards key functional points. The overall structure, including perspectives and text descriptions, enhance the understanding and verification of these modifications for internal operational assurance. #################### File: MGH%20Anlage%2014.pdf Page: 9 Context: # Clamping MGH ## Clamping point 4 in OP20 ![Clamping point 4](image_path.png) **Figure: Projection of rest pad** - **Important Notes:** - Ensure the clamping point is aligned properly. - Check the projections before proceeding to the next step. ### References - S3 | 05.08.2024 | Clamping MGH | PPK-E | Georgy Komarov **Internal Document** Image Analysis: ### Analysis of the Provided Visual Content #### 1. Localization and Attribution - **Image 1**: Located on the left side of the page. - **Image 2**: Located on the right side of the page. #### 2. Object Detection and Classification - **Image 1**: - **Objects Detected**: A complex mechanical component, possibly a section of an automotive engine or transmission assembly. - **Classification**: The object is categorized under engineered mechanical parts. - **Key Features**: Visible parts include what appear to be rest pads and various geometric features indicative of a casting or machining process. - **Image 2**: - **Objects Detected**: Another mechanical component, possibly a 3D model of a related or undetermined part, shown with a wireframe overlay. - **Classification**: Similar to Image 1, categorized under mechanical parts or CAD models. - **Key Features**: Wireframe details and annotations indicating measurements or design parameters. #### 3. Scene and Activity Analysis - **Image 1**: - **Scene Description**: A close-up view of a mechanical part with highlighted regions, specifically indicating the clamping point, rest pad projection, and likely inspection features. - **Activities**: The image appears to be explaining the process of clamping or securing the part at a specified point during a manufacturing operation. - **Image 2**: - **Scene Description**: A zoomed-in view of a 3D CAD model with emphasis on specific features of the part, suggestive of a technical inspection or quality control process. #### 4. Text Analysis - **Image 1 Text**: - "Clamping MGH", - "Clamping point 4 in OP20" - "Projection of rest pad" - **Image 2 Text** (Overlay/Annotations): - Various technical parameters or notes displayed as part of the CAD model, though not entirely legible at the provided resolution. - **Significance**: The text explains that the images are related to clamping mechanisms in a manufacturing process (operation point 20). It highlights the importance of precision in positioning and securing the component for further operations. #### 6. Product Analysis - **Image 1**: - **Product**: Mechanical assembly component. - **Features**: Detailed design, highlighting specific areas such as clamping points and rest pads. - **Materials**: Likely metal, based on typical automotive or heavy machinery parts. - **Colors**: Predominantly gray with highlights in green and red annotations. - **Image 2**: - **Product**: 3D CAD model of a mechanical part. - **Features**: Wireframe and surface details with precision markings. - **Materials**: Virtual model; material inferred to be metal. - **Colors**: Green wireframe overlay on a transparent or light gray background. #### 8. Color Analysis - **Image 1**: - **Dominant Colors**: Gray, with green and red highlights. - **Impact**: The use of color helps in distinguishing specific features (e.g., clamping point, rest pad) making it easier for viewers to focus on important details. - **Image 2**: - **Dominant Colors**: Green wireframe with a grayish background. - **Impact**: The green wireframe offers a clear contrast against the background to emphasize technical details. #### 9. Perspective and Composition - **Image 1**: - **Perspective**: Close-up perspective to focus on the intricate details of the clamping mechanism. - **Composition**: Key features are centrally located with annotations clearly pointing to relevant areas. - **Image 2**: - **Perspective**: Zoomed-in view of a CAD model. - **Composition**: The model is presented in such a way as to highlight the technical annotations and measurements, suggesting a focus on technical accuracy. ### Contextual Significance The blended use of physical part illustrations and CAD models suggests a document focused on explaining engineering processes and the precision required in manufacturing, specifically in the context of automotive or heavy machinery industries. The detailed annotations and 3D representations are intended for an audience well-versed in technical and engineering concepts, aiding in process validation or inspection protocols. The combination of detailed views, annotations, and 3D modeling underscores the importance of accuracy and quality control in manufacturing processes, reinforcing the document's technical nature aimed at engineering professionals. #################### File: Standardanschreiben%281%29.pdf Page: 1 Context: # Skoda AUTO a.s., Václava Klementa 869, 293 60 Mladá Boleslav **Einkäufer:** Michala Senkyróva **Abteilung:** Beschaffung Aggregatfertigung und Infrastruktur **Telefon:** **E-Mail:** Michala.Senkyrova@skoda-auto.cz **Datum:** 26.06.2024 --- **Anfrage-Nr.: SK 2024 001598** Sehr geehrte Damen und Herren, wir bitten Sie um Ihr für uns unverbindliches und kostenloses Angebot unter Zugrundelegung unserer nachstehenden aufgeführten Geschäftsbedingungen und unter Verwendung der beigefügten Unterlagen für: **Obráběcí linka motorové skříně MGH SSP/Machining line of the SSP E-drive motor box** Wir bitten um Einreichung Ihres Angebots über die Konzernbusinessplattform. Zuständig für technische Rückfragen ist ** ** **** Georgy.Komarov@skoda-auto.cz Es gelten die nachfolgend aufgeführten Geschäftsbedingungen: - Einkaufsbedingungen ŠKODA AUTO a.s. - Allgemeine Beschaffung (04/2024) Die aktuelle Fassung der Geschäftsbedingungen finden Sie auf [http://www.vwgroupsupply.com](http://www.vwgroupsupply.com) unter folgendem Pfad: Zusammenarbeit / Geschäftsbedingungen Nicht fristgerecht eingereichte Angebote bleiben unbe berücksichtigt. Mit freundlichen Grüßen i.V. Jiří Kulich i.V. Michala Senkyróva --- Dieses Schreiben wurde maschinell erstellt und ist ohne Unterschrift gültig. **ŠKODA AUTO a.s.** T: Václava Klementa 869, 293 60 Mladá Boleslav, Czech Republic IČO: 00177041, Městský soud v Praze B 332 T +420228241111 --- 26.06.2024 | SK BA/2 | KSU 6.1 - 15 Jahre | vertraulich Image Analysis: **Image Analysis Results:** ### Localization and Attribution: - **Image 1**: The entire content is a single page document. No other images are present on the page. ### Text Analysis: - **Detected Text**: ``` Škoda AUTO a.s., Václava Klementa 869, 293 60 Mladá Boleslav **Einkäufer:** Michala Senkyrova **Abteilung:** Beschaffung Aggregatenfertigung und Infrastruktur **Telefon:** **E-Mail:** Michala.Senkyrova@skoda-auto.cz **Datum:** 26.06.2024 **Anfrage-Nr: SK2024 001598** Sehr geehrte Damen und Herren, wir bitten Sie um Ihr für uns unverbindliches und kostenloses Angebot unter Zugrundelegung unserer nachstehenden aufgeführten Geschäftsbedingungen und unter Verwendung der beigefügten Unterlagen für: Obráběcí linka motorové skříně MGH SSP/Machining line of the SSP E-drive motor box Wir bitten um Einreichung Ihres Angebots über die Konzernbusinessplattform. Zuständig für technische Rückfragen ist Vorname Georgy.Komarov@skoda-auto.cz Es gelten die nachfolgend aufgeführten Geschäftsbedingungen: - Einkaufsbedingungen ŠKODA AUTO a.s.- Allgemeine Beschaffung (04/2024) Die aktuelle Fassung der Geschäftsbedingungen finden Sie auf http://www.vwgroupsupply.com unter folgendem Pfad: Zusammenarbeit / Geschäftsbedingungen Nicht fristgerecht eingereichte Angebote bleiben unberücksichtigt. Mit freundlichen Grüßen i.V. Jiří Kulich i.V. Michala Senkyrova Dieses Schreiben wurde maschinell erstellt und ist ohne Unterschrift gültig. **ŠKODA AUTO a.s.** TE: Václava Klementa 869, 293 60 Mladá Boleslav, Czech Republic IČO: 00177041, Městský soud v Praze B 332 T +4203268-1111 26.06.2024 | SK BA/2 | KSU 6.1 - 15 Jahre | vertraulich ``` ### Text Content Analysis: - **Context and Significance**: - The document appears to be an official request for quotation (RFQ) from Škoda AUTO a.s., a prominent automobile manufacturer. - It is addressed by Michala Senkyrova and dated 26.06.2024, aiming to gather a non-binding and free quotation. - The document requests an offer for "Obráběcí linka motorové skříně MGH SSP/Machining line of the SSP E-drive motor box." - It also outlines the designated point of contact for technical queries and directs submissions to the company's business platform. - Emphasis is given to the adherence to specific terms and conditions, with references to relevant documentation that can be found online. - It is noted that offers not submitted within the specified timeframe will not be considered. - The formality is underscored by the automated nature of the document, which does not require a signature to be valid. ### Object Detection and Classification: - **Logos and Symbols**: - The company’s logo (Škoda) is depicted along with associated contact information. - The header includes the official address and other contact details of Škoda AUTO a.s. ### Color Analysis: - **Color Composition**: - Dominant colors include black and white text on a white background. - The Škoda logo comprises green and black colors. - **Impact on Perception**: - The color scheme provides a professional and corporate appearance, enhancing readability and focusing attention on the textual content. ### Perspective and Composition: - **Perspective**: - The document presents straight-on, as typical of a scanned or digital document. - **Composition**: - Structured with clear sections including header, body, and footer, making it easy to follow and locate specific information within the text. ### Contextual Significance: - **Document's Contribution**: - This image serves as an official communication tool within the procurement processes of Škoda AUTO a.s., ensuring standardized requests for supplier quotations and clarity in business dealings. ### Anomaly Detection: - **Unusual Elements**: - There are no notable anomalies in the document; it follows a standard layout expected for corporate communications of this nature. By adhering to structured text and clear headings, the document effectively communicates its purpose and requirements to its intended recipients. #################### File: Standardanschreiben%281%29.pdf Page: 2 Context: # Škoda AUTO a.s. VÁCLAVA KLEMENTA 869, 293 60 Mladá Boleslav --- **Purchaser:** Michala Senkyrova **Department:** Beschaffung Aggregatenfertigung und Infrastruktur **Telephone:** **E-Mail:** Michala.Senkyrova@skoda-auto.cz **Date:** Jun 26, 2024 --- **Inquiry no.:** SK 2024 001598 Dear Sir or Madam, Please submit a non-binding, free-of-charge offer based on our terms and conditions (as listed below) and using the attached documents for: **Obráběcí linka motorové skříně MGH SSP / Machining line of the SSP E-drive motor box** Please submit your bid via the Group business platform. For technical queries, please contact: **First Name Last Name** Georgy.Komarov@skoda-auto.cz The terms and conditions below apply: - General Purchase Terms and Conditions of ŠKODA AUTO a.s. (04/2024) The current version of the terms and conditions can be found at [VW Group Supply](http://www.vwgroupsupply.com) at: Cooperation information / Purchasing Conditions Quotations submitted after the deadline will not be considered. Yours sincerely, p.p. Jiří Kulich p.p. Michala Senkyrova --- This letter was generated automatically and is valid without a signature. --- ŠKODA AUTO a.s. T.E.: Václava Klementa 869, 293 60 Mladá Boleslav, Czech Republic IČO: 00220173, Městský soud v Praze B 332 T * +420202281111 Jun 26, 2024 | SK BA/2 | KSU 6.1 - 15 years | confidential Image Analysis: ### 1. **Localization and Attribution:** There is only one page with a single image of a letter. We will refer to this as **Image 1**. ### 4. **Text Analysis:** The text on the document contains details related to a formal inquiry or request for a bid submission. **Extracted Text:** - **Company Information:** - Skoda AUTO a.s. - Address: Václava Klementa 869, 293 60 Mladá Boleslav - **Inquiry Information:** - Inquiry no.: SK 2024 001598 - Date: Jun 26, 2024 - **Context of the Inquiry:** - The letter requests a non-binding, free-of-charge offer based on specified terms and conditions. - The specific item for the bid is "Machining line of the SSP E-drive motor box". - **Contact Information:** - Purchaser: Michala Senkyrova - Department: Beschaffung Aggregatefertigung und Infrastruktur - E-Mail: Michala.Senkyrova@skoda-auto.cz - For technical queries: Georgy.Komarov@skoda-auto.cz - **Additional Information:** - Mention of the necessity to submit bids via the Group business platform. - Quotes submitted after the deadline will not be considered. - **Signature Block:** - p.p. Jiří Kulich - p.p. Michala Senkyrova **Significance:** The text is significant in the context of procurement and offers a formal request for proposal. It details the requirements and the method of submission for a specific project within the automotive company Skoda AUTO a.s. ### 6. **Product Analysis:** The focus is on the "Machining line of the SSP E-drive motor box." This implies a sophisticated production setup likely requiring advanced machinery designed for precision manufacturing within the automotive sector. ### 8. **Color Analysis:** The color scheme is predominantly white with black text, which is standard for formal business documents. There is also a green logo of Skoda at the top right, which adds brand identity and recognition to the document. ### 9. **Perspective and Composition:** The document is presented in a straightforward, top-down view commonly used for scanning or digital documentation. The composition follows conventional business format with a letterhead providing company details, followed by the body of the message and ending with signatures and disclaimers. ### 10. **Contextual Significance:** This image serves as an official communication for procurement purposes within Skoda AUTO a.s. It addresses professional relationships with suppliers and clearly sets out the requirements and terms for submission of business proposals. ### 12. **Graph and Trend Analysis:** No graphs or trends are presented in this document. ### 13. **Ablaufprozesse (Process Flows):** There are no direct process flows described in the image. ### 14. **Prozessbeschreibungen (Process Descriptions):** The document does not provide detailed descriptions of processes within the image. ### 16. **Trend and Interpretation:** No visual trends are depicted. The text primarily serves as a static formal request for a bid. ### 17. **Tables:** No tables are present in the image. This analysis captures the essential components and purpose of the document, helping understand its function within the procurement process of Skoda AUTO a.s. #################### File: Standardanschreiben%281%29.pdf Page: 3 Context: # Skoda AUTO a.s. Václava Klementa 869, 293 60 Mladá Boleslav ## Nákup: **Zástupce:** Michala Senkyrova **Oddělení:** Beschaffung Aggregatenteiligung und Infrastruktur **Telefon:** **E-Mail:** Michala.Senkyrova@skoda-auto.cz **Datum:** 26.6.2024 Č. poptávky: SK 2024 001598 Vážení, žádáme Vás o nezávaznou a bezplatnou nabídku na základě našich níže uvedených nákupních podmínek zpracovanou podle poskytnutých podkladů pro: **Obráběcí linka motorové skříně MGH SSP / Machining line of the SSP E-drive motor box** Žádáme Vás o podání Vaší nabídky přes koncernovou obchodní platformu. Za technické dotazy odpovídá **Georgy Komarov** E-Mail: Georgy.Komarov@skoda-auto.cz Platí dále uvedené nákupní podmínky: - Všeobecné nákupní podmínky ŠKODA AUTO a.s. (04/2024) - Aktuální znění nákupních podmínek naleznete na [www.vwgroupsupply.com](http://www.vwgroupsupply.com) v následující složce: - Informace o spolupráci / Nákupní podmínky Nabídky, které nebudou podány včas, nebudou akceptovány. S pozdravem, v.z. Jiří Kulich v.z. Michala Senkyrova Tento dopis byl vyhotoven automaticky a platí bez podpisu. --- **SKODA AUTO a.s.** Těšnov 2, 293 60 Mladá Boleslav, Czech Republic Tel: +420.601.774.205, Městský soud v Praze B 332 Tax ID: +42020228-1111 Image Analysis: ### Analysis of Attached Visual Content #### Localization and Attribution: - The visual content is represented by a single document, hence all references pertain to this document. - **Number of Images:** - Only one image is provided in the document. #### Object Detection and Classification: - **Image 1:** - The document contains various elements including text, logos, and formatting elements like lines and text blocks. #### Scene and Activity Analysis: - **Image 1:** - This appears to be an official letter from Skoda AUTO a.s. addressing a supplier or potential partner regarding a request for a quote. - The letter mentions procurement requirements for a machining line for SSP E-drive motor box. #### Text Analysis: - **Image 1:** - Text Content: - The letter is written in Czech and includes formal procurement language. - Key sections include: - Sender and recipient details. - Purpose of the letter: Request for a quote (RFQ). - Specific details about the needed machining line. - Submission guidelines and contact details. - Reference to procurement conditions. - Significance: - This text is crucial for communicating exact procurement requirements and expectations to potential suppliers, ensuring clarity and proper response. #### Product Analysis: - **Image 1:** - The document does not depict any specific products directly but references a machining line for the SSP E-drive motor box, which indicates the nature of the product or service required. #### Anomaly Detection: - **Image 1:** - There do not appear to be any noticeable anomalies in the document. It follows a typical structure for such correspondence. #### Color Analysis: - **Image 1:** - The document primarily uses a white background with black text. - The Skoda logo adds green and gray colors. #### Perspective and Composition: - **Image 1:** - The document is presented from a straightforward, flat perspective, typical of scanned or digitally created documents. - The elements such as the logo, address, and text blocks are aligned for clear readability and professional appearance. #### Contextual Significance: - **Image 1:** - This document serves an important role in the procurement process for Skoda AUTO a.s., establishing official communication with potential suppliers. #### Metadata Analysis: - **Image 1:** - No metadata is available to analyze in the provided visual content. #### Conclusion: The analysis of the provided document indicates that it is an official procurement communication from Skoda AUTO a.s., seeking a quote for a machining line related to the SSP E-drive motor box. The document includes detailed procurement conditions and contact information, ensuring potential suppliers are fully informed about submission requirements and expectations. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE.pdf Page: 1 Context: # Škoda Auto a.s. ## Richtlinie für die Vereinheitlichung von Elementen ### Projekt Erneuerung der Produktionsanlagen im Bereich PKG **Ausgabedatum:** 28.01.2020 **PSZ/1 - Methodik und Standardisierung** **1 - H - 20 DE** Diese Richtlinie hebt die Gültigkeit von früher erlassenen Richtlinien, Normen, Lastenheft und ITS ŠkodaAuto nicht auf. Bei Komponenten, bei denen mehrere Lieferanten genehmigt sind, wird bei der Vergabe von Lieferungen projektbezogener Anlagen immer nur ein Lieferant vertraglich festgelegt. Potentielle Lieferanten sind Lieferanten, die entweder die Projektfreigabe bereits bekommen haben, oder bei denen davon ausgegangen werden, dass sie nach Erprobung und Erfüllung der Konzernstandards die Projektfreigabe noch bekommen können. ### Bearbeitet von: - Martin Janata **PSZ/12** tel.: +420 732 294 691 - Milan vypraclicky **PKG/4** tel.: +420 732 294 226 ### Genehmigt von: - Aleš Ivanovič **PSZ/1** tel.: +420 730 869 870 - Ing. Ladislav Treml **PKG/4** tel.: +420 732 294 945 - Ing. Roman Tanček **PPK/2** tel.: +420 604 292 729 ### Übersicht von Änderungen: | Datum | Seite | Anmerkung | |--------------|-------|-----------------| | 28.01.2020 | 1 | Erste Ausgabe | **Seite 1 von 4** Image Analysis: ### Analysis of Visual Content #### 1. Localization and Attribution: - **Image Specification:** - The entire content is considered as one image (Image 1). #### 2. Object Detection and Classification: - **Objects Detected:** - **Primary Object:** - Document with text, tables, and signatures. - **Identification Features:** - Company logo at the top right corner. - Several names and contact information listed. - Signatures and stamps at the bottom. #### 4. Text Analysis: - **Text Extracted:** - **Header:** - "SIMPLY CLEVER" - "Škoda Auto a.s." - "Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG" - "Ausgabedatum: 28.01.2020" - **Middle Section:** - "PSZ/1 - Methodik und Standardisierung 1 - H - 20 DE" - Body text regarding the guidelines for the unification of various elements and supplier contracts. - **Signatures and Stamps:** - Names with roles (e.g., Martin Janata, Milan Vprachticky, etc.) - Contact details with phone numbers. - **Table Section:** - Columns for "Datum," "Seite," and "Anmerkung." - Date entry: "28.01.2020" with the note "Erste Ausgabe" indicating the first issue. #### 5. Diagram and Chart Analysis: - **Table Content:** - **Column Descriptions:** - "Datum" (Date) - "Seite" (Page) - "Anmerkung" (Remark) - **Row Entries:** - Date: "28.01.2020" - Page: "1" - Remark: "Erste Ausgabe" (First Issue) #### 7. Anomaly Detection: - **Unusual Elements:** - None detected. The document appears to be a standard guideline with usual elements such as text, signatures, stamps, and a table for changes. #### 8. Color Analysis: - **Color Composition:** - Dominant colors: Black text on a white background. - Additional colors include green (highlighted elements) and logos. #### 9. Perspective and Composition: - **Perspective:** - The image is taken from a top-down view, ensuring the entire page and its contents are clearly visible. - **Composition:** - Structured in a formal document layout with a header, body, and footer sections. #### 10. Contextual Significance: - **Document Analysis:** - The document appears to be an official company guideline or directive for standardizing the processes or elements related to the renewal of production facilities under Škoda Auto a.s. It defines the roles, responsibilities, and contact details of key personnel involved, along with stamps and signatures for authenticity. ### Conclusion: - The image analyzed is a structured official document issued by Škoda Auto, outlining standardization guidelines, key personnel, and their contact information for a project regarding the renewal of production equipment. The presence of signatures and stamps underscores the document's legitimacy, while the table at the bottom indicates it is the first issue of the guideline. The dominant use of black and white colors, with elements in green, contributes to the formal appearance of the document. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE.pdf Page: 2 Context: # Škoda Auto a.s. Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG Ausgabedatum: 28.01.2020 ## PSZ/1 - Methodik und Standardisierung 1 - H - 20 DE ## I. Teil: Standards für Produktionsanlagen und Komponenten Die unentstehenden Standards für den Bereich der Aggregaterfertigung im VW-Konzern sind verbindlich: 1. Lastenheft Mechanik (im Weiteren KLH Mechanik) 2. Lastenheft Elektrik (im Weiteren KLH Elektrik) 3. ITS Škoda Auto, viz.: [CZ version](#) | [DE version](#) | Nr. | Produktionsanlagen/Komponenten | Freigegebene Lieferanten | Potentielle Lieferanten | Anmerkungen | |-----|--------------------------------|--------------------------|------------------------|-------------| | 1. | Elektrik, Steuerungstechnik | s. Teile Elektro, S. 3-4 | ITS: 1.1, 5.13 | | 0.1 | Dokumentation Elektrik und Steuerungstechnik | Eplan P8 ver. 2.2 oder höher | | ITS: 1.10 | | 2. | Mechanik | Festo, SMC | Norgren | ITS: 1.13 | | 3. | Pneumatik | | | ITS: 1.17 | | 4. | Schmieren | SKF Lubrikation | | ITS: 1.12 | | 5. | Hydraulik | Bosch Rexroth, Parker | | ITS: 1.12 | | 6. | Filtertechnik | Hydac, Mahle, Bosch Rexroth | | Viz KLH Mechanik | | 0.6 | Pumpen | KSB, Knoll, Grundfos | | | | 7. | Schraubtechnik | Bosch Rexroth | | Bosch Rexroth system BS350 | ## II. Teil: Elektrik, Steuerungssysteme Seite 2 von 4 Image Analysis: ### Localization and Attribution - Image 1: Single image present on the page. ### Text Analysis - The detected text is primarily in German and includes headers, sections, subsections, and a table with specified standards. - **Primary Heading:** - "Škoda Auto a.s." - Other information: "Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG". - Issue Date: "Ausgabedatum: 28.01.2020". - **Section I:** - "I.Teil: Standards für Produktionsanlagen und Komponenten" - **Sections Detail:** - "Die untenstehenden Standards für den Bereich der Aggregatenfertigung im VW-Konzern sind verbindlich:" - Specific Standards: 1. "Lastenheft Mechanik (im Weiteren KLH Mechanik)" 2. "Lastenheft Elektrik (im Weiteren KLH Elektrik)" 3. "ITS ŠkodaAuto, viz.:" - Links to versions: "CZ version, DE version" - **Sections in Table and Notes:** - "PSZ/1 - Methodik und Standardisierung", "1 - H - 20 DE" ### Table and Content - **Header of the Table:** - Columns: - "Nr." (Number) - "Produktionsanlagen/Komponenten" (Production Equipment/Components) - "Freigegebene Lieferanten" (Approved Suppliers) - "Potentielle Lieferanten" (Potential Suppliers) - "Anmerkungen" (Comments) - **Detailed Table Content:** - **Row 1:** - Nr: 1 - Produktionsanlagen/Komponenten: "Elektrik, Steuerungstechnik" - Freigegebene Lieferanten: "s. Teile Elektro, S. 3-4" - Anmerkungen: "ITS: 1.11, 5.13" - **Row 2:** - Nr: 0.1 - Produktionsanlagen/Komponenten: "Dokumentation Elektrik und Steuerungstech" - Freigegebene Lieferanten: "Eplan P8 ver. 2.2 oder höher" - Anmerkungen: "ITS:1.10" - **Row 3:** - Nr: 2 - Produktionsanlagen/Komponenten: "Mechanik" - Freigegebene Lieferanten: "ITS: 1.10" - **Row 4:** - Nr: 3 - Produktionsanlagen/Komponenten: "Pneumatik" - Freigegebene Lieferanten: "Festo, SMC" - Potentielle Lieferanten: "Norgren" - Anmerkungen: "ITS 1.13" - **Row 5:** - Nr: 4 - Produktionsanlagen/Komponenten: "Schmieren" - Freigegebene Lieferanten: "SKF Lubrikation" - Anmerkungen: "ITS 1.17" - **Row 6:** - Nr: 5 - Produktionsanlagen/Komponenten: "Hydraulik" - Freigegebene Lieferanten: "Bosch Rexroth, Parker" - Anmerkungen: "ITS 1.12" - **Row 7:** - Nr: 6 - Produktionsanlagen/Komponenten: "Filtertechnik" - Freigegebene Lieferanten: "Hydac, Mahle, Bosch Rexroth" - Anmerkungen: "ITS 1.12" - **Row 8:** - Nr: 06.1 - Produktionsanlagen/Komponenten: "Pumpen" - Freigegebene Lieferanten: "KSB, Knoll, Grundfos" - Anmerkungen: "Viz KLH Mechanik" - **Row 9:** - Nr: 7 - Produktionsanlagen/Komponenten: "Schraubtechnik" - Freigegebene Lieferanten: "Bosch Rexroth" - Potentielle Lieferanten: "Bosch Rexroth system BS350" ### Diagram and Chart Analysis - The primary diagram is a table, detailing production components, along with approved and potential suppliers. - The table is not a typical chart but provides structured data that indicates standards for different production components and their suppliers. ### Contextual Significance - This image is likely part of a standardization document for Škoda Auto a.s., aimed at unifying elements for production line renewal. - The document specifies standards and approved suppliers for various components of production systems, ensuring uniformity and consistency within the VW Group. ### Color Analysis - The overall color scheme is professional and minimalistic, primarily using black text with green highlights for certain sections and names. - There is a logo in green and grey, which is indicative of the brand's identity and adds a professional touch. ### Perspective and Composition - The perspective is straightforward, presenting information in a clear, readable format from a direct, straight-on viewpoint. - The composition is well-organized, with a logical flow from headers to tables, ensuring ease of reading and understanding. ### Trend and Interpretation - The data suggests a focus on approved suppliers with specific standards and a smaller list of potential suppliers. This implies a stringent quality control and approval process pivotal for maintaining production standards. - Key insights can be drawn regarding which suppliers have dominance in certain components (e.g., Bosch Rexroth appears multiple times). ### Additional Aspects - **Ablaufprozesse (Process Flows):** While process flows are not explicitly depicted, the structured table can be viewed as a part of a larger workflow ensuring compliance with standards. - **Prozessbeschreibungen (Process Descriptions):** Descriptions involve compliance with predefined guidelines, suggesting a regulated production and approval system for components. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE.pdf Page: 3 Context: # Škoda Auto a.s. Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG Ausgabedatum: 28.01.2020 ## PSZ/1 - Methodik und Standardisierung 1 - H - 20 DE | Nr. | Produktionsanlagen/Komponenten | Lieferantenfreigabe | Potentielle Lieferanten | Anmerkungen | |-----|-----------------------------------------|----------------------|---------------------------------|-----------------------------------------| | 1 | Steuerungssysteme SPS(PLC) | Siemens | Siemens Simatic S7 Baureihe | 1500 - TIA V14 und höher | | 2 | NC - Steuerung | Siemens | Siemens (Sinumerik 840D sl.) | | | 3 | PC- und Panel-PC-basierte Steuerungssysteme, Übergeordnete Steuerung – Kommunikationsmodul | Siemens | System - Simatic S7 (HW SPS) | Profinet | | 4 | Visualisierung | Siemens WinCC Flexible | WinCC Flexible 2008 | | | 5 | Steuerungspanels | Siemens | | | | 6 | Dezentrale Sammlung | Profinet | Profibus, IO-link | | | 6.1 | Passiver Stecker-Injektoren (Sensoren, Ventile) | Balluff | Murrelektronik | IO-link | | 6.2 | Aktiver Stecker-Injektoren (Sensoren, Ventile) | Balluff | | Siemens (ET 200 PRO) | | 7 | Dezentrale Peripherie | Siemens | ABB | Kuka (Külsin VRC 4) | | 8 | Roboter | ABB | | | | 9 | Elektrische Frequenzantriebe – Umrichter | SEW Eurodrive | Siemens | VW Konzern Freigabe | | 10 | Elektrische Servo-Antriebe | Siemens, Bosch Rexroth | Siemens | Spezifikation Škoda Auto a.s. | | 11 | Steuerungselemente – Tasten, Kontrolle | Schneider Electric | Siemens | Spezifikation Škoda Auto a.s. | | 12 | Zweihändige Bedienung | Schneider Electric | Schmersal-Ein | Spezifikation Škoda Auto a.s. | | 13 | Elektroschränke (Verteiler) | Rittal | | VW Konzern Freigabe | | 14 | Klemmkästen | Rittal | | VW Konzern Freigabe | | 15 | Kühlung Verteilerschränke (Klimaanlage) | Sick | | Spezifikation Škoda Auto a.s. | | 16 | Lichtschutzanlagen / Scanner | ASO - Contra, Pilz, Schneider Electric | IOSS | Cognex, Keyence, Balluff | Spezifikation Škoda Auto a.s. | | 17 | DMC- und Strichcode-LEsegerät | Balluff, Turck-Banner | Siemens | Spezifikation Škoda Auto a.s. | | 18 | Schalt- und Sicherungselemente | Siemens, Murrelektronik | Schneider Electric | Spezifikation Škoda Auto a.s. | | 19 | Optisches Sensoren | Sick, IFM Electronic, Balluff | | | Image Analysis: ### Analysis of Visual Content #### 1. Localization and Attribution: - **Image Localization and Attribution:** - The document contains a single image comprising a structured table of components and suppliers. - This image will be referred to as **Image 1**. #### 4. Text Analysis: - **Text Extraction:** - The text includes a header, table headers, and cells within the table. - **Header:** - Škoda Auto a.s. - Richtlinie für die Vereinheitlichung von Elementen Projeklt Erneuerung der Produktionsanlagen im Bereich PKG - PSZ/1 - Methodik und Standardisierung - Ausgabe datum: 28.01.2020 - **Table Columns:** - Nr. - Produktionsanlagen/Komponenten - Lieferantenfreigabe - Potenzielle Lieferanten - Anmerkungen - **Table Data:** - **Row 1:** 1. Steuerungssysteme SPS(PLC) 2. Siemens 3. Siemens Simatic S7 Baureihe 1500 - TIA V14 und höher - **Row 2:** 1. NC - Steuerung 2. Siemens 3. Siemens (Sinumerik 840D sl.) - And so on through 20 rows as listed in the image. #### 9. Perspective and Composition: - **Perspective:** - The image is a top-down view of a single page document. - **Composition:** - The page is structured into a table format which is centrally aligned. - The text is clearly organized with sections separated by lines. #### 10. Contextual Significance: - **Contextual Significance:** - This image appears to be part of a technical document that outlines specifications and supplier information for various components used in production processes. - The table lists specific equipment and systems (such as Steuerungssysteme SPS (PLC), NC-Steuerung) along with their approved suppliers (primarily Siemens) and potential alternative suppliers. - The amendments or notes column provides further specifications or requirements for each component. #### 13. Graph Numbers: - **Detailed Breakdown:** - A total of 20 rows detail various components including control systems, injection systems, robots, cabinets, and safety components. - Each row assigns an item number, a description of the component, the approved supplier, potential suppliers, and any noteworthy comments. ### Conclusion: This structured and detailed table in the image organizes key information about production components and their respective suppliers. It underscores supplier dependability and the specific requirements for various parts of a production system. The table represents a methodical approach to maintain standards and consistency in the production workflow while accommodating precise technical requirements. Checklists like this can ensure streamlined operations and uphold quality control in production environments. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE.pdf Page: 4 Context: # Škoda Auto a.s. Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG Ausgabedatum: 28.01.2020 ## PSZ/1 - Methodik und Standardisierung 1 - H - 20 DE | Nr. | Produktionsanlagen/Komponenten | Lieferantenfreigabe | Potentielle Lieferanten | Anmerkungen | |-----|-----------------------------------------------|--------------------------------|----------------------------------------|------------------------------------| | 21 | Induktionssensoren, Positionsschalter und | Balluff, IFM Electronic | Sick | Spezifikation Škoda Auto a.s. | | | Endschnaller | | | | | 22 | Klemme und Klemmzubehör | Phoenix Contact, Wago | Siemens | Spezifikation Škoda Auto a.s. | | 23 | Durchflussmesser und Thermometer | IFM Electronic, Hydac | Parker, Bosch Rexroth | Spezifikation Škoda Auto a.s. | | 24 | Sensoren- und Endschalteinrichtung | Balluff - Lumberg | Pepperl+Fuchs | Spezifikation Škoda Auto a.s. | | | Kabel, Stecker und Sensorenzubehör | Mur elektorn | | | | 25 | Stecker – schwer und leicht | Harting, Phoenix Contact, Weidmüller | Murrelektronik | | | 26 | Lichtsignalisierung – Blaulicht und | Murrelektronik | Siemens | | | | Signalleuchten | | | | | 27 | Nockensicherheitschalter | Schmersal | Balluff | | | 28 | Sicherheitsschalter an Schutzüren, Fenster usw. | Pilz, Schmersal | Euchner | Spezifikation Škoda Auto a.s. | | 29 | Sicherheitsystem und Sicherheitsmodule | Pilz, Siemens | Schneider Electric | Pilz (PNOZsigma), Siemens (S7 3xxF) | | 30 | Mechanisches Endschnaller | Balluff, Siemens | Euchner | Spezifikation Škoda Auto a.s. | | 31 | Installationskabel | LAPP Kabel | Hellukabel | | | 32 | Hochflexible Kabelzueleme | LAPP Kabel | Hellukabel | | | 33 | Überspannungsschutzelemente | Hakel | ABB | | | 34 | Kabelkanäle und -rinnen | OBO-Bettermann, Niedax | Kopos Kolin | | | 35 | Energiespeichende Kabelbieten | Murrelektronik | Brevetti | | | 36 | Optische Sensoren | IFM, Keyence | Sick | Spezifikation Škoda Auto a.s. | | 37 | Kamerabasierte Messsysteme | Cognex, Keyence, Sick | | | | 38 | Wegmesssysteme, linear, Winkel | HEIDENHAIN | | | | 39 | Reservespeisungsquellen | Siemens, APC, Murrelektronik | Phoenix Contact | | | 40 | Drucksensoren | Rexroth, Parker, IFM | Hydac | | Seite 4 von 4 Image Analysis: ### Detailed Examination of the Visual Content: #### 1. Localization and Attribution: - **Image Identification**: Pages contain a single image. - **Image Number**: Image 1 #### 4. Text Analysis: - **Title**: "Richtlinie für die Vereinheitlichung von Elementen Projekt Erneuerung der Produktionsanlagen im Bereich PKG" - **Subtitle**: "1 - H - 20 DE" - **Date**: "Ausgabedatum: 28.01.2020" - **Company Name**: "Škoda Auto a.s." - **Table Content**: - **Column Headers**: Nr., Produktionsanlagen/Komponenten, Lieferantfreigabe, Potentielle Lieferanten, Anmerkungen - **Row Entries**: 1. 21: Induktionssensoren, Positionsschalter und Endschalter | Balluff, IFM Electronic | Sick | Spezifikation Škoda Auto a.s. 2. 22: Klemme und Klemmenzubehör | Phoenix Contact, Wago | Siemens | Spezifikation Škoda Auto a.s. 3. 23: Durchflussmesser und Thermometer | IFM Electronic,Hyac | Parker, Bosch Rexroth | Spezifikation Škoda Auto a.s. 4. 24: Sensoren- und Endschalterinstallation Kabel, Stecker und Sensorenzubehör | Balluff - Lumberg Nur elektronik | Pepperl + Fuchs | Spezifikation Škoda Auto a.s. 5. 25: Stecker – schwer und leicht | Harting, Phoenix Contact, Weidmüller | Murrelektronik | 6. 26: Lichtsignalisierung – Baulichter und Signalleuchten | Murrelektronik | Siemens | 7. 27: Nockenschalterschutz | Schmersal | Balluff | 8. 28: Sicherheitsschalter an Schutztüren, Fenstern usw. | Pilz, Schmersal | Euchner | Spezifikation Škoda Auto a.s. 9. 29: Sicherheitssystem und Sicherheitsmodule | Pilz, Siemens | Schneider Electric | Pilz (PNOZsigma), Siemens (S7 3xxF) 10. 30: Mechanische Endschalter | Balluff, Siemens | Euchner | Spezifikation Škoda Auto a.s. 11. 31: Installationskabel | LAPP Kabel | Helukabel | 12. 32: Hochflexible Kabel | LAPP Kabel | Helukabel | 13. 33: Überspannungsschutzelemente | Hakel | ABB | 14. 34: Kabelkanäle und -rinnen | OBO-Bettermann, Niedax | Kopos Kolin | 15. 35: Energiebewiegende Kabelketten | Murrplastik, Brevetti | Kabelschlepp | 16. 36: Optische Sensoren | IFM, Keyence | Sick | Spezifikation Škoda Auto a.s. 17. 37: Kameraerfassungssysteme | Cognex, Keyence, Sick | | 18. 38: Wegemesssysteme, linear, Winkel- | HEIDENHAIN | | 19. 39: Reservenovellungsquellen | Siemens, APC, Murrelektronik | Phoenix Contact | 20. 40: Drucksensoren | Rexroth, Parker, IFM | Hydac | #### 5. Diagram and Chart Analysis: - **Table Analysis**: - The table lists various production components (under "Produktionsanlagen/Komponenten"), the approved suppliers (under "Lieferantfreigabe"), potential suppliers (under "Potentielle Lieferanten"), and additional remarks or specifications. - Each row provides detailed information about different components and their associated suppliers. #################### File: Interni%20smernice%20-%20komponenty%20SZ_DE.pdf Page: 4 Context: #### 11. Graph Numbers: - **Row Numbers and Entries**: - 21: "Induktionssensoren, Positionsschalter und Endschalter | Balluff, IFM Electronic | Sick | Spezifikation Škoda Auto a.s." - 22: "Klemme und Klemmenzubehör | Phoenix Contact, Wago | Siemens | Spezifikation Škoda Auto a.s." - 23: "Durchflussmesser und Thermometer | IFM Electronic,Hyac | Parker, Bosch Rexroth | Spezifikation Škoda Auto a.s." - 24: "Sensoren- und Endschalterinstallation Kabel, Stecker und Sensorenzubehör | Balluff - Lumberg Nur elektronik | Pepperl + Fuchs | Spezifikation Škoda Auto a.s." - 25: "Stecker – schwer und leicht | Harting, Phoenix Contact, Weidmüller | Murrelektronik" - 26: "Lichtsignalisierung – Baulichter und Signalleuchten | Murrelektronik | Siemens" - 27: "Nockenschalterschutz | Schmersal | Balluff" - 28: "Sicherheitsschalter an Schutztüren, Fenstern usw. | Pilz, Schmersal | Euchner | Spezifikation Škoda Auto a.s." - 29: "Sicherheitssystem und Sicherheitsmodule | Pilz, Siemens | Schneider Electric | Pilz (PNOZsigma), Siemens (S7 3xxF)" - 30: "Mechanische Endschalter | Balluff, Siemens | Euchner | Spezifikation Škoda Auto a.s." - 31: "Installationskabel | LAPP Kabel | Helukabel" - 32: "Hochflexible Kabel | LAPP Kabel | Helukabel" - 33: "Überspannungsschutzelemente | Hakel | ABB" - 34: "Kabelkanäle und -rinnen | OBO-Bettermann, Niedax | Kopos Kolin" - 35: "Energiebewiegende Kabelketten | Murrplastik, Brevetti | Kabelschlepp" - 36: "Optische Sensoren | IFM, Keyence | Sick | Spezifikation Škoda Auto a.s." - 37: "Kameraerfassungssysteme | Cognex, Keyence, Sick" - 38: "Wegemesssysteme, linear, Winkel- | HEIDENHAIN" - 39: "Reservenovellungsquellen | Siemens, APC, Murrelektronik | Phoenix Contact" - 40: "Drucksensoren | Rexroth, Parker, IFM | Hydac" These insights provide a detailed understanding of the Škoda Auto a.s. component and supplier specifications. #################### File: VW%2010130_CS.pdf Page: 1 Context: # VOLKSWAGEN AG ## Prověrka způsobilosti stroje pro měřitelné charakteristiky **VW 101 30** **Datum:** únor 2005 ### Klíčová slova: Maschinenfähigkeitsunter-suchung [**prověrka způsobilosti**], Fähigkeitskennwert [**parameter způsobilosti**], Qualitätsfähigkeit [**kvalitativní způsobilost**], Maschinenfähigkeit [**způsobilost stroje**] --- ### Obsah 1. [Účel a oblast použití](#1-úcel-a-oblast-použití)......................................................... 2 2. [Principy prověrky způsobilosti stroje](#2-principy-proverky-zpusobilosti-stroje)........... 3 3. [Teoretické základy](#3-teoretické-základy)........................................................... 4 3.1 [Distribuční modely](#31-distribuční-modely)......................................................... 4 3.1.1 [Normální rozdělení](#311-normální-rozdělení).................................................. 5 3.2 [Neúplná rozdělení](#32-neuplna-rozdělení)........................................................ 6 3.3 [Ravleighovo rozdělení](#33-ravleighovo-rozdělení).......................................... 6 3.4 [Zjištění způsobilosti](#34-zjištění-způsobilosti).................................................. 7 3.2.1 [Zjištění způsobilosti u definovaných distribučních modelů](#322-zjištění-způsobilosti-u-definovaných-distribučních-modelů)......................................... 16 3.2.2 [Zjištění způsobilosti u nedodržovaných distribučních modelů](#3222-zjištění-způsobilosti-u-nedodržovaných-distribučních-modelů)................................... 16 3.3 [Měřené hodnoty pro způsobilost stroje](#33-měřené-hodnoty-pro-způsobilost-stroje)....................................................... 21 4. [Statistické testy](#4-statistické-testy)................................................................ 21 4.1 [Provádění prověrky způsobilosti stroje](#41-provádění-prověrky-způsobilosti-stroje)........ 21 4.1.1 [Použití zkušebních prostředků](#411-použití-zkušebních-prostředků)................... 22 4.1.2 [Odběr namátkových vzorků](#412-odběr-namátkových-vzorků)............................ 22 4.2 [Zvláštní pravidla pro omezené MFU](#42-zvláštní-pravidla-pro-omezené-mfu)............... 23 4.3 [Vyhodnocení dat](#43-vyhodnocení-dat).......................................................... 25 4.4 [Výběr očekávaného distribučního modelu](#44-výběr-očekávaného-distribučního-modelu)..... 26 4.4.1 [Test odlehlých hodnot](#441-test-odlehlých-hodnot)...................................... 26 4.4.2 [Test změny polohy výroby](#442-test-změny-polohy-výroby)................................. 27 4.4.3 [Test odkazu na stanovené distribuční modely](#443-test-odkazu-na-stanovené-distribuční-modely)............................................................ 27 4.4.4 [Vyhodnocení podle normálního rozdělení](#444-vyhodnocení-podle-normálního-rozdělení)............................................ 28 4.5 [Vyhodnocení podle stanovené hodnoty](#445-vyhodnocení-podle-stanovené-hodnoty).... 28 4.6 [Nepřímé vyhodnocení](#446-nepřímé-vyhodnocení)............................................... 29 4.7 [Posouzení výsledků](#447-posouzení-výsledků).................................................. 29 5. [Optimalizace stroje](#5-optimalizace-stroje)....................................................... 29 5.1 [Náklady na nezpůsobilý stroj](#51-náklady-na-nezpůsobilý-stroj)........................ 30 6. [Příklady](#6-příklady)....................................................................................... 30 7. [Související podklady](#7-související-podklady)......................................................... 33 8. [Odkazy na literaturu](#8-odkazy-na-literaturu)....................................................... 33 9. [Seznam hesel](#9-seznam-hesel)................................................................ 34 --- ### Informace: Úřad TR1 - Normalizace Tel.: +420-123-456-789 #### Fachverantwortung/Obor odpovědnost KIS-05-12 Název Tel.: 792968 Alternativní Tel.: +420-543-961-123 --- **Poznámka:** Veškerá práva vyhrazena. Webové stránky obsahují ochranné známky a názvy výrobků společnosti Volkswagen Konzern. Image Analysis: ### Localization and Attribution **Image 1**: - This is the only image on the page. ### Text Analysis **Image 1:** - The image is in the Czech language. - **Title**: "Proverka zpusobilosti stroje pro meritlené charakteristiky" (translated: "Machine capability test for measurable characteristics"). - **Subheading**: "VOLKSWAGEN AG, VW 101 30" - **Keywords**: "Machinenfähigkeituntersuchung" (machine capability investigation), "Fähigkeitskennwert" (capability index), "Qualitätsfähigkeit" (quality capability). - **Table of Contents**: - 1 Purpose and Application Area - 2 Principles of Machine Capability Testing - 3 Theoretical Background - 3.1 Distribution Models - 3.2 Determining Capability Based on Defined Distribution Models - 3.3 Statistical Tests - 4 Conducting Machine Capability Tests - 4.1 Use of Testing Resources - 4.2 Sample Collection - 4.3 Special Rules for Measurements - 4.4 Data Evaluation - 5 Related Backgrounds - 6 References - 7 Glossary This outlines the technical report structure on machine capability testing within Volkswagen AG. ### Metadata Analysis **Image 1**: - **Klass-Nr.**: 11 00 5. - **Date**: February 2005. - **Laid Down by**: VW. - **Pertains to Norm**: Koncernnorm. - **Length**: 35 pages. - **Source**: "Quelle: NOLIS (Norm vor Anwendung auf Aktualität prüfen), Check standard for current issue prior to usage." ### Graph and Trend Analysis **Image 1**: - No graphs or trends are visible in the image. ### Process Flows (Ablaufprozesse) **Image 1**: - **Included process descriptions**: - Determining capability based on various distribution models. - Statistical tests involved in machine capability evaluation. - Specific procedures for data evaluation and processing. - Documentation and reporting of the capability tests. #################### File: VW%2010130_CS.pdf Page: 1 Context: ### Prozessbeschreibungen (Process Descriptions) **Image 1**: - The table of contents implies detailed descriptions of the steps taken to evaluate machine capabilities. This includes collecting samples, using testing resources, statistical assessments, and special rules for data collection and evaluation. ### Contextual Significance **Image 1**: - This document appears to be part of a technical standard or guideline manual from Volkswagen AG, outlining the procedures for evaluating machine capabilities. This could form part of internal quality assurance and process optimization efforts. The significance is likely centered around maintaining high standards of production efficiency and product quality within the company. ### Tables **Image 1**: - No tables are visible in the image. ### Perspective and Composition **Image 1**: - Perspective: The image is a direct, upright scan or photograph of a document. - Composition: It focuses on centering the document for clear visibility of the text and structure, designed for easy reading and reference. ### Anomaly Detection **Image 1**: - There do not appear to be any anomalies or unusual elements in this image. ### Color Analysis **Image 1**: - The color scheme is black text on a white background, typical for documents to ensure readability and emphasis on information. ### Summary The analyzed image is a cover page of a technical report from Volkswagen AG detailing the processes and guidelines for conducting machine capability tests on measurable characteristics. The document is technical in nature, meant for internal use, and emphasizes thorough procedural instructions. #################### File: VW%2010130_CS.pdf Page: 2 Context: # Úvod Posouzení způsobilosti stroje z hlediska sledovaných měřitelnych výrobních charakteristik je důležitým předpokladem pro splnění stanovených kvalitativních požadavků. Pro mnoho praktických případů pro způsobilost však neexistují normy nebo jednotné konečné směrnice, takže se studený případ mohl vyplynout celou řadu různých hodnocení způsobilosti. Tato norma byla tedy zpracována, aby bylo možno provádět prověrky způsobilosti podle jednotných pravidel pro všechny praktické případy a tím byla zajištěna srovnatelnost výsledků. Norma obsahuje v uzavřené formě kompletní teoretické podklady, které jsou nutné pro použití a interpretaci. Pouze statistické testy, které již byly podrobně popsány v normách nebo odborné literatuře, jsou uvedeny pouze pomocí odkazu. Cílem prověrky způsobilosti stroje podle této normy počítačový program, ve kterém jsou realizovány popsané algoritmy. Pokud je takový program k dispozici, může se vycházet z této normy i v podstatě na ustanovení oddílu 4 a v případě potřeby si může nalistovat teoretické poznatky. Nejduležitější podmínky jsou naproti tomu: 1. 4 - Odrážení namátkových vzorků 2. 4.5 - Dokumentace 3. 4.6 - Posouzení výsledků V oddílu 5 jsou navíc uvedeny příklady, které mají sloužit jako pomůcka pro posouzení výsledků. # 1 Účel a oblast použití Cílem prověrky způsobilosti stroje je dokumentované posouzení, zda prověřovaný stroj umožňuje bezpečnou výrobu sledovaných charakteristik v rámci definovaných mezních hodnot. V ideálním případě by přitom měly na výrobní proces působit pouze úvahy podmíněným strojem. Jak a za jakých předpokladů je nutno provádět prověrky způsobilosti stroje, je předmětem této normy. Je použitelné na libovolné průběžné (měřitelné) výrobní charakteristiky. 1. Níže pro tento druh charakteristik uveden název „měřitelné charakteristiky“ místo názvu „průběžné charakteristiky“ uvedeného v DIN, proto je tento výraz ze VW zajištěn. Image Analysis: Here is the detailed analysis of the provided image: ### Localization and Attribution: - **Image 1** is located at the top of the page, occupying the entire space of the page. ### Text Analysis: - The image is a document page written in Czech, consisting primarily of text. - **Heading:** - The first section headings are "Úvod" (Introduction) and "Účel a oblast použití" (Purpose and Scope of Use). - **Content:** - **Introduction:** - Describes that the inspection of the machine's capability in terms of monitored measurable production characteristics is a necessary prerequisite for meeting set qualitative requirements. - Indicates that previous verifications were not standardized and lacked a unified guideline. - Explains that the included standard was developed to provide a common framework to ensure the verifications' validity. - **Procedure Sections:** - It lists various sections/references within the document for further procedures: - **4.2**: "Odběr namátkových vzorků" (Random Sampling) - **4.5**: "Dokumentace" (Documentation) - **4.6**: "Posouzení výsledků" (Evaluation of Results) - Additionally, examples are provided in section V to aid in the evaluation. - **Purpose and Scope of Use:** - States the aim of the verification is to document whether the tested machine allows for the safe production of monitored characteristics within defined limits. - Specifies that ideally, the production process should only be influenced by the machine. - Discusses the prerequisites necessary for conducting the verification of the machine's capability according to this standard. - Indicates that the standard is applicable to any measurable production characteristic in continuous production. ### Contextual Significance: - The document appears to be a technical or procedural manual related to manufacturing or production quality assessment, specifically for the Volkswagen (VW) corporation. - The detailed instructions and standard references suggest it is used by professionals to ensure consistency and reliability in machine evaluations within the production environment. #################### File: VW%2010130_CS.pdf Page: 3 Context: # 2 Princip prověrky způsobilosti stroje Na základě náhodných vlivů vyplývajících z výroby různých druhů stejných druhů pomocí prověřovaného stroje zásadně rozdílné hodnoty sledovaných charakteristik. Tyto hodnoty charakteristiky \(S\) jsou v závislosti na kvalitě výroby rozptylené okolo polohy podmíněné systematickými vlivy. Proto se prověřuje, jak dobře souhlasí rozdělení hodnot charakteristiky s tolerančním intervalem definovaným konstruktorem (obrázek 1). Výhodnocení tohoto je vyjádřeno parametry způsobilosti \(C_p\) a \(C_{pk}\) (kdž solo kapacity), přičemž hodnota \(C_{pk}\) zohledňuje polohu výroby rozptylu a hodnota \(C_p\) také polohu výroby. Tyto charakteristiky musí být minimálně tak velké jako definované mezní hodnoty, aby byl splněn požadavek na způsobilost výrob. Pro zjištění charakteristiky způsobilosti z hlediska sledované charakteristiky je nutno zhodnotit možné identifikační podmínky kategorií vlivu materiál, člověk, metoda a prostředí, abychom mohli zjistit pozici vůči stroji. Z tohoto vzorku se v souladu s očekáváním vhodně pohybuje v hranice intervaluu spolehlivosti \(X_{13,5}\), \(X_{99,865}\), což zahrnuje soubor hodnot charakteristik (teoreticky nekonečný počet) a porovná se s intervalem stanovený tak, že podle hodnot do jednotlivých oblastí rozptylu na obě strany vždy \(p_e = 0,135\). Na základě kontroly, zda hodnoty charakteristiky odpovídají očekávané zakonitosti. ## Tolerance ![Obrázek 1 - Příklad rozdělení hodnot charakteristiky v rámci definovaného tolerančního intervalu](path_to_image) \[ \text{Hodnota charakteristiky} = p_{e} \quad G_L \quad G_U \] 2. Pojem hodnoty charakteristiky nesmí být zaměňován s měrnou hodnotou, protože posléze uvedený pojem obsahuje v porovnání s giveny určitou nejasnost. 3. Pro označení mzněných hodnot ji přípustné taktéž USG, OSG nebo USL, OSL nebo Tu, To. Image Analysis: ### Localization and Attribution: 1. **Image Numbering**: - **Image 1**: This is located at the middle and integrates textual data with a schematic representation. ### Object Detection and Classification: 2. **Objects Detected**: - **Image 1**: - Object Type: Diagram/Graph - Key Features: Contains a bell curve with values on the X and Y axes, and labels denoting specific points on the curve. ### Scene and Activity Analysis: 3. **Scene Description**: - **Image 1**: Shows a bell curve graph that depicts the distribution of a characteristic in relation to defect rates, with accompanying descriptive text explaining the significance of the distribution. ### Text Analysis: 4. **Extracted Text**: - Document Title: "Princip prověrky způsobilosti stroje" - Section Title: "2" - Detailed Description: The text explains a principle of machine capability verification. It involves statistical parameters, methodical characteristics, and the depiction of a characteristic’s tolerance and distribution. - Key Phrases: "Náhodných vlivů", "výrobek", "díl", "stejného druhu", "hodnoy shvěro", "II". ### Diagram and Chart Analysis: 5. **Diagram Description**: - **Axes**: - X-axis: Hodnota charakteristiky (Characteristic value) - Y-axis: Četnost (Frequency) - **Legend**: - p = 0.135%: This represents the probability or confidence interval marks on both sides of the bell curve. - G_l and G_u: Represent the lower and upper tolerance limits respectively, in a process distribution context. - μ (mu): The mean value of the distribution. - X_0.135% and X_99.865%: Points on the curve indicating edges of the tolerance limits for a specified confidence level. ### Textual Explanation in Image Context: - This diagram illustrates how the distribution of a characteristic falls within a defined tolerance interval, highlighting the areas of very low probability (0.135%) which lie outside the tolerance limits. This is significant for quality control and indicating machine or process capability. ### Trend and Interpretation: 12. **Trends Identified**: - The bell curve indicates a normal distribution where the majority of values cluster around the mean μ and decrease symmetrically towards the tails. This suggests a process that is statistically controlled with most values falling within the specified tolerance limits. ### Tables: 14. **Analyzed Content**: - There is no specific table in the provided visual content. ### Metadata Analysis: 15. **Available Metadata** (from visible content): - Document Identifier: "VW 101 30: 2005-02" - Page Number: "Strana 3" - These references are to the document’s standard and page number. ### Graph and Trend Analysis: 13. **Detailed Analysis**: - Central Value (μ): Represents the average or target value for the characteristic being measured. - Limits (G_l and G_u): Define the acceptable tolerance range for the process. - Probability Cutoffs (p = 0.135%): Define the thresholds at which values are considered outliers in the tolerance interval. ### Abschlussprozesse (Process Flows): This relates to the explanation provided in the text about the verification of machine capability by checking the spread and alignment of production values with the specified tolerance limits. ### Contextual Significance: 10. **Document contribution**: - The image supports the textual explanation of machine capability verification by visually representing how production values are distributed within the specified tolerances, thereby aiding in understanding and adhering to the statistical principles of quality control. This comprehensive analysis integrates various aspects of the provided visual content, highlighting key features, textual context, and diagrammatic interpretation to provide detailed insights into the information conveyed in the image. #################### File: VW%2010130_CS.pdf Page: 4 Context: # 3 Teoretické podklady ## 3.1 Distribuční modely Rozdělení hodnot charakteristik lze pro většinu druhů výrobních charakteristik popsat distribučním modelem. Tak lze většinou dvourozměrné tolerované výrobní charakteristiky, např. délkové rozměry, průměr a kručící moment, založit na normálním rozdělení. Rozptyl jednostranného nahoru tolerované výrobní charakteristiky lze oproti tomu zpravidla popsat pomocí Weibullova nebo Rayleighova rozdělení. Tak lze např. Weibullovo rozdělení použít pro druhy charakteristik rovnovážnosti, asymetrie a Rayleighovo rozdělení pro druhy charakteristik poloha, soustředěnost. ### 3.1.1 Normální rozdělení #### Funkce hustoty pravděpodobnosti Funkce hustoty pravděpodobnosti (zkráceně funkce hustoty) normálního rozdělení, která je graficky znázorněna v obrázku 2, zní: $$ f(x) = \frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{(x - \mu)^2}{2\sigma^2}} \tag{1.1} $$ kde \(s\) parametry průměrná hodnota \(\mu\) a směrodatná odchylka \(\sigma\), které charakterizují polohu a šířku rozdělení, přičemž mocnina standardní odchylky \(\sigma^2\) je označována jako rozptyl. ![Obrázek 2 – Funkce hustoty pravděpodobnosti normálního rozdělení](link-to-image) **Zdroje:** 1. Informace jsou převzaty z dokumentu VW 101 30: 2005-02. Image Analysis: ### Analysis of the Visual Content: #### Localization and Attribution: - **Image**: There is a single image on the page, which will be referred to as **Image 1**. - **Position**: The image is located at the bottom section of the page. #### Object Detection and Classification: - **Image 1**: This image contains a graph depicting a normal distribution curve. The following objects are identified and classified: - **Graph**: A bell-shaped curve indicating a normal distribution (Gaussian distribution). - **Labels and Text**: The x-axis, y-axis, and specific points along the curve are labeled. - **Markers**: Specific points such as the mean (μ) and standard deviations (σ) are indicated. #### Scene and Activity Analysis: - **Image 1**: The scene is an illustration of the normal distribution function in a mathematical or statistical context. The main activity is the depiction of the distribution probability density function. #### Text Analysis: - **Text Detected**: - "Strana 4" - "VW 101 30: 2005-02" - "3 Teoretické podklady" - "3.1 Distribuční modely" - "3.1.1 Normální rozdělení" - "Funkce hustoty pravděpodobnosti (zkráceně funkce hustoty) normálního rozdělení..." - Formula for normal distribution \( f_v(x) = \frac{1}{\sigma \sqrt{2\pi}} e^{-\frac{ (x-\mu)^2}{2\sigma^2}} \) - Several key parameters and points specified such as "μ-4σ", "μ-3σ", "μ-2σ", "μ-σ", "μ", "μ+σ", "μ+2σ", "μ+3σ", "μ+4σ". - "Obrázek 2 – Funkce hustoty pravděpodobnosti normálního rozděleni" - **Contextual Explanation**: - The text explains the normal distribution density function. Formula (1.1) provides the mathematical definition, while the graph visually represents this function indicating key statistical markers like the mean (μ) and different standard deviations (σ) from the mean. #### Diagram and Chart Analysis: - **Image 1**: - **Axes and Scales**: - **X-axis (Horizontal)**: Represents the characteristic value (Hodnota charakteristiky). - **Y-axis (Vertical)**: Represents the probability density (Hustota pravděpodobnosti). - **Legend and Markers**: - Indicates different points such as "μ", "μ-σ", "μ+σ", etc., representing mean and standard deviations. - **Key Insights**: - Shows typical bell-curve shape of normal distribution. - Indicates inflection points and how the probability density changes around the mean. - Significance of values at "μ", "μ±σ", "μ±2σ", etc. percentages at each specified point (e.g., 0.135% at "μ ±4σ"). #### Graph Numbers: - **Data Points** (Approximations due to the nature of labeling): - **At μ**: Maximum probability density. - **At μ±σ**: Probabilities decrease significantly. - **External Points**: 0.135% likelihood at "μ±4σ". #### Color Analysis: - **Image 1**: - **Color Composition**: Primarily black and white. - **Dominant Colors**: Black (for text and lines) on white background. - **Impact on Perception**: Ensures clear visibility and emphasis on graph and text for analytical purposes. #### Perspective and Composition: - **Perspective**: Frontal, straight-on view. - **Composition**: Centralized graph with explanatory text surrounding it, making it effective in demonstrating the concept clearly. #### Contextual Significance: - **Image 1**: Contributes significantly to the text's explanation by visually depicting the mathematical concept of normal distribution, aiding in understanding and retention. ### Summary: The document discusses theoretical underpinnings of statistical distribution models, specifically focusing on the normal distribution. The included graph is critical for illustrating key concepts and providing a visual reference for the probability density function of the normal distribution. The text serves to elucidate the mechanics and importance of these statistical markers and their practical applications. #################### File: VW%2010130_CS.pdf Page: 5 Context: # Jako pravděpodobnost lze interpretovat Jako pravděpodobnost lze interpretovat v obrázku 2 podíl plochy pod grafem ve sledovaném intervalu. Pravděpodobnost, že se hodnota charakteristiky x bude nacházet v základním souboru, který je maximálně tak velký, jako sledovaná mezní hodnota \(x_p\), je tak uváděna primitivní funkcí – funkcí rozdělení. Ta zní pro normální rozdělení: \[ F_x(x) = \int_{-\infty}^{x} f_x(u) \, du \tag{1.2} \] Příčina: \[ f_x(x) = \frac{dF_x(x)}{dx} \tag{1.3} \] a pro všechny hodnoty \(x\) platí \(f_x(x) \geq 0\). ## Transformace \[ u = \frac{x - \mu}{\sigma} \tag{1.4} \] Vyplněte (2.1) hustota pravděpodobnosti standardizovaného normálního rozdělení: \[ \phi(u) = \frac{1}{\sqrt{2\pi}} e^{-\frac{u^2}{2}} \tag{1.5} \] a distribuční funkce: \[ \Phi(u) = \int_{-\infty}^{u} \phi(t) \, dt \tag{1.6} \] se standardní odchylkou \(\sigma = 1\). ### 3.1.2 Weibullovo rozdělení Weibullovo rozdělení vzniká přeložením funkce hustoty normálního rozdělení na nulovém bodě, přičemž hodnoty funkce větší od bodu přeložení se přitukují v bodu správno od nich. Distribuční funkce a funkce rozdělení pravděpodobnosti Weibulova rozdělení tak zní: \[ f(x) = \frac{1}{\sigma} \left(\frac{x - H_m}{\sigma}\right)^{\beta - 1} e^{-\left(\frac{x - H_m}{\sigma}\right)^\beta} \quad \text{pro } x \geq 0 \tag{1.7} \] \[ F(x) = 1 - e^{-\left(\frac{x - H_m}{\sigma}\right)^\beta} \tag{1.8} \] **Příčina:** - \(H_m\): Střední hodnota původního normálního rozdělení, která označuje systematický posun nulového bodu - \(\sigma\): Standardní odchylka původního normálního rozdělení - \(\Phi\): Distribuční funkce standardizovaného normálního rozdělení Image Analysis: ### Text Analysis 1. **Localization and Attribution:** - **Image Number:** Image 1 - This is the only image on the page. 2. **Text Analysis:** - **Detected Text:** - The text is written in Czech. - The headline at the top right indicates the document section, "Strana 5" (Page 5) with a code "VW 101 30: 2005-02". - The main part of the text explains probabilistic concepts and distributions. - **Mathematical Formulas and Equations:** - Several mathematical formulas and equations are present, labeled from (1.2) to (1.8). - (1.2) Integral equation for cumulative distribution function \( F_{W}(x) \). - (1.3) Property of the integral of the probability density function over its entire range. - (1.4)Transforming variable \( u = \frac{x - \mu}{\sigma} \). - (1.5) Normal distribution density function \( \varphi(u) \). - (1.6) Distribution function \( \Phi_{0}(u_{α}) \). - (1.7) and (1.8) Relate to Weibull distribution. - **Section Title:** - Another title reads "Weibullovo rozdělení", which translates to "Weibull distribution". - **Subsection and Reference Equations:** - The document contains references to specific subsections (e.g., 3.1.2), indicating structured content about probability distributions. - **Key Significance:** - This context is likely educational or instructional, focusing on probability and statistical distributions, specifically the normal and Weibull distributions. ### Scene and Activity Analysis 1. **Scene Description:** - The scene is a structured document page with textual and mathematical content. - There are no visual elements apart from text and mathematical formulas. ### Diagram and Chart Analysis 1. **Net Content:** - No diagrams or charts are included within this image. The focus is entirely on explanatory text and formulas. ### Process Descriptions (Prozessbeschreibungen) 1. **Process Descriptions:** - The document explains the process of calculating probabilities using the normal and Weibull distributions. - **Normal Distribution Process:** - Describes how to derive the density function and cumulative function. - **Weibull Distribution Process:** - Details the generation of the Weibull distribution from the normal distribution, highlighting shifts in the distribution's mean and deviation. ### Metadata Analysis 1. **Metadata Review:** - No metadata is explicitly visible within the image, and therefore not analyzed. ### Trend and Interpretation 1. **Trends and Interpretations:** - Trend in focus on probability distributions highlighting the methods for density and cumulative function formulations for normal and Weibull distributions. - Educative emphasis on the properties and transformations necessary for statistical analyses. ### Tables 1. **Table Analysis:** - No tables are present in the image. In conclusion, the image is a page from an educational or scientific document discussing the normal and Weibull distributions in the context of probability theory. The detailed mathematical formulas are used to explain the calculation and transformation processes for these distributions. The primary focus is on theoretical understanding rather than practical application. #################### File: VW%2010130_CS.pdf Page: 6 Context: # Strana 6 VW 101 30: 2005-02 Obrázek 3 ukazuje funkce rozdělení pravděpodobnosti, která vyplyne ze složení hustoty normálního rozdělení při různých posunech nulového bodu. ![Obrázek 3 – Funkce hustoty Weibullova rozdělení s různými posuny nulového bodu](path/to/image) **Střední hodnota a rozptyl Weibullova rozdělení zná:** \[ \mu = \mu_H + \left( \frac{H_N}{\sigma_N} \right) - \frac{2 - \sigma_N}{\sqrt{2\pi}} \] (1.9) \[ \sigma^2 = H_N - \mu^2 \] (1.10) Pro případ nulového bodu \(\mu_N = 0\) vyplyne z (1.9) a (1.10): \[ \mu = -\frac{2 - \sigma_N}{\sqrt{2\pi}} \] (1.11) \[ \sigma^2 = \left( 1 - \frac{2}{\sigma_N} \right) \] (1.12) Jak ukazuje obrázek 3, blíží se Weibullovo rozdělení s rostoucím posunem nulového bodu normálnímu rozdělení. Tak lze pro případ: \[ \frac{\mu}{\sigma} \approx 0 \] (1.13) Weibullovo rozdělení dobře aproximálně nahrazuje normálním rozdělením. Image Analysis: ### Comprehensive Examination of the Visual Content #### 1. Localization and Attribution - **Image Position**: The analyzed visualization, which contains a graph and related mathematical formulas, is centrally located on the page. - **Image Number**: Image 1. #### 2. Object Detection and Classification - **Graph**: Present, labeled "Obrázek 3 - Funkce hustoty Weibullova rozdělení s různými posuny nulového bodu." - **Mathematical Formulas**: Displayed below the graph with sequential numbering. #### 3. Scene and Activity Analysis - **Actors**: No human actors present. - **Activities**: The page primarily involves the examination and explanation of statistical distributions. #### 4. Text Analysis - **Detected Text**: The text is in Czech. Key text includes: - Title: "Obrázek 3 - Funkce hustoty Weibullova rozdělení s různými posuny nulového bodu." - Additional Descriptions: Explanations of mathematical formulas and their notation. - **Content Analysis**: The text is critical for understanding how the Weibull distribution function changes with different zero point shifts. #### 5. Diagram and Chart Analysis - **Graph Analysis**: - **Axes**: - **X-Axis**: "Hodnota charakteristiky" (translated: Characteristic Value) - **Y-Axis**: "Hustota pravděpodobnosti" (translated: Probability Density) - **Trends**: Multiple curves represent Weibull distributions with different zero point shifts. As the shift increases (indicated as \( μ_N \)), the curves diverge and intersect at various points. #### 7. Anomaly Detection - **Possible Anomalies**: No apparent anomalies or unusual elements. The presentation appears standard and consistent with scientific formats. #### 8. Color Analysis - **Color Composition**: Predominantly black and white, with distinct black curves on a white background. This high contrast aids in clarity and comprehension. #### 9. Perspective and Composition - **Perspective**: The image is a frontal view, common for graphs. - **Composition**: Top to bottom flow; the graph at the top is followed by descriptive mathematical explanations. #### 10. Contextual Significance - **Document Context**: The document seems to be a technical or academic piece addressing statistical distributions, likely for educational or research purposes. - **Contribution to Overall Message**: The image and accompanying explanations demonstrate the behavior and calculation of Weibull distribution, especially under varied conditions. This contributes significantly to mathematical or statistical analysis. #### 12. Graph and Trend Analysis - **Analysis of Trends**: - **Data Points**: While specific numeric data points aren't noted on the curves, the intersecting lines and the gradual changes in the curves denote how shifts in the zero point (\( μ_N \)) affect the Weibull distribution shapes. - **Interpretation**: As indicated, the Weibull distribution can approximate normal distribution under certain shifts of the zero point. ### Conclusion The provided image is a detailed graphical and mathematical analysis of the Weibull distribution, specifically examining how shifts in the zero point affect the distribution's density function. The clean presentation, logical flow, and detailed mathematical annotations provide a comprehensive understanding of the distribution's behavior, making it valuable for those studying statistical distributions. #################### File: VW%2010130_CS.pdf Page: 7 Context: # 3.1.3 Rayleighovo rozdělení Rayleighovo rozdělení vyplývá z vektorových hodnot ortogonálních komponent x a y dvourozměrného normálního rozdělení, přičemž pro komponenty jsou předpokládány stejné standardní odchylky. Tento případ nastává u mnoha výrobních charakteristik ve formě radiálních odchylek r od sledovaného bodu nebo sledované osy. ## Funkce hustoty a funkce rozdělení Rayleighova rozdělení obecně zní \[ f_{2}(r) = \frac{1}{2 \pi \sigma_{d}^{2}} e^{-\frac{r^{2}}{2\sigma_{d}^{2}}} \quad \text{pro } r \geq 0 \] (1.14) \[ F_{2}(r) = \int_{0}^{r} f_{2}(t) \, dt = 1 - e^{-\frac{r^{2}}{2\sigma_{d}^{2}}} \] (1.15) přitom: - \(\sigma_{d}\): Standardní odchylka ortogonální složky x a y, ze které vyplývá radiální odchylka r od referenčního bodu nebo od referenční osy - \(z\): Excentricita: Vzdálenost mezi počátkem soustavy souřadnic a středem čtverce Obrázek 4 ukazuje funkce rozdělení pravděpodobnosti Rayleighova rozdělení, které vyplývají z různých excentricit v jednotkách \(\sigma_{d}\). ![Obrázek 4 – Funkce hustoty Rayleighova rozdělení s různými excentricitami](image_link) Střední hodnota a rozptyl Rayleighova rozdělení zní. Image Analysis: ### Image Analysis #### 1. Localization and Attribution: - **Image Position**: The page contains a single image located at the bottom part of the document. - **Image Number**: Image 1. #### 2. Object Detection and Classification: - **Objects Identified**: The image includes a chart or graph. - **Category**: Data visualization. #### 3. Scene and Activity Analysis: - **Scene Description**: The image is of a graph illustrating the probability density functions of Rayleigh distributions with various eccentricities. #### 4. Text Analysis: - **Text Detected**: - "3.1.3 Rayleighovo rozdělení" - "Rayleighovo rozdělení vyplyne z vektorových hodnot ortogonálních komponent x a y dvourozměrného normálního rozdělení, přičemž pro komponenty jsou předpokládány stejné standardní odchylky. Tento případ nastává u mnoha výrobních charakteristik ve formě radiálních odchylek r od sledovaného bodu nebo sledované osy." - "Funkce hustoty a funkce rozdělení Rayleighova rozdělení obecně zní" - Various mathematical formulas and constructs. - "Obrázek 4 ukazuje funke rozdělení pravděpodobnosti Rayleighova rozdělení, které vyplynou z různých excentricit v jednotkách σN." - **Text in Graph**: - "Hustota pravděpodobnosti" - "Hodnota charakteristiky" - Markings on the graph: Z=0, Z=1σN, Z=2σN, Z=3σN - "Obrázek 4 - Funkce hustoty Rayleighova rozdělení s různými excentricitami" - "Střední hodnota a rozptyl Rayleighova rozdělení zní" #### 5. Diagram and Chart Analysis: - **Chart Analysis**: - **Axes**: - X-axis: "Hodnota charakteristiky" (Characteristic Value). - Y-axis: "Hustota pravděpodobnosti" (Probability Density). - **Features**: - Multiple overlaid probability density curves are shown for different eccentricities, indicated by Z=0, Z=1σN, Z=2σN, and Z=3σN. - The chart illustrates how the shape of the Rayleigh distribution varies with changes in eccentricity. #### 8. Color Analysis: - **Color Composition**: The image appears to be in grayscale, with different shades used to differentiate the various curves in the graph. - **Dominant Colors**: Shades of black and gray. #### 9. Perspective and Composition: - **Perspective**: The image is a standard two-dimensional chart view, looking directly at the graph. - **Composition**: The graph is centered at the bottom of the page with clear X and Y axes and labeled curves, making it easy to interpret. #### 10. Contextual Significance: - **Contribution**: This graph is critical for understanding the properties and effects of varying eccentricities on Rayleigh distribution. It supports the textual explanation provided above it and demonstrates the practical application of the theoretical concepts discussed in the document. #### 13. Graph Numbers: - **Data Point Description**: Not explicitly provided, but the curves demonstrate typical behavior expected in Rayleigh distributions: as eccentricity increases, the peak of the probability density decreases and shifts. ### Summary: Image 1 presents a detailed graph depicting the Rayleigh distributions for different eccentricities, enhancing the understanding of related statistical concepts. The text above the graph explains the theoretical background and mathematical foundations, while the graph itself illustrates the practical impact of changing eccentricity values on Rayleigh distribution. The clear, grayscale image effectively communicates complex statistical information in an accessible visual format. #################### File: VW%2010130_CS.pdf Page: 8 Context: # Strana 8 VW 101 30: 2005-02 \[ \mu = \int_{\Gamma} \frac{\partial z}{\partial r} \, dr \tag{1.16} \] \[ \sigma^2 = 2 \alpha z^2 + \mu^2 \tag{1.17} \] Pro případ excentricity \( z = 0 \) vyplývá z (1.14) a (1.15) funkce hustoty a distribuční funkce Weibullova rozdělení s hodnotou parametru tvaru 2: \[ f_{\beta} = \frac{2}{\sigma} \left( \frac{z}{\sigma} \right)^{\beta - 1} e^{-\left( \frac{z}{\sigma} \right)^{\beta}} \tag{1.18} \] \[ F_{\beta}(z) = 1 - e^{-\left( \frac{z}{\sigma} \right)^{\beta}} \tag{1.19} \] a z toho opět střední hodnot a rozptyl \[ \mu = \sigma \left( \frac{\Gamma(1 + 1/\beta)}{\Gamma(1 + 2/\beta)} \right) \tag{1.20} \] \[ \sigma^2 = \sigma^2 \left( \frac{\Gamma(1 + 2/\beta)}{\Gamma(1 + 2/\beta)} - \left( \frac{\Gamma(1 + 1/\beta)}{\Gamma(1 + 2/\beta)} \right)^2 \right) \tag{1.21} \] Rayleighovo rozdělení dobrou aproximaci nahradit normálním rozdělením: \[ \mu = \sigma \sqrt{\frac{\pi}{2}} \tag{1.22} \] ## 3.2 Zjištění způsobilosti Charakteristiky způsobilosti \( c_m \) a \( c_k \) udávají, jak dobře dodržují výrobní výsledky toleranční interval sledované charakteristiky. Pritom je hodnota \( c_n \) zohledněna pouze rozptyl výroby. Poloha výrobky je zohledněna hodnotou \( c_k \). Tím lze na jedné straně vyjádřit, jaká hodnota je při ideální poloze výrobky možná, a na druhé straně lze porovnávat obě hodnoty, jak silné se poloha výrobky vychyluje od požadované hodnoty. Čím větší jsou zjištěné charakteristiky způsobilosti, tím lepší je výroba. Pro zjištění charakteristik způsobilosti existují různé vyhodnocovací vzorce, které je nutno zvolit podle jednotlivého případu. Protože však charakteristiky způsobilosti poskytuje pouze hodnocení hledaných hodnot základního rozdělení, představují pouze odhady hledaných hodnot. Image Analysis: ### Comprehensive Analysis of the Visual Content #### 1. Localization and Attribution: - **Image 1**: - Entire content depicted is a single page, considered as Image 1 for analysis. #### 2. Object Detection and Classification: - **Image 1**: - Key objects: - Mathematical symbols and equations - Text paragraphs - Footnotes or references - Detected objects and their classification: - Equations: \( \mu = \int_{-\infty}^{\infty} r\, f_{R} (r)\, dr \) (1.16) - Text paragraphs in the Czech language. #### 3. Scene and Activity Analysis: - **Image 1**: - The scene represents a technical or academic document, likely a standard or technical report. - The activities involved are passive reading and comprehension activities. #### 4. Text Analysis: - **Image 1**: - Detected text and significance: - Title at the top: "Strana 8" (Page 8) - Document identifier: "VW 101 30: 2005-02" - Sections: - Equations defining various mathematical functions and parameters, focusing on statistical distributions (Weibull distribution, Rayleigh distribution). - Explanation of derivations (equations 1.16 to 1.22) - Section 3.2 titled "Zjištění způsobnosti" (Determination of capacity/competence), discussing parameters for evaluating manufacturing tolerance intervals and their relevance in production. #### 9. Perspective and Composition: - **Image 1**: - The perspective is a direct top-down view, typical for document viewing. - Composition includes mathematical formulas on the top, followed by a descriptive text section. #### 12. Graph and Trend Analysis: - **Image 1**: - While there aren’t explicit graphs, the trends in the equations suggest standard probabilistic functions and statistical distributions. #### 13. Graph Numbers: - **Image 1**: - Equations numbered from (1.16) to (1.22) - each detailing a step in the derivation or formula. **Additional Aspects:** - **Ablaufprozesse (Process Flows):** - Mention of characterization processes in section 3.2 involving \( c_m \) and \( c_{mk} \) parameters. - **Prozessbeschreibungen (Process Descriptions):** - Descriptive process for evaluating production outcomes based on defined statistical tolerances. ### Summary of Key Insights: The image analyzed is a technical or academic document related to statistical evaluation methods in production. It includes a series of mathematical equations that define statistical distributions (Weibull and Rayleigh) and describes a methodology for assessing production capability through tolerance intervals. The text analysis reveals a precise approach to quality control and assurance in manufacturing settings. The overall composition helps in understanding the context of the mathematical derivations, contributing to the document's aim of establishing standard statistical methods in manufacturing processes. #################### File: VW%2010130_CS.pdf Page: 9 Context: # 3.2.1 Zjištění způsobilosti u definovaných distribučních modelů ## 3.2.1.1 Charakteristiky způsobilosti Pro prověřování výrobní charakteristiky, jejíž namátkové vzorky nejsou v rozporu s teoreticky očekávaným distribučním modelem, jsou charakteristiky způsobilosti odhadovány podle příslušného případu (viz také příklady 1 a 2 v oddílu 5) podle následujících vzorců: Charakteristiky způsobilosti pro oboustranně tolerovanou charakteristiku (podle DIN 56319, metoda M4), např. pro délkovou míru: \[ \hat{c}_{m} = \frac{G_u - G_l}{X_{0.95} - X_{0.135}} \] Charakteristiky způsobilosti pro jednoduše nahoře tolerovanou charakteristiku s přirozenou dolní mentní hodnotou rovnou nule, např. radiální házení: \[ \hat{c}_{m} = \frac{G_u - \mu}{X_{0.995} - X_{0.135}} \] Charakteristika způsobilosti pro jednoduše dole tolerovanou charakteristiku, např. pro pevnost v tahu: \[ \hat{c}_{m} = \frac{\mu - G_l}{\mu - X_{0.135}} \] přičemž: - \(G_u, G_l\): maximální rozměr, popř. minimální rozměr - \(\mu\): odhadovaná střední hodnota - \(X_{0.135}, X_{0.995}\): odhadované hodnoty pro hranice intervalu spolehlivosti (kvantily, pod nimiž leží uvedený podíl p naměřených hodnot) Image Analysis: ### Analysis of the Attached Visual Content #### 1. **Localization and Attribution** - **Image 1**: Single image provided. #### 4. **Text Analysis** - **Image 1**: The image contains textual content in Czech that relates to statistical characteristics for evaluating the capability of manufacturing processes with respect to a theoretical distribution model. It includes formulas and explanations for various capability indices. Key points from the text include: - **Section Title**: "Zjistění způsobilosti u definovaných distribučních modelů" (Determination of Capability for Defined Distribution Models). - **Subsection Title**: "Charakteristiky způsobilosti" (Capability Characteristics). - Descriptions of different capability indices and relevant formulas. - Explanation of symbols used in the formulas at the bottom. #### 5. **Diagram and Chart Analysis** - There are no diagrams or charts present in the image. #### 12. **Graph and Trend Analysis** - No graphs are present in the image. #### 13. **Graph Numbers** - Not applicable as there are no graphs present in the image. #### **Additional Aspects** - **Ablaufprozesse (Process Flows)** - No process flows depicted in the image. - **Prozessbeschreibungen (Process Descriptions)** - The text provides descriptions of processes for estimating capability indices. - **Typen Bezeichnung (Type Designations)** - Types of capability indices are described through formulas (e.g., \( \hat{c}_{mk} \)). - **Trend and Interpretation** - The image contains detailed statistical formulas and descriptions for various capability indices. The general trend is an analytical one focusing on the precise quantification and evaluation of manufacturing characteristics relative to distribution model expectations. - **Tables** - No tables are present in the image. ### Detailed Descriptions 1. **Localization and Attribution** - **Image 1**: The entire page is an image located as a single page document. 2. **Object Detection and Classification** - **Image 1**: The primary objects are textual elements comprising paragraphs, formulas, and explanatory notes. 3. **Scene and Activity Analysis** - **Image 1**: The image represents a textual document page, likely from an academic or technical manual on quality control and statistical analysis of manufacturing processes. 4. **Perspective and Composition** - **Image 1**: The image is a scanned page taken from a direct, flat perspective. The composition is structured in a traditional academic format with section headings, formulas, and explanatory text. 5. **Color Analysis** - **Image 1**: The image is grayscale, typical for scanned academic documents. ### Conclusion The image provided is a page from a technical document detailing the statistical evaluation of manufacturing processes' capability indices. The section primarily consists of textual explanations and formulas with no diagrams, charts, or additional graphical elements. The text is in Czech and is aimed at providing precise definitions and calculations related to manufacturing process evaluation. #################### File: VW%2010130_CS.pdf Page: 10 Context: # 3.2.1.2 Odhad statistických parametrů Statistické parametry střední hodnota \( \mu \) a smírodatná odchylka \( \sigma \) základního souboru lze nezávisle na distribučním modelu podle očekávání odhadnout z naměřených hodnot vzorku pomocí vzorců: \[ \mu = \frac{1}{n} \sum_{i=1}^{n} x_i \tag{2.6} \] \[ \sigma^2 = \frac{1}{n - 1} \sum_{i=1}^{n} (x_i - \bar{x})^2 \tag{2.7} \] přičemž: - \( n_p = n_e - n_a \): efektivní rozsah namátkové zkoušky - \( n_a \): zvolený rozsah namátkové zkoušky - \( n = \): počet odlehlých hodnot - \( \hat{\theta} \): i-tá hodnota parametru V případě vyhodnocovaných dat ve formě rozdělení četností tříděných naměřených hodnot, např. v rozčlenění za oblastí jako formy čárek v rozdělení tříd rozsahu hodnot (statistika četností) lze odhadnout parametry \( \mu \) a \( \sigma \) pomocí vzorce: \[ \hat{\mu} = \frac{1}{n} \sum_{k=1}^{K} f_k \cdot x_k \tag{2.9} \] \[ \sigma = \sqrt{\frac{1}{n} \sum_{k=1}^{K} f_k \cdot (x_k - \bar{x})^2} \tag{2.10} \] přičemž: - \( x_k \): střední hodnota k-té třídy - \( f_k \): absolutní četnost naměřených hodnot v k-té třídě (bez mimořádných hodnot) - \( K \): maximální počet naměřených hodnot ## 3.2.1.3 Odhad hranic intervalu spolehlivosti Hranice intervalu spolehlivosti závisí na distribučním modelu a odhadují se následujícím způsobem: ### Hranice intervalu spolehlivosti normálního rozdělení: V případě normálního rozdělení jako vhodného distribučního modelu vyplněnou hodnot zjištěných podle (2.6) a (2.7) popř. (2.9) a (2.10) jako \( \hat{\mu} \) a \( \hat{\sigma} \) pro oblast intervalu spolehlivosti: \[ \hat{I} = \hat{\mu} \pm z_{\alpha/2} \cdot \hat{\sigma} \tag{2.11} \] které opět po dosazení do vzorců (2.1) a (2.2) dají klasické vzorce pro výpočet charakteristik způsobilosti (viz také příklad 1 v oddílu 5). Image Analysis: ### Analysis of Visual Content #### 1. Localization and Attribution - This visual content contains a single page consisting mainly of text and mathematical notations. For the purpose of this analysis, it will be referred to as **Image 1**. #### 4. Text Analysis - **Title and Section Numbers:** - The page begins with "Strana 10", which means "Page 10" in Czech. - Standard reference: "VW 101 30: 2005-02". - Section "3.2.1.2 Odhad statistických parametrů" translates to "Estimation of Statistical Parameters". - **Content Description:** - **Subsection (Statistical Parameters):** - Talks about the mean value (μ) and standard deviation (σ) of a sample. - Equations (2.6) describe the computation of the mean: - \(\hat{μ} = \frac{1}{n_e} \sum_{i=1}^{n_e} x_i\) - Equation (2.7) describes the computation of the standard deviation: - \(\hat{σ}^2 = \frac{1}{n_e - 1} \sum_{i=1}^{n_e} (x_i - \bar{x})^2\) - **Explanation of Terms (Equations and Variables):** - \(n_e\): Effective sample size. - \(n_a\): Chosen sample size. - \(n_o\): Number of outliers. - \(x_i\): i-th observed value. - **Distribution of Frequency Data:** - Equations (2.9) and (2.10) provide methods to estimate parameters with frequency data. - **Interval Estimates (Confidence Interval):** - Section "3.2.1.3 Odhad hranic intervalu spolehlivosti" translates to "Estimation of Confidence Interval Limits". - Equation (2.11) defines boundary estimation using standard deviation: - \(x_{1-α/2} = \hat{x} \pm 3\hat{\sigma}\), assuming a normal distribution. #### 6. Product Analysis - N/A (The page contains no relevant product imagery or descriptions). #### 9. Perspective and Composition - **Perspective:** - The perspective of the image is a straightforward, flat view of a document page, conducive to reading. - **Composition:** - Text is composed in a traditional structured manner, common in technical or scientific documents. - Equations are interspersed within the text, formatted clearly for comprehension. #### 12. Graph and Trend Analysis - N/A (The page contains no graphical plots or trends). #### 13. Graph Numbers - N/A (The page does not contain graphs with data rows). #### Contextual Significance - The page appears to be part of a technical or academic document, specifically focusing on statistical analysis and estimation methods. The context implies it is likely part of a standardized instruction or educational material, possibly related to an engineering or scientific field. - The inclusion of mathematical equations and the focus on statistical parameters suggest the intended audience is individuals with a foundational understanding of statistics. Overall, the detailed text analysis suggests that the document is instructional or explanatory in nature, intended for readers who are learning about or applying statistical methodologies. #################### File: VW%2010130_CS.pdf Page: 11 Context: # Hranice intervalu spolehlivosti Weibullova rozdělení Pro zjištění hranic intervalu spolehlivosti pro Weibullova rozdělení se nejprve podle vzorce (2.6) a (2.7), popř. (2.9) a (2.10) odhadnou veličiny \(\eta\) a \(\sigma\). Pro případ, že \(2 < \frac{\mu}{\sigma} < 3\) se pak z odhadnutých veličin \(\eta\) a \(\sigma\) způsobem odhadu hledají hodnoty parametrů \(\mu_N\) a \(\sigma_N\) příslušného Weibullova rozdělení: Z rovnice (1.9) získáme funkci \[ \frac{\bar{\mu}}{\sigma} = \frac{\left( \frac{\partial \bar{\mu}}{\partial \eta} \right) }{\left( \frac{\partial \bar{\mu}}{\partial \sigma} \right)} + 2 \cdot \frac{\eta}{\sigma} \cdot \frac{e^{-\frac{\eta}{\sigma}}}{\sqrt{2\pi}} \cdot \frac{\partial L}{\partial \sigma} \tag{2.12} \] Pomocí rovnice (1.10) z toho vyplývá funkce \[ \mu = \psi \cdot \left( \frac{\bar{\mu}}{\sigma} \right) \tag{2.13} \] Z rovnic (1.11) a (1.12) vyplývá podmínka \[ \frac{\bar{\mu}}{\sigma} = \frac{\sqrt{2}}{ \sqrt{\pi - 2}} = 1.3236 \tag{2.14} \] Hledané hodnoty parametrů Weibullova rozdělení tak lze za podmínek (2.14) odhadnout pomocí \[ \sigma_N = \left( 1 + \left( \frac{\bar{g}}{\eta} \right)^2 \right) \cdot \left( \frac{\bar{\psi}}{\eta} \right)^2 \tag{2.15} \] \[ \mu_N = \bar{\alpha} \left( \frac{\bar{g}}{\eta} \right) - \delta_N \tag{2.16} \] přičemž \[ \bar{g} = \text{inverzní funkce } k \tag{2.17} \] Pro případ, že by poměr \(\mu / \sigma\) na základě náhodných odchylek parametrů vzorků byl menší než mezní hodnota 1.3236 z podmínky (2.14), je poměr \(\mu / \sigma\) nastaven na tuto mezní hodnotu, při které vyplynou následující hodnoty parametrů: \[ \mu_N = 0 \text{ podle vzorce (1.12)} \] \[ \sigma_N = \sqrt{\frac{\pi}{\pi - 2}} \cdot 1.659 \cdot \hat{g} \tag{2.17} \] Image Analysis: ### Comprehensive Examination of the Visual Content: #### 1. **Localization and Attribution:** - Only one page/image is present. - Thus, this is **Image 1**. #### 2. **Object Detection and Classification:** - The primary objects detected in the image are as follows: - **Text**: Primarily in the Czech language, with various mathematical equations. - **Mathematical Notations**: Numerous equations and variables related to the Weibull distribution. #### 4. **Text Analysis:** - **Detected Text (in Czech):** - Title: "Hranice intervalu spolehlivosti Weibullova rozdělení" - Description of methodology for deriving confidence intervals for the Weibull distribution. Reference to equations and conditions for calculating μ̂ and σ̂. - Equations (e.g., equations 2.12, 2.13, 2.14, etc.) are outlined throughout the text. - Mention of parameters: μ̂, σ̂, ψ, θ, ξ, k, and specific constants. - Application of the method for different cases, including references to formulas 2.15 and 2.17. - **Content Analysis and Significance:** - The text details the process of determining confidence intervals for the Weibull distribution. - Equations provided in the text, along with their conditions and necessary adjustments, are vital for statistical calculations related to reliability engineering and life data analysis. - The significant constants and functions derived play a crucial role in achieving accurate estimation. #### 8. **Color Analysis:** - The entire page is monochrome (black text on white background). - Dominant colors: Black and white. - Impact: Monochrome setup ensures clarity and focus on mathematical content without distractions. #### 9. **Perspective and Composition:** - **Perspective:** - Straight-on view of the text and equations, similar to an academic paper. - **Composition:** - Structured and organized with sections, equations, and explanatory text. Equations are referenced and numbered systematically. - Uses mathematical notation standards, ensuring clarity for readers familiar with the subject matter. #### 11. **Metadata Analysis:** - **Metadata present on the page:** - "Strana 11" (Page 11) - Document identifier: "VW 101 30: 2005-02" - **Contribution to Image Analysis:** - These metadata elements indicate that this is part of a larger document, likely a technical paper or a standard reference document dated February 2005. #### 12. **Graph and Trend Analysis:** - Although no explicit graphs are visible, the series of equations and their dependencies could represent trends in the data if plotted. - Interpretation of equations and relationships between variables can direct trends in reliability and quality metrics calculated from the Weibull distribution. ### Additional Aspects: #### **Process Descriptions (Prozessbeschreibungen):** - Detailed steps are described for deriving confidence intervals of the Weibull distribution. This includes: - Use of initial equations. - Manipulations to reach simplified forms. - Final conditions for variables. #### **Typen Bezeichnung (Type Designations):** - Various types of functions and variables such as: - Inverse function "ξ"} - Functions "ψ" and "θ". - Conditional variance "σ̂" #### **Trend and Interpretation:** - Trends in the equations provided indicate a relationship between the mean and variance of the Weibull distribution under different conditions. This is significant for reliability analysis, helping in maintenance planning and lifespan estimation. #### **Tables:** - There are no explicit tables in the image. ### Summary: The page provides a detailed explanation and mathematical derivations for calculating confidence intervals for the Weibull distribution. It uses a systematic approach with labeled equations and clear methodological steps. This is crucial for statistical analyses in fields such as reliability engineering. The metadata indicates this is part of a larger technical document. #################### File: VW%2010130_CS.pdf Page: 12 Context: # Strana 12 VW 101 30: 2005-02 Souvislost mezi hodnotami parametrů \( \lambda_N \) a \( \sigma_W \) Weibullova rozdělení a statistických veličin \( \mu \) a \( c \) je graficky znázorněno na obrázku 5 vztaženo na \( c \). ![Obrázek 5 – Relativní poloha parametrů Weibullova rozdělení v závislosti na relativní poloze](obrazek5.png) Pro přizpůsobené Weibullovo rozdělení lze pak čísleně zjistit hranice intervalů spolehlivosti, jejichž závislost na relativní poloze je znázorněna v obrázku 6. ![Obrázek 6 – Relativní hranice intervalů spolehlivosti Weibullova rozdělení v závislosti na relativní poloze](obrazek6.png) Image Analysis: ### Localization and Attribution 1. **Image 1:** - Position: Top of the page - Description: Chart showing relative position of Weibull distribution parameters. 2. **Image 2:** - Position: Bottom of the page - Description: Chart illustrating the relative confidence interval boundaries of the Weibull distribution. ### Object Detection and Classification #### Image 1: - **Objects:** - Graph. - Axes (X and Y). - Curves. #### Image 2: - **Objects:** - Graph. - Axes (X and Y). - Curve. ### Scene and Activity Analysis: #### Image 1: - **Scene Description:** - The image shows a line graph that represents the relationship between relative position and relative parameter values of the Weibull distribution. - **Activities:** - Analysis of the relationship between different statistical parameters in Weibull distribution. #### Image 2: - **Scene Description:** - The image displays a graph that shows the relative confidence interval boundaries as a function of relative position for a Weibull distribution. - **Activities:** - Analysis of the confidence interval's behavior with changes in relative position. ### Text Analysis: - **Image 1 Text:** - Graph Title: "Obrázek 5 – Relativní poloha parametrů Weibullova rozdělení v závislosti na relativní poloze" - Axis Labels: - X-axis: "relativní poloha μ/σ" - Y-axis: "relativní distribuiční parametr" - Other Text: "μ_N / σ", "σ_N / μ" - **Significance:** - The graph demonstrates how the Weibull distribution parameters change with the relative position. - **Image 2 Text:** - Graph Title: "Obrázek 6 – Relativní hranice intervalu spolehlivosti Weibullova rozdělení v závislosti na relativní poloze" - Axis Labels: - X-axis: "relativní poloha μ/σ" - Y-axis: "relativní hranice intervalu spolehlivosti" - Other Text: "X_99.865% / σ", "X_0.135% / σ" - **Significance:** - The graph illustrates how the confidence intervals' limits change with the relative position in a Weibull distribution. ### Diagram and Chart Analysis: #### Image 1: - **Axes and Scales:** - X-axis: Relative position (μ/σ) ranging approximately from 1.2 to 3.0. - Y-axis: Relative distribution parameter, ranging from 0 to 2.5. - **Curves:** - There are multiple curves indicating different parameter relationships. #### Image 2: - **Axes and Scales:** - X-axis: Relative position (μ/σ) ranging from approximately 1.2 to 3.0. - Y-axis: Relative confidence interval boundary, ranging from 0 to 7. - **Curve:** - There is a single curve indicating the boundary of the confidence interval. ### Trend and Interpretation: #### Image 1: - **Trend:** - The distribution parameters increase with the relative position. #### Image 2: - **Trend:** - The confidence interval boundaries show a slight increase as the relative position increases. ### Contextual Significance: - **Overall Theme:** - The images contribute to the understanding of how Weibull distribution parameters and confidence intervals vary with changes in relative position. This information is useful in reliability engineering and statistical analysis for understanding the behavior of materials or systems described by the Weibull distribution. ### Graph and Trend Analysis: #### Image 1: - The plotted curves show different relationships between Weibull distribution parameters and their relative positions, indicating how these parameters interact with one another under different circumstances. #### Image 2: - The graph shows the change in the boundaries of confidence intervals for the Weibull distribution as the relative position varies, which is crucial for assessing the reliability with a certain confidence level. #################### File: VW%2010130_CS.pdf Page: 13 Context: Pro primé zjištění charakteristik \(\mu_N\) a \(\sigma\) z charakteristik \(\mu\) a \(\sigma\) pro \(1.3236 < \frac{\sigma}{\mu} < 3\) s dostatečnou přesností použít následující aproximaci jako inverzní funkci vztahu (2.13) (chyba vztažena na \(\sigma\) méně než 0,1): \[ \frac{\sigma}{\mu} = 1.604 \left( \frac{a}{1.3236} \right) + 0.634 \left( \frac{a}{1.3236} \right)^2 \] Navíc může být zjištěn hranic intervalů spolehlivosti pro \(1.3236 < \frac{\sigma}{\mu} < 3\) provedením pomoci následující aproximace (chyba vztažena na \(\sigma\) je menší než 0,02): \[ \begin{aligned} & \frac{Z_{0.05}}{ \sqrt{n}} \left( \frac{a}{1.3236} \right) = 1.321 \\ & \frac{R}{\sqrt{n}} \left( \frac{a}{1.3236} \right) = \text{(další výraz)} \end{aligned} \] Pro \(\frac{I}{\sigma < 3}\) se vypočet hranic intervalů spolehlivosti provedlo podle 2.11. ## Hranice intervalu spolehlivosti Rayleighova rozdělení: Pro zjištění hranic spolehlivosti pro Rayleighovo rozdělení (viz také příklad 2 v oddílu 5) se nejprve podívejte vzorce (2.6) a (2.7), popřípadě (2.9) a (2.10) odhadnouvací veličiny \(\mu\) a \(\sigma\). Pro případ, že \(\frac{I}{\sigma} < 6\) se pak z odhadnutých veličin \(\mu\) a \(\sigma\) následujícím způsobem zjistí hledané hodnoty parametru \(z\) pro přizpůsobeného Rayleighova rozdělení: Z rovnic (1.14) a (1.16) získáme funkci: \[ \frac{d \mu}{d N} = \frac{B^2}{\left( \frac{d \sigma}{d N} \right)} \cdot \frac{d}{dz} \left( e^{-z^2 / 2} \right) \left( v_0 \cdot e^{z} \cdot \left( \int_0^{\infty} e^{-z^2} \, dz \right) \right) \] přičemž \[ v = \frac{r}{d N} \] Pomocí rovnice (1.17) z toho vyplývá funkce: \[ \frac{d \sigma}{d N} = -2 \left( \frac{z}{d}{\sigma - \left( \frac{v^2}{d \sigma} \right)} \right) \] Z rovnic (1.20) a (1.21) vyplývá podmínka: \[ \frac{\mu}{\sigma} = \frac{\pi}{4 - \pi} = 1.9131 \] Image Analysis: ### Comprehensive Examination of the Provided Visual Content #### **Localization and Attribution:** - The provided content consists of a single page with textual and mathematical content. #### **Object Detection and Classification:** - **Image 1**: This image contains several mathematical equations and explanatory text in a structured format. - **Objects Detected:** - Text paragraphs - Mathematical symbols and equations #### **Scene and Activity Analysis:** - **Image 1**: - **Scene Description:** The image displays a page from what appears to be a technical or academic document. The content is written in a structured manner with several paragraphs, equations, and figures. - **Activities:** The main activity involves the presentation of mathematical derivations, approximations, and equations used to describe specific characteristics and intervals in a statistical or scientific context. #### **Text Analysis:** - **Image 1**: - **Detected Text:** - The text is in Czech. - It includes headings like "Hraniční interval spolehlivosti Rayleighova rozdělení" which translates to "Rayleigh Distribution Confidence Interval." - Other notable phrases include "Pro přímé zjištění charakteristik" translating to "For direct determination of characteristics". - **Text Significance:** - The text serves to explain the mathematical derivations and approximations used for determining characteristics in the context of the Rayleigh distribution. #### **Diagram and Chart Analysis:** - **Image 1**: - There are no diagrams or charts to analyze. #### **Product Analysis:** - **Image 1**: - There are no products depicted in this image. #### **Anomaly Detection:** - **Image 1**: - No noticeable anomalies or unusual elements are present. The page appears to be a standard academic or technical document. #### **Color Analysis:** - **Image 1**: - The image is in grayscale. The dominant colors are black (for text and symbols) and white (background). This has a neutral impact and facilitates readability. #### **Perspective and Composition:** - **Image 1**: - **Perspective:** The image is taken from a front-facing view, showing the entire page clearly. - **Composition:** The content is well-organized, with equations and text clearly separated. Headings and subheadings are used to break down the information. #### **Contextual Significance:** - **Image 1**: - This image seems to be a page from a statistical or mathematical academic document. It contributes to the overall message by providing detailed mathematical explanations and derivations pertinent to the document's subject. #### **Metadata Analysis:** - **Image 1**: - There is no accessible metadata to analyze. #### **Graph and Trend Analysis:** - **Image 1**: - No graphs are present in this image. #### **Trend and Interpretation:** - **Image 1**: - The image mostly focuses on providing mathematical formulas and explanations without exhibiting any discernible trends. #### **Tables:** - **Image 1**: - No tables are provided in this image. #### **Ablaufprozesse (Process Flows):** - **Image 1**: - No process flows are depicted. #### **Prozessbeschreibungen (Process Descriptions):** - **Image 1**: - The image describes processes for calculating reliable intervals using Rayleigh distribution, but no step-by-step processes or workflows are visually depicted. #### **Typen Bezeichnung (Type Designations):** - **Image 1**: - The content includes type designations for various mathematical terms and variables in the context of Rayleigh distribution and interval reliability. --- This comprehensive analysis covers the significant aspects of the provided image, focusing on its academic and technical content. #################### File: VW%2010130_CS.pdf Page: 14 Context: # Strana 14 VW 101 30: 2005-02 Hledané hodnoty parametrů Rayleighova rozdělení tak lze za podmínek (2.23) odhadnout pomocí: \[ \sigma_N = \sqrt{ \left( 1 + \left( \frac{\mu}{\sigma} \right)^2 \right) \frac{(1 + \frac{1}{\sqrt{2}})^2}{2} } \; \sigma \; \] (2.24) \[ \hat{z} = \frac{\xi_{2}}{2} + \sigma_N \] (2.25) při čemž \[ \xi_{2} = \text{inverse Funktion von (2.22)} \] Pro případ, že by poměr \(\frac{\mu}{\sigma}\) na základě náhodných odchylek parametrů vzorků byl menší než mezí hodnota 1.9131 z podmínek (2.23), je poměr \(\frac{\mu}{\sigma}\) nastaven na tuto mezí hodnotu, při které vyplývá následující hodnoty parametrů: \[ \hat{z} = 0 \; podle vzorce \; (1.21) \] (2.26) Souvislost mezi hodnotami parametrů \(\sigma_N\) a \(\sigma\) Rayleighova rozdělení a statistických veličin \(\mu\) a \(\sigma\) je graficky znázorněna na obrázku 7, vztaženo k \(\alpha\). ## Obrázek 7 - Relativní poloha parametrů Rayleighova rozdělení v závislosti na relativní poloze | relativní poloha \(\mu/\sigma\) | relativní distribučí parametry | |----------------------------------|----------------------------------| | 1.5 | 0 | | 2 | 1 | | 2.5 | 3 | | 3 | 5 | | 5 | 7 | Image Analysis: 1. **Localization and Attribution:** - **Image 1:** Located at the top section of the page. This image contains mathematical equations and text explanations. - **Image 2:** Located below Image 1. This is a graph titled "Obrázek 7 – Relativní poloha parametrů Rayleighova rozdělení v závislosti na relativní poloze." 2. **Object Detection and Classification:** - **Image 1 Objects:** - Mathematical equations. - Descriptive text. - **Image 2 Objects:** - Graph with axes, scales, data points, and labels. 3. **Text Analysis:** - **Image 1 Text:** - The text includes mathematical formulas and equations related to the calculation of parameters in a statistical distribution (specifically, a Rayleigh distribution). - Descriptions and explanation of these formulas in the Czech language. - **Extracted Equations:** - \[ \hat{\sigma}_N = 1 + \frac{\hat{\mu}}{\hat{\sigma}} \] - \[ \hat{z} = 6_{82}(\hat{\sigma}) + \hat{\sigma}_N \] - \[ \hat{\sigma} = \sqrt{\frac{2}{4 - \pi}} . \hat{\sigma} = 1,526 . \hat{\sigma} \] - **Image 1 Text Content:** - The text explains the derivation and estimation of maximum likelihood parameters and their relationships, referencing specific equations. - **Extracted Passages:** - "Pro případ, že by poměr \(\hat{\mu}/\hat{\sigma}\)..." - "Souvislost mezi hodnotami parametrů... Rayleighova rozdělení a statistických veličin \(\mu\) a \(\sigma\)..." 4. **Diagram and Chart Analysis:** - **Image 2 Graph:** - The x-axis is labeled "relativní poloha μ/σ" (relative position μ/σ). - The y-axis is labeled "relativní distribuční parametr" (relative distribution parameter). - The graph includes two curves: one labeled "Z/σ" and the other "σ_N /σ". - **Axes and Scales:** - X-axis ranges from 1.5 to 6.0. - Y-axis ranges from 0 to 7. - **Key Insights:** - The graph visualizes the relationship between relative positions and distribution parameters in the context of a Rayleigh distribution, showing how parameters evolve with changes in μ/σ. 5. **Graph Numbers (Image 2):** - Data points for "Z/σ": - \( \mu/σ = 1.5 \rightarrow Z/σ \approx 0.5 \) - \( \mu/σ = 2.5 \rightarrow Z/σ \approx 1.0 \) - \( \mu/σ = 3.5 \rightarrow Z/σ \approx 2.7 \) - \( \mu/σ = 4.5 \rightarrow Z/σ \approx 4.5 \) - \( \mu/σ = 5.5 \rightarrow Z/σ \approx 5.8 \) - Data points for "σ_N /σ": - \( \mu/σ = 1.5 \rightarrow σ_N /σ \approx 1.5 \) - \( \mu/σ = 2.5 \rightarrow σ_N /σ \approx 1.8 \) - \( \mu/σ = 3.5 \rightarrow σ_N /σ \approx 2.0 \) - \( \mu/σ = 4.5 \rightarrow σ_N /σ \approx 2.03 \) - \( \mu/σ = 5.5 \rightarrow σ_N /σ \approx 2.1 \) #################### File: VW%2010130_CS.pdf Page: 15 Context: # Pro přizpůsobené Rayleighovo rozdělení Pro přizpůsobené Rayleighovo rozdělení lze pak číselně zjistit hranice intervalů spolehlivosti, jejichž závislost na relativní poloze je znázorněna na obrázku 8. ![Obrázek 8 – Relativní hranice intervalu spolehlivosti Rayleighova rozdělení v závislosti na relativní poloze](path/to/image.png) ## 1. Zjištění charakteristik Pro přímé zjištění charakteristik \( \alpha \) a \( \sigma \) lze pro \( 1.9131 \leq \frac{\mu}{\sigma} < 6 \) s dostatečnou přesností použít také následující aproximaci jako inverzní funkci vztahu (2.22) (chyba vážená na \( c \) je menší než 0.02): \[ \begin{equation} \hat{\sigma}_{\alpha} = 2.1 \left( \frac{ \mu}{\sigma} - 1.9131 \right)^{3.630} + 0.466 \left( \frac{\mu}{\sigma} - 1.9131 \right)^{1.82} \end{equation} \] Navíc může být zjištěn hranice intervalu spolehlivosti pro \( 1.9131 \leq \frac{\mu}{\sigma} < 6 \) provedením přímo pomocí následujících aproximací (chyba vážená na \( c \) je menší než 0.03): \[ \begin{equation} \hat{y}_{0.95} = -1.64 \left( \frac{ \mu }{ \sigma } - 1.9131 \right) + 2.075 \left( \frac{ \mu }{ \sigma } - 1.9131 \right) + 5.5485 \end{equation} \] \[ \begin{equation} \hat{y}_{0.80} = 2.6 \cdot \exp\left( -1.7031 - 0.8 \left( \frac{ \mu }{ \sigma } - 1.9131 \right) \right) - 2.1206 \end{equation} \] Pro \( \mu / \sigma < 6 \) se výpočet oblasti rozpětí provádí podle vzorce (2.11). Image Analysis: 1. **Localization and Attribution:** - The document contains one image positioned centrally on the page. - Numbering the image: Image 1. 2. **Object Detection and Classification:** - Image 1 contains a line graph with axes and multiple plotted lines. 3. **Scene and Activity Analysis:** - The scene depicts a line graph titled "Obrázek 8 – Relativní hranice intervalu spolehlivosti Rayleighova rozdělení v závislosti na relativní poloze" which translates to "Figure 8 – Relative confidence interval boundaries of the Rayleigh distribution in relation to relative position." - The main activity involves analyzing data points on the graph that show the dependency of relative position on the relative confidence interval boundaries of Rayleigh distribution. 4. **Text Analysis:** - Detected text in the image includes headings, descriptions, and annotations on the graph. - The text explains mathematical relationships and provides formulas and numerical approximations relevant to the graph. - Main formulas presented: - Formula (2.27): \[ \hat{ɛ_{a}} \left(\frac{\hat{µ}}{\hat{σ}}\right) = \frac{2.1}{\sqrt{\hat{µ}/\hat{σ}} -1.9131}^{-3.93} + 0.466 \left(\frac{\hat{µ}}{\hat{σ}} - 19131\right)^{1.42} \] - Formula (2.28): \[ \hat{x}_{0.995,} \left(\frac{\hat{µ}}{\hat{σ}}\right) = -1.84 \left(\frac{\hat{µ}}{\hat{σ}} - 19131\right)^{0.82} + 2.075 \left(\frac{\hat{µ}}{\hat{σ}} - 19131\right) + 5.5485 \] \[ \hat{x}_{0.995,} \left(\frac{\hat{µ}}{\hat{σ}}\right) = 2.6 \cdot \exp^{\left(-\frac{\hat{µ}}{\hat{σ}} - 1.703\right) \cdot 0.8} + 1.425 \cdot \left(\frac{\hat{µ}}{\hat{σ}} - 1.9131\right) - 2.1206 \] 5. **Diagram and Chart Analysis:** - The horizontal axis is labeled "relativní poloha μ/σ" (relative position μ/σ), ranging from 1.5 to 6. - The vertical axis is labeled "relativní hranice intervalu spolehlivosti" (relative confidence interval boundaries). - The graph contains two plotted lines representing different data series: \( \hat{x_{0.995,} / σ} \) and \( \hat{x_{0.995,} / μ/σ} \). - The trend shows that as the relative position increases, the relative confidence interval boundaries also change, which can be inferred from the behavior of the plotted lines. 13. **Graph Numbers:** - The specific data points on the graph are not numerically listed in the image, but the graph provides a visual representation of the relationship between relative position and relative confidence interval boundaries. - **Prozessbeschreibungen (Process Descriptions):** - The text describes mathematical procedures for determining the relative confidence interval boundaries based on the characteristics of the Rayleigh distribution. This involves using specific formulas to approximate the results. Overall, the image contributes to the comprehension of the mathematical relationships involved in the analysis of the Rayleigh distribution, offering a visual and analytical approach to understanding confidence interval boundaries concerning relative position. #################### File: VW%2010130_CS.pdf Page: 16 Context: # 3.2.2 Zjištění způsobilosti u nedf initovaných distribučních modelů Pokud nelze vybrané charakteristiky přidat vhodný distribuční model nebo pokud naměřené hodnoty odebrané vzorku neodpovídají předpokládaném distribučním modelu, proveďte se neparemetrický odhad charakteristik způsobilosti metodou rozptylu v následně modifikované formě při zohlednění rozsahu namátkových vzorků.5 (viz také příklad 3 v oddílu 5): ## Charakteristiky způsobilosti pro oboustranně tolerovaný ukazatel: \[ \hat{c}_{m} = \frac{G_{r} - G_{l}}{x_{u} - x_{l}} \tag{2.29} \] \[ \hat{c}_{m} = \min\left(\frac{G_{r} - x_{s_{95}}}{G_{r} - G_{l}}, \frac{x_{s_{95}} - G_{l}}{G_{r} - G_{l}}\right) \tag{2.30} \] ## Charakteristiky způsobilosti pro jednosměrně nahoře tolerovanou charakteristiku a přirozenou dolní mezní hodnotu rovnou nule: \[ \hat{c}_{m} = \frac{x_{0}}{x_{u}} \tag{2.31} \] \[ \hat{c}_{l} = \frac{G_{r} - x_{s_{95}}}{G_{r} - G_{l}} \tag{2.32} \] ## Charakteristika způsobilosti pro jednosměrně dole tolerovanou charakteristiku: \[ \hat{c}_{m} = \frac{x_{s_{05}} - G_{l}}{x_{u} - x_{l}} \tag{2.33} \] * přičemž - \( x_{0} - x_{u} \): odhadované hodnoty horní a dolní hranice intervalu spolehlivosti - \( \hat{x} \): odhadnutá hodnota 50%ního kvantilu ## V případě dílčí hodnoty je \[ x_{s_{05}} = \bar{x} \tag{2.34} \] * přičemž - **Median**, hodnota, která je zprostředná spolehlivosti naměřených hodnot. \[ \hat{x}_{0} = \bar{x} + \frac{R}{2} \tag{2.35} \] * přičemž - \( \bar{x} \) a \( R \) = normální rozdělení ukazatele. Image Analysis: ### Analysis of the Attached Visual Content #### Localization and Attribution: **Single Image:** The provided image appears on a single page, specifically labeled "Strana 16," which is the Czech word for "Page 16". #### Text Analysis: The text appears to be an excerpt from a technical document or manual, and it's written in Czech. The main headings and sections include: 1. **Section 3.2.2:** - Title: "Zjištění způsobilosti u nedefinovaných distribučních modelů" which translates to "Determining capability for undefined distribution models." - This section seems to discuss methods for estimating process capability when measured values or distribution models don’t conform to typical distribution assumptions. 2. **Formulas:** - It contains several formulas for calculating different capability indices: - Formula (2.29): Describes the general index for two-sided tolerances. - Formula (2.30): Modified index considering range and sample. - Formula (2.31) & (2.32): Indices for upper and lower one-sided tolerance characteristics. - Formula (2.33): Another form of index for lower one-sided tolerance. - Various parameters are defined: - \( \hat{X}_{50\%} \): Estimated median value. - \( \overline{X} \): Mean value. - \( k \): Upper and lower confidence interval limits. - \( R \): Range. 3. **Footnote:** - There's a footnote numbered [5] indicating that the similar approach to capability calculation might have been used in previous guidelines or standards. #### Diagram and Chart Analysis: There are no diagrams or charts present on this page. #### Mathematical Content Breakdown: The image includes various mathematical formulas and symbols primarily indicating statistical measures: - **Capability Indices (č.m, č mak, etc.)**: These are statistical metrics used to measure if a process meets specifications. - **Odhad (Estimate)**: Terms related to upper and lower limits of the confidence interval. - **Medián (Median)**: Measure of central tendency. #### Contextual Significance: Based on the title and technical nature of the content, this page likely belongs to a technical document detailing statistical process control (SPC) or quality control methods in manufacturing or production environments. The formulas and their specific indices are significant for engineers or quality control professionals who need to understand and implement statistical methods to ensure manufacturing processes are within acceptable tolerance levels. #### Anomaly Detection: No anomalies are detected in terms of unusual elements or inconsistencies. #### Perspective and Composition: The image was taken from a straightforward, eye-level perspective suitable for documents. The composition follows a clear, structured format typical for technical documents, with headings, formulas, and related explanations. #### Metadata Analysis: No metadata information is available in the image provided. This document seems to be quite technical and assumes the reader has a good understanding of statistical methods and quality control terminology. The detailed mathematical formulas are used to provide precise calculation methods for determining process capabilities in manufacturing or analysis scenarios. #################### File: VW%2010130_CS.pdf Page: 17 Context: \[ x_c = \frac{x_{\text{max}} + x_{\text{min}}}{2} \tag{2.36} \] \[ R = x_{\text{max}} - x_{\text{min}}: \text{rozpětí} \quad x_{\text{max}}, \, x_{\text{min}}: \text{maximální, popř. minimální naměřená hodnota efektivního celkového namátkového vzorku.} \] Opravným faktorem \[ k = \frac{d}{d_n} \tag{2.38} \] je přitom zohledněn efektivní rozsah namátkových vzorků \(n_e\), přičemž: \[ d^*: \text{očekávaná hodnota w rozdělení}^{6} \] Pro některé rozsahy namátkových vzorků \(n_e\) je v tabulce 1 uvedena hodnota \(d_n\). ### Tabulka 1 – Očekávaná hodnota w rozdělení v závislosti na \(n_e\) | \(n_e\) | \(d_n\) | |---------|---------| | 20 | 3,74 | | 25 | 3,93 | | 30 | 4,09 | | 35 | 4,21 | | 40 | 4,32 | | 45 | 4,42 | | 50 | 4,50 | Pro rozsahy namátkových vzorků, které jsou větší než 20, lze zjistit očekávané hodnoty w rozdělení podle následujícího přiblížení vzorce: \[ d_n = \frac{1.748}{\sqrt{(\ln(n_e))}} \tag{2.39} \] V případě rozdělení četnosti setříděných naměřených hodnot je \[ \bar{x}^* : \bar{x}^* \text{rovno horní popř. dolní mezi nejnižší, popř. nejspodnější obsazené třídy} \] \[ \bar{x}_{k} = x_{k} + \frac{n_{k} - A_{k}}{a_{k}} \cdot \Delta x \quad \text{pro } A_{k} < n_{k} \leq A_{k} + a_{k} \tag{2.40} \] přičemž \(\bar{x}^*:\) spodní hranice k-té třídy \\ \(\Delta x:\) šířka třídy \\ \(a_k:\) absolutní četnost naměřených hodnot v k-té třídě \\ \(A_{k}:\) absolutní distribuční funkce naměřených hodnot až po spodní hranici k-té třídy Image Analysis: ### Localization and Attribution - **Image 1**: This is the only image on the page. ### Text Analysis - **Image 1** contains mathematical equations, text, and a table: **Text Content:** - Title: "Tabulka 1 - Očekávaná hodnota v rozdělení v závislosti na ne" - Columns & Rows Content: - `ne` values: 20, 25, 30, 35, 40, 45, 50 - `d` values: 3.74, 3.93, 4.09, 4.21, 4.32, 4.42, 4.50 - Equations: Several equations are shown, such as: - \( x_c = \frac{x_{\text{max}} + x_{\text{min}}}{2} \) - Equation 2.36 - \( R = x_{\text{max}} - x_{\text{min}}: \) rozsah: maximální, popř. minimální naměřená hodnota efektivního celkového namátkového vzorku. - Equation 2.37 - An equation defining `k`: - \( k = \frac{d_e}{n_{n}} \) - Equation 2.38 - \( d_e = 1.748 \cdot (ln(n_e))^{0.993} \) - Equation 2.39 - Additional descriptions in Czech following these equations, likely explaining terms and application in sampling distribution. ### Diagram and Chart Analysis - **Table 1 - Očekávaná hodnota v rozdělení v závislosti na ne**: - A table showing the relationship between `ne` (likely sample size) and `d` (a distribution parameter or expected value). ### Anomaly Detection - No visible anomalies in the image. ### Color Analysis - The image is predominantly black-and-white, indicative of a document or textbook page. There are no other colors used. ### Perspective and Composition - The image is a straight-on scan or capture of a document page with text and table components properly aligned and centered. ### Contextual Significance - Based on the mathematical equations and detailed table, it is evident this image is part of a technical or academic document, likely focusing on statistical analysis or sampling methods. ### Graph and Trend Analysis - The table shows a trend where the value of `d` increases with the increase of `ne`, describing the expected relationship in the sample size and a parameter of distribution. ### Graph Numbers - From the table data: - \( n_e \) values: 20, 25, 30, 35, 40, 45, 50 - \( d \) values: 3.74, 3.93, 4.09, 4.21, 4.32, 4.42, 4.50 #################### File: VW%2010130_CS.pdf Page: 18 Context: # 3.3 Mezni hodnoty pro způsobilost stroje Pro dosažení způsobilosti stroje pro sledovanou charakteristiku je nutno splnit následující požadavky z hlediska stanovených mezních hodnot \( C_{mk}^{Gen.} \) a \( C_{mk}^{Gen.} \): \[ \bar{c}_{mk}^{Gen.} \geq c_{mk}^{Gen.} \tag{3.1} \] \[ \bar{c}_{mk}^{Gen.} \geq C_{mk}^{Gen.} \tag{3.2} \] v efektivním rozsahu námětkových vzorků \( n \geq 50 \). Pokud není dohody nutno nic jiného, platí následující mezni hodnoty způsobilosti: \[ C_{mk}^{Gen.} = 2,0 \] \[ C_{mk}^{Gen.} = 1,67 \] V případě, kdy je za účelných nákladů možná pouze jedna prověrka s menším efektivním rozsahem námětkových vzorků než 50, je nutno následujícím způsobem přihlédnout k vyšší nejistotě a to vyplyvajících zjištěných charakteristik způsobilosti pomocí příslušně zvýšených mezních hodnot. Zjištění mezních hodnot pro efektivní rozsahy námětkových vzorků menší než 50 je přitom vztaženo na mezní hodnoty, které lze z požadavku (3.1) nebo (3.2) pro prověřování základní soubor dodržet z 95% pravděpodobností (dolní meze oblasti spolehlivosti). Ty vyplývají ze předpokladů normálně rozděleného základního souboru z horní mezí oblasti spolehlivosti směrodatné odchylky: \[ \sigma = \frac{49}{\sqrt{n}} \tag{3.3} \] a statistické podílové oblasti pro výrobní rozptyl: \[ X_{89,965} = \mu + t_{(1 - \alpha/2, n - 2)} \cdot \sigma \left(1 + \frac{1}{n}\right)^{1/2} \tag{3.4} \] \[ U_{89,965} = 3.0: \quad \text{kvalitní standardizované normální rozdělení} \] \[ \chi^2_{(n-1)} = 33.9: \quad \text{kvalitní rozdělení chi kvadrát při stupni volnosti } f = 49 \text{ (viz také 1)} \] Image Analysis: ### Image Analysis #### 1. Localization and Attribution: - **Image 1**: - The entire page is a single image. #### 2. Object Detection and Classification: - Text: This is the primary element on the page. - Mathematical Equations: Several equations and formulas are listed. - Diagrams: There are diagrammatic representations, likely related to statistical or mathematical calculations. #### 3. Scene and Activity Analysis: - The image presents a technical document with text explaining processes and mathematical requirements. - The key activities include presenting and calculating certain tolerance indices for machinery, specifying effective sample size, and the boundary regions for confidence intervals. #### 4. Text Analysis: - **Header Text**: - "Strana 18" - "VW 101 30: 2005-02" - This indicates the page number and a standard code or document identifier. - **Section Header**: - "3.3 Mezní hodnoty pro způsobilost stroje" - This means "3.3 Limiting values for machine capability" in Czech. - **Body Text**: A detailed discussion on calculating limiting values for machine capability, necessary sample sizes, specific formulas, and statistical bounds. - **Equations and Formulas**: - Several mathematical representations, such as C_m, C_mk, and related statistical variables. #### 5. Diagram and Chart Analysis: - **Diagrams**: Present mathematical formulations - likely for normalizing effective ranges and determining probability limits. These diagrams support the equations presented in the text. #### 6. Product Analysis: - **Not Applicable**: No products are depicted. #### 7. Anomaly Detection: - **None Identified**: The document seems professionally structured with no unusual elements. #### 8. Color Analysis: - The document is primarily black and white, typical of formal technical documents to ensure clear readability. #### 9. Perspective and Composition: - **Perspective**: Top-down view of a single-page document. - **Composition**: The text is segmented by headings and subheadings. Equations and diagrams are integrated within the sections for clarity. #### 10. Contextual Significance: - This image is part of a larger technical document or engineering manual, providing specific standards, calculations, and tolerances. #### 11. Metadata Analysis: - **Not Available**: No metadata is embedded in the image. #### 12. Graph and Trend Analysis: - Equations suggest statistical norms and tolerance ranges, but no trend analysis is required as the focus is on static formulas. #### 13. Graph Numbers: - **Extracted Equation Elements**: - `C_m, C_m_gen` - `C_mk, C_mk_gen` - `49` - `3.0` - `33.9` - `49` #### Additional Aspects: - **Ablaufprozesse (Process Flows)** and **Prozessbeschreibungen (Process Descriptions)**: - The process describes the calculation of machine capability indices and bounds. - **Typen Bezeichnung (Type Designations)**: - Designations like `C_m` and `C_mk` are types of capability indices. - **Trend and Interpretation**: - The focus is on calculating tolerance and capability thresholds to ensure machine accuracy and reliability. - **Tables**: - No tables are identified in this specific image. In summary, this document page is primarily instructional, detailing the statistical methods and calculations necessary for determining machine capability in an engineering context. The detailed equations and sample size requirements highlight the precision needed for industrial standards. #################### File: VW%2010130_CS.pdf Page: 19 Context: # Transformace a dosazením do vyhodnocovacích vzorců (2.1) a (2.2) z toho vyplývá mezě způsobilosti pro základní soubor \[ c_{m} \geq \frac{2 \times 5.26}{49} \cdot 0.832 \] (3.5) \[ c_{mk} \geq \frac{1}{1 + \frac{1}{100}} \cdot \frac{1 \times 5.26}{49} \cdot 0.824 \] (3.6) Z toho vyplývá pro efektivní rozsahy namátkových vzorků \(n_k < 50\) následující přizpůsobené hodnoty mezi způsobilosti: \[ \hat{c}_{m} \geq c_{m, \text{G}rnez} \cdot 0.832 \cdot \sqrt{\frac{1}{2 \times n_k}} \cdot \left(\frac{f}{\sqrt{2}} \right) \] (3.7) \[ \hat{c}_{mk} \geq c_{mk, \text{G}rnez} \cdot 0.824 \cdot \left(1 + \frac{1}{2 \cdot n_k}\right) \cdot \sqrt{f} \] (3.8) se stupněm volnosti \[ f = n_k - 1 \] (3.9) ## Příklad Při stanovených mezích způsobilosti \(c_{m, \text{G}rnez} = 2.0\), \(c_{mk, \text{G}rnez} = 1.67\) a efektivním rozsahu namátkových vzorků \(n_k = 20\) vyplývá podle vzorců (3.7) až (3.9) následující přizpůsobené mezní hodnoty pro oboustranně tolerovanou charakteristiku: \[ \hat{c}_{m} \geq 2.0 \cdot 0.832 \cdot \sqrt{\frac{20}{10.1}} = 2.28 \] \[ \hat{c}_{mk} \geq 1.67 \cdot 0.824 \cdot \left(1 + \frac{1}{2 \cdot 20}\right) \cdot \sqrt{\frac{20}{10.1}} = 1.93 \] Image Analysis: Here is the comprehensive analysis based on the provided image: 1. **Localization and Attribution:** - There is only one image on the entire page, hence it is identified as **Image 1**. 4. **Text Analysis:** - The image contains text in the Czech language, which outlines formulas and mathematical explanations. - The header reads: "Strana 19 VW 101 30: 2005-02". - The main content contains formulas and calculations concerning "meze způsobilosti pro základní soubor" which translates to "limits of capability for the basic set". - Key formulas include: - \( c_{m} \geq c_{m_{Grenze}} \cdot \sqrt{\frac{2x \cdot r}{49}} = 0.832 \cdot c_{m_{Grenze}} \) [Formula 3.5] - \( c_{m_{k}} \geq c_{m_{k_{Grenze}}} \cdot \sqrt{\frac{1}{1 + \frac{1}{100}}} = 0.824 \cdot c_{m_{k_{Grenze}}} \) [Formula 3.6] - There is an explanation following these formulas indicating that this is applicable when the number of random samples \( n_{k} < 50 \). - Example calculations provided with specific values: - \( c_{m} \geq 2.0 \cdot 0.832 \cdot \sqrt{\frac{20 - 1}{10.1}} = 2.28 \) - \( c_{m_{k}} \geq 1.67 \cdot 0.824 \cdot \left( 1 + \frac{1}{2 \cdot 20} \right) \cdot \sqrt{\frac{20 - 1}{10.1}} = 1.93 \) - There is a footer note explaining that the adjusted capability limits are used for cross-checking and stand as a compromise method due to a lack of more sophisticated procedures in practice for samples less than 50. 5. **Diagram and Chart Analysis:** - The image does not contain any diagrams or charts. 8. **Color Analysis:** - The document is primarily black and white. The absence of color emphasizes the text and mathematical formulas, providing clear readability for technical content. 9. **Perspective and Composition:** - The image is taken from a straight-on perspective, likely a scan or direct capture of a document page. The text and formulas are centered and aligned to present a clear and structured format. 10. **Contextual Significance:** - The document appears to be an excerpt from a technical manual or academic paper, likely related to statistical methods or quality control based on the context of the formulas and calculations provided. - It contributes to explaining specific statistical parameters and their practical applications in determining capability limits for smaller sample sizes. **Additional Aspects:** - **Ablaufprozesse (Process Flows) and Prozessbeschreibungen (Process Descriptions):** - The document does not depict any process flows or descriptions. - **Typen Bezeichnung (Type Designations):** - Types or categories of proficiency limits and sample sizes (e.g., "základní soubor" for the basic set, "efektivním" for effective range) are identified and described within the formulas. - **Trend and Interpretation:** - The formulas and examples illustrate the trend of adjusting capability limits when dealing with smaller sample sizes to ensure reliable quality control measures. This comprehensive examination of the provided image covers all visual and textual aspects presented and their implications within a technical or academic context. #################### File: VW%2010130_CS.pdf Page: 20 Context: # 3.4 Statistické testy Náměrné hodnoty prozkoumávat schopnost stroje zpravidla nesmí vykazovat: - nečekaně velké odchylky jednotlivě naměřených hodnot (odlišné hodnoty) oproti rozptylu ostatních hodnot, - signifikantní změny polohy během obou vzorků a - signifikantní změnu od očekávaného distribučního modelu. V opakovaném případě je nutno počítat s dodatečnými systémovými vlivy na výrobu. Pro toto chování by pak měly být známy příčiny a měly by být akceptovatelné jejich účinky, aby byl splněn předpoklad bezpečného výrobního procesu. Pro provádění výše uvedených kritérií je proto nutno jít prozkoumávat schopnost stroje použít podklady statistické teorie. Protože tyto testy jsou podrobně popsány v normách nebo doporučeních druhů statistické literatury, jsou zde uvedeny pouze pomoci odkazů: V rámci prověřování schopnosti stroje je nutno provádět následující testy: 1. **Testy odchylek hodnot pomocí testů nezávislých na rozdělení podle Hampela modifikované formě (viz VW 10133)** - **Testy změny polohy** výroby pomocí neparametrického testu podle Swed-Eisenharda (viz [1]) - **Test odchylek od normálního rozdělení** podle Epps-Pullev (viz ISO 5479) - **Test odchylek od libovolně stanoveného distribučního modelu** pomocí testu chi kvadrát (viz [1]) Statistické testy podle následujícího schématu: - formulace nulové hypotezy \( H_0 \) a alternativní hypotezy \( H_a \), např. - H1: základní soubor naměřených hodnot sledovaného znaku má normální rozdělení - H1: základní soubor naměřených hodnot sledovaného znaku nemá normální rozdělení - Stanovení pravděpodobnosti vyjádření \( 1 - \alpha \) nebo hladiny významnosti α - Formulace vzorce pro zkušební veličinu - Výpočet zkušební hodnoty \( h \) podle namátkových vzorků podle vzorce pro zkušební veličinu - Zjištění prahové hodnoty testovacích rozdělení ## Porovnání Je nutno dbát na to, že u statistického testu s uvedenou vycházející pravděpodobností je přípustné prokázat pouze rozptyl nulovou hypotézou, např. že existuje signifikantní odchylka naměřených hodnot od normálně rozděleného základního souboru. Pokud z výsledků testu vyplývá rozpor s nulovou hypotézou, pak to není potvrzením platnosti nulové hypotézy. Proto v případě nelze s uvedeným spolehlivostí např. prokázat, že existuje zakladní soubor s normálním rozdělením. Pak se vytvořte analogicky k právnímu principu, v případě spojení normálně rozděleného souboru jako pro předpoklad nulové hypotézy. Hladina významnosti se uvažuje jako riziko, že se na základě testu zamítne nulová hypotéza, ačkoli je správná (α-riziko). Pro hladinu významnosti vždy lze jen jednoduše stanovit libovolné menší hodnoty, proto že tím pak roste riziko neobjevení skutečně odchylek od normálního rozdělení (β riziko). Image Analysis: ### Text Analysis: #### Detected Text: 1. **Header Information:** - "Strana 20" - "VW 101 30: 2005-02" 2. **Section Title:** - "3.4 Statistické testy" (Statistical tests) 3. **Content:** - The main text discusses statistical tests used to validate the quality and reliability of machinery during production. The text details methods to check significant deviations in measured values and significant changes in anticipated distribution models. - Emphasis is placed on the need to avoid systematic influences during checks to ensure the impact is valid and meets safety standards. #### Subtopics and Bullet Points: - **Primary Methods:** - Tests for significant deviations using non-parametric Ronald Hampel's test. - Tests for change points using the Swed-Eisenhart method. - Tests for normal distribution deviation using Epps-Pulley method. - Test using chi-squared for any arbitrary distribution model. - **General Schema for Statistical Tests:** - Formulation of null hypothesis (H0) and alternative hypothesis (Ha). - Calculation based on measured values assuming normal distribution. - Presentation of probability significance from 1 - α. - Formulation of test statistic formulas. - Calculation of threshold values for test statistics. - Determining threshold values for test distributions. - Comparing test indicators with threshold values to make decisions regarding null hypotheses. - **Significance and Decision Making:** - Determining when there is a significant deviation or a match with an alternative hypothesis. - Distinguishing true and false deviations by considering significant results against accepted norms. #### Contextual Significance: - This text is likely part of a technical or scientific document, particularly dealing with quality control in manufacturing, and highlights various statistical methods to ensure the reliability of production machinery. The thorough explanation of the tests and decision-making process indicates a focus on precision and compliance with certain standards. ### Metadata Analysis: - **Page Number:** - 20 (This suggests that the document is part of a larger series, likely a standard or guideline manual.) - **Document Code:** - VW 101 30: 2005-02 (This could denote a standard document/specification used by Volkswagen or pertaining to a specific technical standard.) ### Prozessbeschreibungen (Process Descriptions): - **Processes:** - The processes described involve systematic testing for deviations in machinery performance during production. These tests need to objectively and accurately indicate whether the deviations are within acceptable bounds to ensure safe and reliable manufacturing outputs. ### Trend and Interpretation: - **Significance:** - The emphasis on statistical validity and the detailed method descriptions suggest that maintaining high-quality standards in manufacturing is crucial. The use of various statistical tests ensures a comprehensive approach towards validating machinery performance, highlighting a commitment to quality and safety. This analysis considers the various components of the document and offers insights into its purpose and significance within a manufacturing and quality assurance context. #################### File: VW%2010130_CS.pdf Page: 21 Context: # 4 Provádění prověřování způsobilosti stroje Provádění prověřování způsobilosti stroje (MFU) je nutno provádět podle procesu znázorněného na obrázcích 9 až 11. ## 4.1 Použití zkušebních prostředků ## 4.2 Odběr namátkových vzorků ### Podmínky pro MFU splněny - **ano**: - 4.4 Vyhodnocování dat - 4.5 Dokumentace - 4.6 Posouzení výsledků - **ano**: Opačování vyhodnocení - **ne**: Stroj způsobilý - **ano**: - 4.8 Nakládání s nezpůsobilými stroji - **ne**: Proveditelná optimalizace stroje - **ne**: 4.3 Zvláštní pravidla pro omezenou MFU ## 4.7 Optimalizace stroje Konec ![Obrázek 9 – Průběh prověrky způsobilosti stroje](path-to-image) Image Analysis: ### Comprehensive Examination of the Visual Content #### Localization and Attribution - **Image Number**: Image 1 - This is the only image on the page. #### Object Detection and Classification - **Objects Detected**: - Rectangular boxes with text (flowchart components) - Various arrows connecting the boxes (indicating flow direction) #### Scene and Activity Analysis - **Scene Description**: - The image depicts a flowchart related to the machine suitability test process ("Provádění prověřování způsobilosti stroje"). - **Activities Taking Place**: - The flowchart outlines a step-by-step process starting from initialization (Start) to various decision points and actions until the completion (Konec) of the machine suitability test. #### Text Analysis - **Text Extracted**: - "Strana 21" - "VW 101 30: 2005-02" - "4 Provádění prověřování způsobilosti stroje" - "Provádění prověřování způsobilosti stroje (MFU) je nutno provádět podle procesu znázorněného na obrázcích 9 až 11." - "Obrázek 9 - Průběh prověrky způsobilosti stroje" - Start - 4.1 Použití zkušebních prostředků - 4.2 Odběr namátkových vzorků - Podmínky pro MFU splněny - ano - ne - 4.3 Zvláštní pravidla pro omezenou MFU - 4.4 Vyhodnocování dat - 4.5 Dokumentace - 4.6 Posouzení výsledků - Opakování vyhodnocení - ano - ne - Stroj způsobilý - ano - ne - 4.7 Optimalizace stroje - ano - Proveditelná optimalizace stroje - ne - 4.8 Nakládání s nezpůsobilými stroji - ne - Konec - **Text Significance**: - The text describes a documented process in Czech for conducting machine suitability tests (MFU - Machine Fitness Unit). It specifies steps and decision points for evaluating whether a machine is fit for use and any corrective actions required. #### Diagram and Chart Analysis - **Diagram Type**: - Flowchart - **Key Insights**: - The chart begins with "Start" and goes through steps such as using testing equipment, sampling random samples, evaluating conditions, data evaluation, documentation, and result assessment. - Conditional branches determine if certain criteria (e.g., suitability conditions, optimization feasibility) are met, directing the flow to different paths and actions (e.g., repeating assessments, handling unsuitable machines). #### Process Descriptions (Prozessbeschreibungen) - **Process Flow**: - The process flow involves several stages: 1. **Using testing tools (4.1)** 2. **Sampling random samples (4.2)** - If conditions are met (yes/no decision) 3. **Special rules for limited MFU if conditions are not met (4.3)** 4. **Data evaluation (4.4)** 5. **Documentation (4.5)** 6. **Result assessment (4.6)** - If the assessment needs to be repeated (yes/no decision) - If the machine is suitable (yes/no decision) 7. **Machine optimization if it is not suitable (4.7)** - Feasibility of optimization (yes/no decision) 8. **Disposition of unsuitable machines if optimization is not feasible (4.8)** 9. **End of process ("Konec")** #### Color Analysis - **Color Composition**: - The flowchart is in black and white, which ensures clear readability and highlights the process and decision points efficiently without the distraction of colors. #### Perspective and Composition - **Perspective**: - The flowchart is presented from a straightforward, top-down perspective suitable for procedural diagrams. - **Composition**: - The flowchart has a logical and orderly layout, with steps arranged sequentially and decision points branching appropriately, making it easy to follow. #### Contextual Significance - **Contribution to Overall Message**: - The diagram plays a crucial role in conveying a standardized procedure for assessing machine suitability within a broader context, likely a quality control or process management document. #### Trend and Interpretation - **Trend and Insights**: - The process demonstrates a rigorous quality assurance trend, emphasizing systematic evaluations, documentation, and decision-making criteria to ensure only suitable machines are in operation. #### Tables - Not applicable in this image. ### Conclusion The visual content provided is a detailed flowchart outlining the process of machine suitability testing (MFU) in Czech language. It offers a step-by-step, decision-driven framework ensuring meticulous assessments, documentation, and necessary actions to maintain machine efficacy and adherence to standards. The orderly and straightforward depiction ensures clarity and ease of implementation in practical scenarios. #################### File: VW%2010130_CS.pdf Page: 22 Context: # 4.4 Vyhodnocování dat ## 4.4.1 Výběr očekávaného distribučního modelu ## 4.4.2 Test na odlišné hodnoty Existují odlišné hodnoty? - **ano** → 4.4.3 Vyjmout odlišné hodnoty z výpočtu statistických ukazatelů - **ne** → ## 4.4.4 Test změny polohy výrobky ## 4.4.5 Test odchylek od stanoveného distribučního modelu Odchylka od distribučního modelu? - **ano** → 4.4.8 Neparametrické vyhodnocení - **ne** → - Normální rozdělení? - **ano** → 4.4.6 Vyhodnocení podle normálního rozdělení - **ne** → 4.4.7 Vyhodnocení podle stanoveného modelu Pokračování v bodě 4 **Obrázek 10 – Průběh vyhodnocování dat** Image Analysis: ### Comprehensive Examination of the Attached Visual Content **Image Identification:** - **Image Number:** 1 - **Description:** A process flowchart related to data evaluation as indicated by the text “Průběh vyhodnocování dat.” ### Analysis: #### 1. **Localization and Attribution:** - **Position:** Only one image is present in the document. - **Designation:** Image 1 #### 2. **Object Detection and Classification:** - **Objects Identified:** - Multiple geometric shapes including ovals and rectangles. - Connecting arrows. - Text inside the shapes. - **Classification:** - **Ovals**: Indicate the start and continuation points of the process. - **Rectangles**: Represent various steps or actions. - **Diamonds**: Indicate decision points in the process. #### 4. **Text Analysis:** - **Extracted Text:** - "4.4 Vyhodnocování dat" - "4.4.1 Výběr očekávaného distribučního modelu" - "4.4.2 Test na odlehlé hodnoty" - "Existují odlehlé hodnoty" - "4.4.3 Vyjmout odlehlé hodnoty z výpočtu statistických ukazatelů" - "4.4.4 Test změny polohy výrobě" - "4.4.5 Test odchylky od stanoveného distribučního modelu" - "Odchylka od distribučního modelu" - "Normální rozdělení" - "4.4.7 Vyhodnocení podle stanoveného modelu" - "4.4.8 Neparametrické vyhodnocení" - "4.4.6 Vyhodnocení podle normálního rozdělení" - "Pokračování v bodě 4" - "Strana 22" - "VW 101 30: 2005-02" - "Obrázek 10 – Průběh vyhodnocování dat" - **Contextual Significance:** The text provides a structured overview of data evaluation procedures, likely from a procedural or technical guide. #### 5. **Diagram and Chart Analysis:** - **Description:** - **Title:** "Průběh vyhodnocování dat" - **Structure:** The diagram is a flowchart outlining a decision-making process for evaluating data. - **Flow:** Begins with “4.4 Vyhodnocování dat” and follows through various decision points with conditional operations. - **Key Components:** - **Start:** "4.4 Vyhodnocování dat" - **Steps:** Sequential steps are numbered from 4.4.1 to 4.4.8. - **Decisions:** Conditional branches are based on whether outliers exist, deviations from the model, and normalization of distribution. - **End:** Concludes with "Pokračování v bodě 4". - **Key Insights:** - The chart systematically handles data evaluation, starting with model selection, testing for outliers, and evaluating deviations from the expected model. - It also incorporates decision points for non-parametric evaluation and consideration of normal distribution. ### Additional Analysis: #### **Ablaufprozesse (Process Flows):** - **Description:** The flowchart depicts a detailed process flow for evaluating data. It highlights the decision points and clearly distinguishes the steps to be taken based on the evaluation results. #### **Prozessbeschreibungen (Process Descriptions):** - **Detail:** Each step is described, ensuring a thorough understanding of the stages involved in data evaluation. It starts with model selection and progresses through testing stages, decision-making regarding outliers and model deviations, and appropriate evaluation methods based on the statistical analysis. #### **Typen Bezeichnung (Type Designations):** - **Identification:** The types or categories are designated by the step numbers (e.g., 4.4.1 for model selection, 4.4.2 for testing outliers). ### Summary: This flowchart, designated as "Obrázek 10 – Průběh vyhodnocování dat" on "Strana 22", outlines a comprehensive data evaluation process, demonstrating the stages and decision points essential for statistical data analysis. Structured with clear conditional operations and procedural steps, it’s an effective tool for ensuring systematic and consistent data evaluation in line with technical guidelines. #################### File: VW%2010130_CS.pdf Page: 23 Context: # 4.6 Posouzení výsledků ![Obrázek 11 – Průběh posouzení výsledku](link_to_image) 1. **Existují odlišné hodnoty?** - **ano**: Pokračovat k bodu 2. - **ne**: Konec. 2. **Změna polohy výrobky?** - **ano**: Pokračovat k bodu 3. - **ne**: Konec. 3. **Odchylka od distribučního modelu?** - **ano**: Pokračovat k bodu 4. - **ne**: Možný jiný distribuční model. - **ano**: Opakování vyhodnocení pokračování v bodě 4. - **ano**: Známá příčina a akceptovatelný vliv. - **ano**: Stroj způsobilý. Pokračování v bodě 4. - **ne**: Stroj nezpůsobilý. Pokračování v bodě 4. - **ne**: Konec. 4. **Charakteristiky způsobilosti menší než mezní hodnoty?** - **ano**: Stroj způsobilý. Pokračování v bodě 4. - **ne**: Stroj nezpůsobilý. Pokračování v bodě 4. Image Analysis: **Analysis of Image 1: Flowchart** 1. **Localization and Attribution:** - This is a single image located centrally on the page. - Labeled as Image 1. 2. **Object Detection and Classification:** - Objects: Contains various geometric shapes including ovals, diamonds, rectangles, and connectors (arrows). - Categories: Flowchart diagram elements. 3. **Text Analysis:** - Detected text: - "4.6 Posouzeni vysledku" - "Existují odlehlé hodnoty" - "Odlehlé hodnoty v důsledku chybných měření" - "Změna polohy výroby" - "Odchylka od distribučního modelu" - "Možný jiný distribuční model" - "Opakování vyhodnocení, pokračování v bodě 4" - "Známá příčina a akceptovatelný vliv" - "Charakteristiky způsobilosti menší než mezní hodnoty" - "Stroj způsobilý, Pokračování v bodě 4" - "Stroj nezpůsobilý, Pokračování v bodě 4" - "Obrázek 11 – Průběh posouzení výsledku" - Analysis of text: - Title "4.6 Posouzeni vysledku" translates to "4.6 Outcome Assessment". - Diagram evaluates different steps in outcome assessment with decision paths indicated by "ano" (yes) and "ne" (no). - The text in diagrams describes steps and conditions for deciding on manufacturing and distribution impact, including potential errors and known causes. - The final outcomes are either "Stroj způsobilý" (Machine suitable) or "Stroj nezpůsobilý" (Machine unsuitable). 4. **Diagram and Chart Analysis:** - Diagram Type: Flowchart showing decision points and flow of actions. - The flowchart begins with the assessment of the results "4.6 Posouzeni vysledku". - It queries whether there are outlier values which, if due to erroneous measurements, suggests re-evaluation. - If not erroneous, it examines changes in production positions, deviations from the distribution model, possible use of other distribution models, and known acceptable influences. - At various decision points, the chart concludes whether the machine continues to be suitable or unsuitable, directing to procedure in "bodě 4" when necessary. 5. **Ablaufprozesse (Process Flows):** - The flowchart clearly details the process of outcome assessment with conditional steps resulting in suitability evaluation of machines. - It captures a methodical approach to decision-making, considering multiple variables and contingencies in manufacturing processes. 6. **Prozessbeschreibungen (Process Descriptions):** - Describes assessment steps starting from checking outliers, evaluating model deviations, potential errors, and known influences. - Each step involves clear conditional checks leading to a final verdict on machine suitability. #################### File: VW%2010130_CS.pdf Page: 24 Context: # 4.1 Použití zkušebních prostředků Pro MFU je nutno používat pouze zkušební prostředky, které byl pro plánovaný zkušební proces schválen příslušným místem. ## 4.2 Odběr namátkových vzorků MFU se vztahuje pouze na výrobní charakteristiky nebo parametr vzorku. Zpravidla je nutno pro vyhodnocení zjistit jednotlivé naměřené hodnoty vzorků. V případě ručně zaznamenávaných naměřených hodnot ve formě čárek v rozdělení tříd oblastí hodnocení (statistickou četností) je nutno také evidovat rozdělení četností daných naměřených hodnot9. Aby bylo možno pi MFU poskytnout pouze v této stroj, je nutno při výrobě vzorků dodržet následující podmínky: - Při provádění musí být zajištěna jednotná **šarže polotovaru** a jednotná příprava (dodavatel, materiál). Během MFU musí stroj nebo zařízení obsluhovat vždy stejný pracovník. - **Kvalita přípravy** hodnocených značek musí odpovídat požadovaným výrobním předpisům. - Počet vybraných dílů (rozsah namátkových vzorků) by měl zpravidla činit 50 ks. Pokud je tento rozsah namátkových vzorků z technických nebo ekonomických důvodů obtížně realizovatelný, je přípustný i menší. Pak je nutno dodržet odpovídajícím způsobem vyšší měrný rozsah (hodnoty podle tabulky 3 nebo var. (3.7) a (3.8). Efektivní rozsah namátkových vzorků (např. bez odlehlých hodnot) musí činit minimálně 20. - Dílů je nutno vyrábět bezprostředně po sobě a číslo podávat výrobě. Na každém dílu je nutno provést všechny stanovené záznamy. - MFU se smí provádět pouze u stroje zahřátého na provozní teplotu. Pojem "zahřátí na provozní teplotu" je nutno definovat pro každý případ použití zvlášť. - Je nutno zajistit, aby se nenačítala MFU záznamy pro sériových podmínek požadovaných pro daný stroj (tzn. z období tahu a parametry nastavené přímo pro sériovou výrobu). V závislosti na projektu je nutno stanovit pravidla, aby bylo na začátku MFU zaručeno, že je např. **zaparované žádánce**, a že konec doby životnosti nebyl nařízen v rámci MFU. - Během MFU se nesmí provádět **výměna zařízení**, různí seřizovací zařízení nebo jiné změny parametrů strojů. Vyměníte-li automatické korektury návrdu pomocí integrovaného nebo trvalého kontrolního měření. - Při poruchách vzniklých Během MFU, které ovlivňují prověřovací znak, je nutno zahájit MFU znovu. - Před výrobní zkouškou musí být zahájení prověřovací metody oznámeno a doslohnmých metod navíc uvedená a odložená. - Při výrobě rozměrových dílů (rozdílná čísla dílů, např. cejlové hřídele / litinové hřídele) na žádném MFU, které mohou vykazovat různé charakteristiky, je nutno MFU prověřit způsobem veškeré důkazy. Image Analysis: ### Text Analysis: 1. **Localization and Attribution:** - **Image Location and Positioning**: The image is a single page from what appears to be a document or a manual. It contains a structured text layout with numbered sections and bullet points. 2. **Text Content and Analysis**: - The page is in Czech and addresses protocols and processes for using test resources and taking samples in a manufacturing context. - **4.1 Use of Test Resources**: States that test resources should only be used for the intended approval process with the designated authority. - **4.2 Sampling**: Details about sampling processes are provided: - **Production Sample Characteristics**: Emphasizes the need to measure parameters of production samples properly. - **Uniform Batch Preparation**: Highlights the need for uniform batch preparation and proper handling by designated personnel. - **Preparation Quality**: Draws attention to the requirement that preparation quality characteristics should meet production standards. - **Sample Quantity**: Mentions the typical quantity of samples (usually 50 pieces), and exceptions for technical or economic reasons, permitting smaller quantities as long as they meet certain criteria. - **Direct Production and Marking**: Stipulates the direct preparation and marking of samples. - **Operational Testing**: Notes the importance of testing samples at operational temperature. - **Production Conditions**: Details that samples should be produced under specific conditions analogous to serial manufacturing. - **Tools and Equipment**: Mentions the restricted change of tools and parts, calling out exceptions such as integrated monitoring systems. - **Testing and Methodology**: Elaborates on the test methods and their required approval before commencing testing. - **Unique Characteristics**: Speaks to the need for diverse procedures for different characteristics of parts (e.g., different diameters or materials). 3. **Process Descriptions**: - The document provides a detailed description of protocols related to the manufacturing sampling process, stating explicit steps and conditions necessary for testing and sample preparation. 4. **Typen Bezeichnung (Type Designations)**: - The text makes specific mentions of different types of components and processes e.g., 'bare, semi-finished, or finished batch', indicating the varying types of samples and their preparatory needs. 5. **Prozessbeschreibungen (Process Descriptions)**: - Describes the process steps for ensuring quality in test samples: - Ensuring uniform sample batches. - Regularly measuring and assessing samples. - Handling and operational protocols for sample testing. - Adjustments for component variability. ### Conclusion: This document page from a manual outlines explicit manufacturing protocols for testing and sample preparation, emphasizing standardization, quality checks, and procedural adherence. It is meant to guide operators and quality assurance teams in maintaining adherence to manufacturing standards and ensuring reliable sample quality for testing purposes. #################### File: VW%2010130_CS.pdf Page: 25 Context: # 4.3 Zvláštní pravidla pro omezené MFU Pokud nelze pro odběr vzorku zcela splnit podmínky uvedené v bodě 4.2, pak ze o odváděných případech pro omezení MFU, pro které je nutno mezi dodavatelem a odběratelem sjednat zvláštní pravidla a zadokumentovat je pod poznámkou „Omezení MFU“. # 4.4 Vyhodnocení dat ## 4.4.1 Výběr očekávaného distribučního modelu Očekávaný distribuční model závisí na druhu charakteristiky. Pro důležité druhy charakteristik (viz také VW 01056) jsou přiřazeny distribuční modely uvedeny v tabulce 2. ## Tabulka 2 – Přiřazení druhů charakteristik a distribuční modely | Druh charakteristiky | Distribuční model | |---------------------------|-------------------| | Délkové rozměry | N | | Průměr, radius | N | | Plošnost | B1 | | Rovnoust | B1 | | Křivkovost | B1 | | Václový tvar | B1 | | Linijový tvar | B1 | | Plošný tvar | B1 | | Rovnběžnost | B1 | | Kolmost | B1 | | Sklon | B2 | | Pozice | B2 | | Sousous | B2 | | Symetrie | B1 | | Házivost | B2 | | Pohyb v rovině | B2 | | Drsnost | B1 | | Neváženost | B2 | | Krouticí moment | N | **Legenda:** N: Normální rozdělení B1: Weibullovo rozdělení B2: Rayleighovo rozdělení Pro neuvedené druhy charakteristik lze ve většině případů provést přiřazení rozdělení podle následujících pravidel: - u oboustranně nebo jednostranně dolů tolerovaných charakteristik normální rozdělení - a u jednostranně nahoru tolerovaných charakteristik Weibullovo rozdělení nebo Rayleighovo rozdělení Image Analysis: ### Image Analysis #### 1. Localization and Attribution: - **Image Location**: The image encompasses the entire page. - **Image Numbering**: This is the only image on the page, thus referred to as Image 1. #### 4. Text Analysis: - **Text Detection and Extraction**: - **Header**: "Strana 25", "VW 101 30: 2005-02" - **Sections**: - **4.3 Zvláštní pravidla pro omezené MFU** - **4.4 Vyhodnocení dat** - **4.4.1 Výběr očekávaného distribučního modelu** - **Tabulka 2 – Přiřazení druhů charakteristik a distribučních modelů** - **Content Analysis**: - The text is in Czech and appears to be from a technical or regulatory document related to data evaluation and distribution models. - **Key Sections**: - **4.3 Zvláštní pravidla pro omezené MFU**: Discusses special rules for limited MFU. - **4.4 Vyhodnocení dat**: Pertains to data evaluation. - **Tabulka 2**: A table that maps different types of characteristics to specific distribution models. - **Table Explanation**: - **Columns**: - **"Druh charakteristiky"**: Type of characteristic. - **"Distribuční model"**: Distribution model. - **Legend**: - "N": Normální rozdělení (Normal distribution) - "B1": Weibullovo rozdělení (Weibull distribution) - "B2": Rayleighovo rozdělení (Rayleigh distribution) - Other descriptions involve double-sided or one-sided tolerance distribution rules. #### 5. Diagram and Chart Analysis: - **Tabulka 2**: - **Rows/Columns**: Lists various characteristics (e.g., "Délkové rozměry", "Průměr, rádius", etc.) and their corresponding distribution models. - **Legend**: - **N**: Normální rozdělení - **B1**: Weibullovo rozdělení - **B2**: Rayleighovo rozdělení #### 12. Graph and Trend Analysis: - **Interpretation of the Table**: - Various characteristics are linked to different distribution models, providing a structured methodology for data evaluation based on the type of characteristic. - Some characteristics are commonly associated with normal distribution ("N"), while others are linked to Weibull ("B1") or Rayleigh ("B2") distributions. - The table helps in standardizing how data is to be distributed based on the specific characteristic, ensuring consistent and accurate evaluations. #### 19. Tables: - **Table Content**: - **Column 1** (Druh charakteristiky - Type of characteristic): Lists various types of dimensional and physical characteristics (e.g., dimensions, radius, flatness, roundness). - **Column 2** (Distribuční model - Distribution model): Indicates which distribution model fits each characteristic type (N, B1, B2). #### 9. Perspective and Composition: - **Perspective**: The image is a straightforward, top-down view of a text-heavy page. - **Composition**: - Structured in sections, with headings and subheadings clearly delineated. - The table (Tabulka 2) is centered and easily identifiable. - Text is evenly spaced and aligned for readability. #### 19. Process Descriptions: - **Process Description**: - The image outlines a structured process for determining the appropriate distribution model based on the characteristic type. - Provides guidelines for special cases not included in the table. ### Conclusion: This comprehensive analysis of the visual content reveals a technical document page with structured sections, detailed tables, and clear guidance on choosing distribution models based on specific characteristics. The text, tables, and accompanying explanations provide a robust framework for ensuring consistent data evaluation in a presumably engineering or quality control context. #################### File: VW%2010130_CS.pdf Page: 26 Context: ``` ## 4.4.2 Test odlehlých hodnot Pomocí neparametrického testu odlehlých hodnot podle VW 1013/3 je nejprve nutno zjistit, zda zjištěné naměřené hodnoty obsahují odlehlé hodnoty. Odlehlé hodnoty jsou naměřené hodnoty, které leží do jisté vzdálenosti od jinde naměřených hodnot tak daleko, že s vysokou pravděpodobností nepatří k této populaci. Tato měření, test na odlehlé hodnoty je nutno provést s koeficientem spolehlivosti 95%. ## 4.4.3 Výjimečné odlehlé hodnoty z výpočtu statistických ukazatelů V případě identifikovaných odlehlých hodnot nejsou tyto hodnoty zohledněny při výpočtu statistických ukazatelů. Odlehlé hodnoty však nesmí být smazány. Naopak je nutno je vygenerovat v zobrazené podobě jednotlivých hodnot odpovídajícími způsoby označit a uvést je do příslušné dokumentace. ## 4.4.4 Test změny polohy výroby S pomocí parametrického testu podle Swed-Eisenharta (viz [1]) je nutno zjistit, zda se při výběru vzorku systematicky změnila poloha výroby. Systematická změna polohy výrobků může vzniknout např. vlivem teploty opotřebení materiálu (trendový průběh). Tento test je nutno provést s koeficientem spolehlivosti 95%. Pokud použité pro výpočtové zjištěné rozdílení určitých zatížených naměřených hodnot, nelez tento test použít. ## 4.4.5 Test odchylek od stanoveného distribučního modelu Je nutno prověřit zjištěné naměřené hodnoty, zda nevykazují signifikantní odchylku od distribučního modelu, který byl pro příslušný znak stanoven. K tomu je nutno v případě zjištěného normálního rozdělení provést test podle Epps-Pulley (viz 150 5479) a v případě jiné statické distribuční model, např. v Weibullově rozdělení nebo Rayleighova rozdělení, test podle Nývarta (viz [1]) s koeficientem spolehlivosti 95%. Odchylka od zjištěného distribučního modelu může vzniknout např. rozdělením šarží materiálu při odběru vzorku (smíšené rozdělení, viz příklad 3 v oddílu 5). Odchylka od zjištěného distribučního modelu může vzniknout např. odběrem vzorku z různě nadřazené distribuční, viz příklad 3 v oddílu 5. ## 4.4.6 Vyhodnocení podmínek normálního rozdělení V případě stanoveného aproximováním normálního rozdělení nebo aproximováním normálního rozdělení podle kritérií (1.1), (1.22), ve kterém naměřené hodnoty nevykazují signifikantní odchylku od distribučního modelu, se provede výpočet charakteristických vlastností v závislosti na toleranci podílu vzorců (2.1) až (2.5), přičemž se hraniční intervaly spolehlivosti zjistí podle pozice (2.6). ## 4.4.7 Vyhodnocení polohy stanoveného modelu V případě jaké stanoveného distribučního modelu, např. Weibullova rozdělení nebo Rayleighova rozdělení, je nutno prověřit naměřené hodnoty, zda nevykazují signifikantní odchylku od distribučního modelu, se provede výpočet charakteristických vlastností podílu vzorců (2.1) až (2.5), přičemž se charakteristiky přizpůsobeného rozdělení vypočtou podle vzorců (2.15) a (2.16) popř. (2.24) a (2.25) pomocí aproximovaných funkcí (2.18) popř. (2.27) a hraniční intervaly spolehlivosti se vypočte podle aproximovaných funkcí (2.19) popř. (2.28). ``` Image Analysis: ### Text Analysis: - **Image Localization and Numbering:** - This image will be denoted as **Image 1** since there is only one image provided. - **Extracted Text and Content Analysis:** - The text in the image is in Czech and appears to be sections from a technical document, specifically related to tests and processes influenced by certain standards and procedures. - The sections are as follows: - **4.4.2 Test odlehlých hodnot (Test of Outlying Values):** - Discusses the testing of outlier values according to VW 10133 with a confidence interval of 99%. - **4.4.3 Vyloučení odlehlých hodnot z výpočtu statistických ukazatelů (Exclusion of Outliers from Statistical Calculation):** - Procedures for excluding outliers in the calculation of statistical indicators. - **4.4.4 Test změny polohy výroby (Test of Production Position Change):** - Tests based on the Swed-Eisenhart method to determine if systematic shifts in production samples are systematic. - **4.4.5 Test odchylky od stanoveného distribučního modelu (Deviation Test from Established Distribution Model):** - Discusses tests like Epps-Pulley, Weibull, and Rayleigh models, with a 95% confidence interval. - **4.4.6 Vyhodnocení podle normálního rozdělení (Evaluation According to Normal Distribution):** - Outlines the criteria for evaluating against normal distribution and calculated fitting characteristics. - **4.4.7 Vyhodnocení podle stanoveného modelu (Evaluation According to Established Model):** - Similar to the above but uses different distribution models and calculation methods. ### Contextual Significance: - **Context and Role in Document:** - This image appears to be a page from a technical document related to quality control or standards compliance in manufacturing, probably for the automotive industry as indicated by "VW 10133". - The page is an excerpt from a larger document concerned with statistical testing, evaluation of production shifts, and assessment models. - The image contributes towards understanding the specific methodologies and statistical models used in evaluating manufacturing and production processes. ### Color Analysis: - **Color Composition:** - The image is mostly black text on a white background, a common format for printed documents. - The lack of color variation indicates a formal document focusing on the delivery of information rather than visual appeal. ### Perspective and Composition: - **Composition:** - The image is in a standard page format with a clear heading structure, numbered sections, and paragraphs. - This structured approach aids in easy navigation and understanding of the subjected tests and procedures. ### Summary: #################### File: VW%2010130_CS.pdf Page: 26 Context: ### Summary: - **Overall Analysis:** - **Image 1** is a section from a technical manual or standard document related to statistical testing and evaluation methods in production processes. - The document includes detailed descriptions of various tests and their purposes, highlighting procedures, models, confidence intervals, and criteria. - There is no visual data or graph present in the image, and the text is well-structured for a technical audience. This comprehensive analysis encompasses relevant aspects drawn from the provided list, with focus on text and contextual significance as they are the most prominent features in this image. #################### File: VW%2010130_CS.pdf Page: 27 Context: ``` 4.4.8 Neparametrické vyhodnocení Pokud ze statistického testu vyplyne rozpor mezi zjištěnými naměřenými hodnotami a zjištěnými distribučním modelem, nebo pokud se sledované výrobní charakteristiky nelze nalézt výchybném distribučním modelu, pak se provede neparametrický výpočet charakteristik způsobilosti podle vzorce (2.29) až (2.40). 4.5 Dokumentace Dokumentace MFU z hlediska určité charakteristiky musí obsahovat následující informace a záznamy: Data zahrnují: - oddělení, autor a datum vytvoření - údaje o dílu - název, jmenovitý rozměr a tolerance charakteristiky - údaje o stroji - údaje o zkušebních prostředcích - období výroby Výsledky: - grafické znázornění průběhu jednotlivých hodnot se středními hodnotami vzorku s hranicemi liniemi tolerančního intervalu (pokud byly evidovány jednotlivé hodnoty) - histogram s přizpůsobeným distribučním modelem, hranicemi liniemi tolerančního intervalu a oblastí rozptylu a linií střední hodnoty a mediánu - zobrazení v pravděpodobnosti stisí s přizpůsobeným distribučním modelem, hranicemi liniemi tolerančního intervalu a oblastí rozptylu a linií střední hodnoty a mediánu (viz [2]) - počet naměřených hodnot - počet vyhodnocených naměřených hodnot nebo nalezených odchylých hodnot - odhadovaná hodnota polohy výroby - odhadovaná hodnota hranic oblasti rozptylu nebo odhadovaná šíře rozptylu - pozitivity distribuční model - výsledek testu změny polohy výroby - výsledek testu odchylek od stanoveného distribučního modelu - vypočtené charakteristiky způsobilosti Cm a Cmk (se dvěma místy za desetinnou čárkou) - požadované mezi hodnoty Cm a Cmk Upozornění a poznámky: - případné upozornění na omezenou MFU - případné zvláštní dohody mezi dodavatelem a odběratelem - případně zvláštní udalosti během odběru vzorku ``` Image Analysis: ### 1. Localization and Attribution: - **Image Position:** Single image present on the page. - **Image Number:** Image 1. ### 2. Object Detection and Classification: - **Objects Detected:** Text elements in the image. - **Key Features:** - Blocks of textual elements distributed evenly. - Headings for different sections. - Bulleted lists and paragraphs. ### 4. Text Analysis: - **Content of the Text:** - Headings and Section Identifiers: - "4.4.8 Neparametrické vyhodnocení" - "4.5 Dokumentace" - Bulleted Lists: - Contains details about data portion under "Data záhlaví:". - The results under "Výsledky:". - Text Descriptions: - Section 4.4.8 discusses the conditions under which non-parametric evaluation is necessary due to the observed discrepancies among measured values. - Section 4.5 elaborates on the type of documentation required from MFU for certain characteristics. - **Significance:** - The text provides detailed guidelines and protocols for statistical evaluations and documentation within a technical or quality control context. This is crucial for ensuring compliance and standardization. ### 9. Perspective and Composition: - **Perspective:** The document is scanned from a flat, birds-eye view, indicating it is likely a scanned page from a larger document. - **Composition:** - Structured formally with headings, subheadings, bulleted lists, and ordered paragraphs. ### 13. Graph Numbers: - **Data Points:** - The text does not include specific numeric data points but does refer to quantities and results that would typically be numerical, such as the number of sampled points, number of outliers, and median values. ### Prozessbeschreibungen (Process Descriptions): - **Processes Detailed:** - The documentation process for statistical evaluations of manufacturing processes. - Steps for graphical representations, histogram adjustments, and the use of distribution models. ### Typen Bezeichnung (Type Designations): - **Types/Categories:** - Evaluations and documentation processes categorized by: - Graphically represented values. - Histograms and distribution model fits. - Evaluated test results (deviation, positional accuracy, and distribution model adherence). ### Trend and Interpretation: - **Trends:** - Emphasis on non-parametric evaluation when discrepancies are found. - Detailed documentation requirements indicating a trend towards meticulous record-keeping and strict adherence to quality standards. ### Flow and Interpretation: - The structure of the document suggests a flow from identifying the need for non-parametric evaluation, through to detailed documentation requirements and specific results recording. ### Summary: This document segment outlines specific statistical evaluation processes and documentation requirements, particularly focusing on quality control measures within manufacturing processes. The emphasis on non-parametric evaluation and detailed documentation suggests stringent adherence to quality standards and regulatory compliance. #################### File: VW%2010130_CS.pdf Page: 28 Context: 4.6 Posouzení výsledku Na následující posouzení výsledku závisí, zda je možno vyhodnotit stroj z hlediska výroby sledovaných charakteristik jako způsobilý. Pokud jsou během vyhodnocení zjištěny odchylky hodnoty, je nutno zjistit jejich příčinu. Odchylky hodnoty mohou být způsobeny pochybným měřením nebo též, byly jako jakékoli jiné doby jiné jiné než normální. V opačném případě není možné říci, jaké hodnoty, pak by mělo být více než 5 % nebo více z 2 hodnot týchž jako odchylky hodnoty, pak je nutno prověřit, zda nejsou chyby procesu prověřování. MFU je potom nutno případech zopakovat. Pokud se poloha výroby významně změnila, pak musí být zpravdlila změna jejich příčina a musí být akceptovatelný účinek, aby byl splněn předpoklad pro způsobilost stroje (vyjímka platí pro poslední odstavec tohoto oddílu). Pokud existuje neparametrické vyhodnocení na základě signifikantních odchylek od stanoveného modelu a pokud lze posuzované charakteristiky teoreticky přiradit příslušné distribuční model, pak musí být změna příčinu a musí být akceptovatelný účinek, aby byl splněn předpoklad pro způsobilost stroje (vyjímka viz poslední odstavec tohoto oddílu). Pokud není dohodnuto jinak, musí být zjištěné hodnoty způsobilosti při efektivním rozsahu vzorku \( n_b \geq 50 \) (bez odchylek hodnot) splňovat požadavek \[ c_{m}^{2} = 2.0 \, c_{m}^{2} < 1.67 \text{ pro oboustranné tolerovanou charakteristiku} \] \[ c_{m} = 1.67 \text{ pro jednostranné tolerovanou charakteristiku} \] aby bylo možno stroj posoudit jako způsobilý. Pritom je nutno pro srovnání s mezími hodnotami zakotvit zjištěné charakteristiky způsobilosti na dvě desetinná místa, také např. zjištěná hodnota \( c_{k1} = 1.6545 \) pro příslušné zakotvení na 1.67 ještě splňuje požadavek. Pokud efektivním rozsahu vzorku \( 20 \leq n \leq 50 \) je nutno dodržet příslušné výšky hodnoty. Pro některé rozsahy hodnot jako je tabulka 2 uvedeny příslušné mezní hodnoty. Při sjednaní jiné mezní hodnoty na bázi \( n_b \leq 50 \) je nutno příslušné mezní hodnoty zjistit podle vzorců \((3.7) \text{ az } (3.9)\). ## Tabulka 3 – Mezi hodnoty pro způsobilost stroje pro \( 20 \leq n \leq 50 \) | \( n \) | \( \overline{c_m} \) | \( c_m \) | |---------|-----------------|---------| | 20 | 2.28 | 1.93 | | 25 | 2.19 | 1.85 | | 30 | 2.13 | 1.79 | | 35 | 2.05 | 1.74 | | 40 | 1.94 | 1.67 | | 50 | 1.80 | 1.67 | Při vyplynutí hodnoty způsobilosti, která je níže než příslušná mezní hodnota, pak je nutno stroj posoudit jako nezpůsobilý. Image Analysis: ### Analysis of the Attached Visual Content #### Localization and Attribution - **Image 1:** There is only one page containing multiple sections and a table located near the bottom of the page. #### Text Analysis - **Extracted Text:** - Title: "4.6 Posouzení výsledku" - Section headers, paragraphs, and explanations in the Czech language discussing the statistical evaluation of results. - A footnote highlighted with a superscript '10'. #### Diagram and Chart Analysis - **Table Analysis (Tabulka 3 - Mezní hodnoty pro způsobilost stroje pro 20 ≤ n e ≤ 50):** - The table presents "Mezní hodnoty pro způsobilost stroje" (Machine capability limit values) for specific sample sizes. - **Columns:** - **ne:** The sample series sizes (e.g., 20, 25, 30, 35, 40, 45, 50). - **cmk:** Process capability index for a two-sided tolerance. - **cmk:** Process capability index for a one-sided tolerance. - The values in the table: - For ne 20: cmk2 = 2.28, cmk1 = 1.93 - For ne 25: cmk2 = 2.19, cmk1 = 1.85 - For ne 30: cmk2 = 2.13, cmk1 = 1.79 - For ne 35: cmk2 = 2.06, cmk1 = 1.73 - For ne 40: cmk2 = 2.00, cmk1 = 1.67 - For ne 45: cmk2 = 2.00, cmk1 = 1.67 - For ne 50: cmk2 = 2.00, cmk1 = 1.67 #### Contextual Significance - This text appears to be an excerpt from a technical or quality control document, potentially from a manufacturing process evaluation. - The significance centers around evaluating machine capability, using statistical benchmarks to ensure quality and precision in production. #### Typen Bezeichnung (Type Designations) - **Types or Categories Mentioned:** - odchyle (deviation) - mezní hodnoty (threshold values) - způsobilost stroje (machine capability) #### Trend and Interpretation - **Trend:** - The table shows a decreasing trend in cmk values as the sample size increases from 20 to 35, after which it stabilizes at 2.00 for two-sided tolerance and 1.67 for one-sided tolerance. - **Interpretation:** - This trend indicates that smaller sample sizes require higher capability indices, possibly due to higher variability and uncertainty in measurements. #################### File: VW%2010130_CS.pdf Page: 28 Context: #### Tables - **Table Content Description:** - **ne:** Represents the sample sizes. - **cmk2** and **cmk1:** Represent the capability indices for two-sided and one-sided tolerances, respectively. - **Data Points:** - The table provides specific value thresholds required for machine capability validation. Overall, the document is focused on machine capability evaluation using statistical methods, emphasizing the importance of adherence to specified thresholds in manufacturing processes. #################### File: VW%2010130_CS.pdf Page: 29 Context: # Strana 29 VW 101 30: 2005-02 Při zjištěné hodnotě způsobilosti \( C_{mk} \) = 2,33 (odpovídá 14 a) a pro obustraně tolerované charakteristiky dodatečné při \( C_{mk} \) ≥ 2,67 (odpovídá 16 b) lze stroj z hlediska sledovaných charakteristik také nezávisle na signifikantní změně polohy nebo odchylech od stanoveného distribučního modelu posoudit jako způsobilý. ## 4.7 Optimalizace strojů Pro případ, že by nebylo možno z hlediska prověřovaných charakteristik prokázat způsobilost stroje, jsou nutná opatření pro optimalizaci stroje. Za tímto účelem je nutno identifikovat příslušné vlivy (např. pomocí statistické metody zkoušek DOE) a odstranit je. ## 4.8 Nakládání a nezpůsobilými stroji Pokud nelze způsobilost stroje dosáhnout ekonomickými účely při optimalizaci, může být nejprve pomocí statistického výpočtu tolerance podle VW 01057 prověřeno, zda je možné dosáhnout způsobilosti stroje prostřednictvím rozšířené tolerance. Pokud není ani tímto opatřením možné dosáhnout způsobilosti stroje, je nutno se rozhodnout, zda bude stroj převzat podle následujících pravidel, nebo nikoliv. Tato zvláštní pravidla by měla obsahovat následující body: - zdůvodnění pro přejímku - vyhodnocení rizika a nákladů - případné omezené podmínky pro výrobu a dodatečné podmínky pro zkoušky - uvedení zodpovědností Image Analysis: **Image Analysis Report:** ### Localization and Attribution: - **Image Number:** 1 (Only one image is present on the page). ### Text Analysis: - **Detected Text:** ``` Strana 29 VW 101 30: 2005-02 Při zjištěné hodnotě způsobilosti č_mk ≥ 2,33 (odpovídá 14 σ) a pro oboustranně tolerované charakteristiky dodatečné při č_mk ≥ 2,67 (odpovídá 16 σ) lze stroj z hlediska sledované charakteristiky také nezávisle na signifikantní změně polohy nebo odchylce od stanoveného distribučního modelu posoudit jako způsobilý. 4.7 Optimalizace stroje Pro případ, že by nebylo možno z hlediska prověřované charakteristiky prokázat způsobilost stroje, jsou nutná opatření pro optimalizaci stroje. Za tímto účelem je nutno identifikovat příslušné vlivy (např. pomocí statistické metodiky zkoušek DOE) a odstranit je. 4.8 Nakládání s nezpůsobilými stroji Pokud nelze způsobilost stroje dosáhnout ekonomicky účelnými optimalizacemi, pak by mělo být nejprve pomocí statistického výpočtu tolerance podle VW 01057 pověřeno, zda je možno pro dosažení způsobilosti stroje provést rozšíření tolerance. Pokud není ani tímto opatřením možno dosáhnout způsobilosti stroje, je nutno se rozhodnout, zda bude stroj převzat podle přesně specifikovaných zvláštních pravidel, nebo nikoliv. Tato zvláštní pravidla by měla obsahovat následující body: - zdůvodnění pro přejímku - vyhodnocení rizika a nákladů - případné omezené podmínky pro výrobu a dodatečné podmínky pro zkoušky - uvedení zodpovědnosti ``` - **Content Analysis:** - **Section 4.7: Optimalizace stroje** - This section discusses the necessary measures for optimizing machinery in case its capability cannot be proven with respect to examined characteristics. It emphasizes identifying and removing relevant influences using statistical testing methods (e.g., DOE tests). - **Section 4.8: Nakládání s nezpůsobilými stroji** - This section provides guidance on handling non-compliant machinery. It suggests first utilizing statistical tolerance calculations as per VW 01057 to determine the feasibility of extending tolerance to achieve capability. If this is not possible, it outlines the decision-making process for whether to accept the machine based on specific rules, which should include: - Justification for acceptance - Risk and cost assessment - Potential restrictive conditions for production and additional testing conditions - Accountability ### Contextual Significance: - **Document Context:** - The image likely represents a technical manual or guideline related to the optimization and management of machinery within a manufacturing or industrial setting. The text provides detailed procedures and considerations for ensuring machinery meets required specifications and how to handle situations when it does not. - **Significance of the Text:** - The text is critical for quality control and process optimization in manufacturing. It ensures that machinery operates within acceptable parameters and outlines clear steps for addressing deviations, emphasizing statistical validation and cost-effective measures. Overall, the detailed text provides significant insight into the technical and procedural standards necessary for ensuring machinery operability and compliance in an industrial context. #################### File: VW%2010130_CS.pdf Page: 30 Context: # 5 Příklady ## Příklad 1 Průměr hřídele s jmenovitým průměrem 20 mm, minimálním rozměrem \( G_u = 19,7 \, \text{mm} \) a maximálním rozměrem \( G_s = 20,3 \, \text{mm} \). Z = 50 naměřených hodnot vzorku nevyplynuly ve statistických testech žádné odchylkové hodnoty, žádné signifikantní změny polohy a žádné signifikantní odchylky od očekávaného normálního rozdělení. Byly zjištěny následující charakteristiky namátkových vzorků: - \( \bar{x} = 20,05 \) - \( a = s = 0,05 \) Proto podle vzorce (2.11) z charakteristik vzorků vyplynuly následující odhadnuté hodnoty hranic rozptylu pro normální rozdělení základní soubor: \[ x_{0.975} = \bar{x} + a = (20,05 - 3 \cdot 0,05) \, \text{mm} = 19,9 \, \text{mm} \] a z toho nakonec vyplynou následující charakteristiky způsobilosti: \[ G_u - G_s = 20,3 - 19,7 = 2,0 \] \[ \bar{c}_m = \min \left( \frac{G_u - G_s}{x_{0.865}} \right) = \frac{20,3 - 19,7}{x_{0.136} \cdot a} = \frac{2,0}{x_{0.865}} = 2,0 \] Pomocí zjištěných charakteristik způsobilosti se tak prokázalo, že stroj z hlediska posuzovaného průměru hřídele právě ještě splňuje požadavky na způsobilost. Výsledek je znázorněn na obrázku 12. ## Obrázek 12 **Příklad výroby s modelem normálního rozdělení a charakteristikami způsobilosti** \( C_m = 2,0, \; C_{m} = 1,67 \) Image Analysis: ### Analysis of Provided Image #### 1. Localization and Attribution: - **Image 1**: The entire page consists mainly of textual content with two subsections. There is one specific visual component: - **Image 1**: Located at the bottom of the page (graph/chart). #### 2. Object Detection and Classification: - **Image 1**: The objects in the image include: - A normal distribution graph (bell curve) indicating statistical data. - Vertical lines and bars illustrating different data points. #### 3. Scene and Activity Analysis: - **Image 1**: The scene focuses on a normal distribution graph used to explain statistical characteristics of a manufacturing process. The main activity is the visualization of data to interpret manufacturing consistency and capability. #### 4. Text Analysis: - **Text Content**: - **Header**: "Strana 30 VW 101 30: 2005-02" indicating the document page and reference number. - **Title**: "5 Příklady" which means "5 Examples." - **Subsection**: "Příklad 1" meaning "Example 1." - The subsequent text includes detailed statistical calculations and assessments related to a production process. - **Figures and Equation Descriptions**: This includes formulae and symbols for statistical parameters such as mean (\(\mu\)), standard deviation (\(\sigma\)), and capability indices (\(C_m\), \(C_{mk}\)). - **Diagram Caption**: "Obrázek 12 – Příklad výroby s modelem normálního rozdělení a charakteristikami způsobilosti C_m = 2,0 a C_{mk} = 1,67". This describes the graph as an example of production with a normal distribution model and certain capability characteristics. #### 5. Diagram and Chart Analysis: - **Image 1**: - **Data Range**: X-axis represents 'Naměřená hodnota' (Measured Value); Y-axis represents 'Četnost' (Frequency). - **Graph Interpretation**: The normal distribution graph displays observed variations in production measurements. The central peak represents the average value with spread indicating the standard deviation. - **Key Insight**: A capability index (\(C_m = 2.0\), \(C_{mk} = 1.67\)) signifies the process's ability to produce within specified limits. #### 14. Tables: - **Equation and Data Interpretation**: - Various equations are presented with specific values and parameters that explain the calculation of process capability and variability. - Capabilities depicted through: - \(C_m = \frac{20,3 - 19,7}{2 \cdot 0,15}\approx 2.0\) - \(C_{mk} = \min(\frac{20,3 - 20,05}{3 \cdot 0,15}, \frac{20,05 - 19,7}{3 \cdot 0,15}) \approx 1.67\) ### Additional Observations: #### Anomaly Detection: - No noticeable anomalies in the diagram or text. #### Color Analysis: - The document is primarily grayscale with black text and lines to denote various statistical data points clearly. #### Perspective and Composition: - Document Layout: Standard vertical orientation with sequential flow from top to bottom. - Graph Composition: Center-aligned at the bottom of the page with clear axes and labeled sections. #### Contextual Significance: - The provided example is an instructional aid focused on demonstrating statistical quality control in a manufacturing environment. The integration of text and graph aids in explaining the practical application of theoretical statistical concepts. #### Process Descriptions: - Describes a process for evaluating the manufacturing capability of a cylindrical component, involving mean diameter calculations and statistical capability indices. By analyzing the image and its content, we can conclude that it serves as an educational example of statistical quality control in a manufacturing context, providing detailed calculations and graphical representations to explain the processes involved. #################### File: VW%2010130_CS.pdf Page: 31 Context: # Příklad 2: Otvór s maximální odchylkou polohy \( G_s = 0,2 \, \text{mm} \). Z = 50 naměřených hodnot vzorku nevyplnily ve statistických testech žádné odchyle. Žádné signifikantní změny polohy a žádné signifikantní odchylky od očekávaného Rayleighova rozdělení. Byly zjištěny následující charakteristiky naměřených vzorků: \[ \overline{\mu} = -0,038 \, \text{mm} \] \[ a = s = 0,02 \, \text{mm} \\ \text{Z charakteristiky způsobilosti vyplyne poměr} \, \frac{\overline{\mu}}{a} = \frac{-0,038}{0,02} = -1,9 \] Protože tato hodnota na základě náhodného rozptylu charakteristik vzorků menší, než zmíněná hodnota 1,9131 podle podmínky (2.23), je poměr nastaven na tuto nemí hodnotu, z čehož opět vyplývá excentricita \( z = 0 \). Tak lze druhu hodnotu parametru přizpůsobovaného Rayleighova rozdělení spočítat následujícím způsobem podle zvláštního případu (2.26): \[ \alpha_n = 1,526 - 0,02 = 1,506 \, 0,0305\, \text{mm} \] Ze vzorců (2.27) vyplývají odhadované hodnoty hranic oblasti rozptylu: \[ x_{0,865} = 5,5485 - 0,02 = 5,5485 - 0,2111 \] \[ x_{0,135} = 0,0773 - 0,0773 - 0,02 \, 0,0016 \, \text{mm} \] Ze vzorců (2.3) a (2.4) nakonec vyplynou následující charakteristiky způsobilosti: \[ \overline{c}_m = \frac{x_{0,865}-\overline{\mu}}{a} = \frac{5,86965 - (-0,038)}{0,111 - 0,0016} = 1,83 \\ G_s = \frac{x_{0,865} - 0,2}{0,2 - 0,038} = \frac{5,86965 - 0,2}{0,2 - 0,038} = 2,22 \] Výsledky vyhodnocení je znázorněno na obrázku 13. ### Obrázek 13 – Příklad výroby s modelem Rayleighova rozdělení a charakteristikami způsobilosti \( \overline{c}_m = 1,83 \, \text{a} \, c_m^k = 2,22 \) Pomocí zjištěné charakteristiky \( c_m \) se tak prokáže, že stroj z hlediska odchylek polohy otvoru dobře splňuje požadavky na způsobilost. Pro hodnotu \( G_s \) sice neví i jednoduché náhory tolerovaném případě definována žádné mezní hodnotu, avšak porovnáním s hodnotou \( c_m \) vyplývá informace o poloze výroby, přičemž nežší hodnota \( G_s \) udává, že leží spíše blíže přirozené nulové hranici než maximálním rozměrům. Image Analysis: Here is a comprehensive examination of the attached visual content based on the requested aspects: --- ### 1. Localization and Attribution: - **Image Number:** 1 - **Number of Images on Page:** 1 ### 2. Object Detection and Classification: - **Image 1:** - **Objects Detected:** - A graph with labeled axes - Text explanations and calculations ### 3. Scene and Activity Analysis: - **Image 1:** - **Scene Description:** The scene includes a page of text with a mathematical example (Příklad 2), along with calculations and explanations of various statistical characteristics and a histogram (Obrázek 13). - **Activities:** - Displaying data analysis - Describing analytical results ### 4. Text Analysis: - **Text Detected:** - **Příklad 2:** - Detailed explanation of the example including statistical tests and calculations. - Includes various calculated parameters: - \(\hat{\mu} = -0,038 mm\), \(a = s = 0,02 mm\) - Other significant formulas and statistical parameters. - **Graph Title:** - "Obrázek 13 – Příklad výroby s modelem Rayleighova rozdělení a charakteristikami způsobilosti \(c_m = 1,83 a c_{mk} = 2,22\)" - **Graph Axis Labels:** - Vertical Axis: "Četnost" (Frequency) - Horizontal Axis: "Naměřená hodnota" (Measured Value) ### 5. Diagram and Chart Analysis: - **Image 1:** - **Type of Diagram/Chart:** - A histogram showing the distribution of measured values. - **Axes, Scales, and Legends:** - **Vertical Axis (Frequency)** labeled "Četnost" - **Horizontal Axis (Measured Value)** labeled "Naměřená hodnota" - **Insights:** - The histogram depicts how the measured values are distributed and compares these with certain statistical thresholds. ### 13. Graph Numbers: - **Data Points and Values:** - Numerical data points and threshold values are derived from statistical properties: - \( \hat{\mu} \) - \( \hat{\sigma} \) - \( a \) - \( c_m \) - \( c_{mk} \) ### Additional Aspects: - **Ablaufprozesse (Process Flows):** - The process described includes taking 50 measurements and assessing their statistical properties. - **Prozessbeschreibungen (Process Descriptions):** - Step-by-step calculations of statistical measures. - **Trend and Interpretation:** - Comparison of \( \hat{\mu} \) and \( \hat{\sigma} \) with expected values. - Analysis of machine capability metrics \( c_m \) and \( c_{mk} \). --- ### Contextual Significance: - **Significance:** - The image contributes to a technical or statistical analysis document, enhancing understanding of machine capability and variation using a Rayleigh distribution model. ### Metadata Analysis: - There is no visible metadata in the image to contribute to the analysis. --- This examination integrates multiple requested aspects of the visual content, providing a detailed overview and interpretation of the text, diagram, and contextual significance. #################### File: VW%2010130_CS.pdf Page: 32 Context: # Strana 32 VW 101 30: 2005-02 ## Příklad 3: Průměr hřídele s jmenovitým průměrem 20 mm, minimálním rozměrem Gₓ = 19,7 mm a maximálním rozměrem Gₕ = 20,3 mm. Z = 50 naměřených hodnot vzorku nevyplynuly ve statistických testech žádné odlehlé hodnoty a žádné signifikantní změny polohy, avšak signifikantní odchylka od očekávaného normálního rozdělení. Proto se provedly nepramenité výpočty podle oddílu 3.2.2. Za tímto účelem byly zjištěny následující charakteristiky namátkových vzorků: - \[ \bar{x}_{s} = 20,02 \, \text{mm} \] - \[ x_{\text{max}} = 20,19 \, \text{mm} \] - \[ x_{\text{min}} = 19,85 \, \text{mm} \] **Opravným faktorem podle vzorce (2.38) a tabulky 1:** \[ k = \frac{d}{4} = 1,33 \] **Rozpětí podle vzorce (2.37):** \[ R = x_{\text{max}} - x_{\text{min}} = (20,19 - 19,85) \, \text{mm} = 0,34 \, \text{mm} \] **Podle vzorce (2.36):** \[ \bar{x}_{c} = \frac{x_{\text{max}} + x_{\text{min}}}{2} = \frac{20,19 + 19,85}{2} = 20,02 \, \text{mm} \] **Odvozené hodnoty pro hranice oblasti rozptylu podle vzorce (2.35):** \[ \bar{x}_{k} = \bar{x}_{c} \pm k \cdot \frac{R}{2} \] \[ \bar{x}_{k} = 20,02 \pm 1,33 \cdot 0,34 \] \[ \bar{x}_{k} = 20,02 \pm 0,45 \approx 20,246 \, \text{mm}, \, \sigma_{k} = 19,794 \, \text{mm} \] **Tak ze vzorců (2.29) a (2.30) vyplynuly následující charakteristiky způsobilosti:** \[ c_{m} = \frac{G_{u} - \bar{x}_{s}}{G_{u} - G_{l}} = \frac{20,3 - 19,7}{20,3 - 19,7} = 1,33 \] \[ c_{m} = \min\left(1, \frac{\bar{x}_{s} - x_{\text{min}}}{x_{\text{max}} - \bar{x}_{s}} \right) \] \[ c_{m} = \frac{20,02 - 19,85}{20,19 - 20,02} = 1,24 \] **Výsledek vyhodnocení je znázorněn na obrázku 14.** ## Obrázek 14 **Příklad výrobů s definovaným distribučním modelem s charakteristikami způsobilosti \( C_{m} = 1,33 \) a \( C_{mk} = 1,24 \)** Ze zjištěných charakteristik způsobilosti tak vyplývá, že stroj z hlediska posuzované charakteristiky nesplňuje požadavky na způsobilost. Zajímavou informací této souvislosti poskytuje signifikantní odchylka od očekávaného normálního rozdělení. Neboť z toho je zřejmý potenciál pro optimalizaci, jako zde v případě smíšeného rozdělení. Image Analysis: ### Localization and Attribution: - **Image 1:** This image occupies the top part of the document. It consists of a textual explanation followed by mathematical formulas. - **Image 2:** A histogram chart located in the lower part of the document, illustrating data related to the preceding textual content. ### Text Analysis (Image 1): - **Image 1:** - The text appears to be technical in nature, likely focusing on statistical analysis related to a manufacturing process. - The document starts by specifying a standard diameter of a shaft (20 mm) and discusses the statistical properties of a sample of 50 measurements with no significant deviation detected from the expected normal distribution. - Several mathematical formulas and calculations follow, focusing on mean, variance, and corrected factors. Each formula references specific equations, such as `(2.35)`, `(2.36)`, and `(2.38)`, which likely belong to a larger set of rules or standards. ### Diagram and Chart Analysis (Image 2): - **Image 2 (Chart):** - The chart is titled "Obrázek 14 – Příklad výroby s definovaným distribučním modelem s charakteristikami způsobilosti Cm = 1,33 a Cmk = 1,24". - **Axes:** - X-axis labeled "Naměřená hodnota" and represents measured values ranging from 19.7 to 20.4. - Y-axis labeled "četnost" and represents frequency. - **Bars in Histogram:** - The histogram displays frequency data for specific measurement ranges. - Key values such as \( G_u = 20.3 \) mm, \( G_m = 20.2 \) mm, and \( G_l = 19.9 \) mm are highlighted within the chart. - **Significance:** - The chart exemplifies the distribution of measurements with specific capability indices \( C_m \) and \( C_{mk} \). - The values and distribution imply the evaluated samples generally fit within the normal distribution but highlight areas for potential optimization around smíšené (mixed) distribution. ### Anomaly Detection: - No evident anomalies in both images. The histogram and the accompanying formulas and text appear consistent and relevant to each other. ### Color Analysis (Image 2): - **Image 2:** - Primarily grayscale with key features such as bars, labels, and lines. The histogram bars have varying shades to differentiate frequencies clearly. ### Perspective and Composition: - **Image 1:** - The text is written in a structured, sequential format, with formulas and calculations following a logical order. - **Image 2:** - The histogram uses a standardized format common for statistical data, with a clear and concise layout to enhance readability and interpretability. ### Contextual Significance: - **Overall Contribution:** - The document, likely a technical report, uses the histogram to visualize the statistical findings complementing the text and mathematical analysis. It underscores the consistency and accuracy of the manufacturing process measurements. ### Graph and Trend Analysis: - **Image 2:** - The histogram suggests that most measurements lie within a narrow range close to the mean value, signifying a well-maintained process with potential areas for improvement based on capability indices. ### Conclusion: This document segment, including both text and histogram, provides a thorough examination of a manufacturing process's statistical properties. The combination of detailed textual analysis and visual representation form a comprehensive assessment indicating the process efficiency and areas for potential optimization. #################### File: VW%2010130_CS.pdf Page: 33 Context: # 6 Související podklady - **VW 010 56** Zeichnungen; Form- und Lagetoleranzen [Výkresy; Tvarové a polohové toleranace] - **VW 010 57** Statistische Toleranzrechnung von Maßketten [Statistické výpočty tolerancí rozměrových řetězců] - **VW 101 33** Test auf Ausreißer [Test odlehlých hodnot] - **DIN 55319** Qualitätsfähigkeitskenngrößen [Charakteristiky kvalitativní způsobilosti] - **ISO 5479** Statistical interpretation of data - Tests for departure from the normal distribution [Statistická interpretace dat – testy odchylek od normálního rozdělení] # 7 Odkazy na literaturu 1. Graf, Henning, Stange, Willich. Formeln und Tabellen der angewandten mathematischen Statistik, Springer-Verlag, Dritte Auflage, 1987 [Graf, Henning, Stange, Willich, Vzorce a tabulky aplikované matematické statistiky, Springer-Verlag, Dritte Auflage, 1987] 2. Kühlmeyer M. Statistische Auswertungsmethoden für Ingenieure, Springer-Verlag, 2001 [Kühlmeyer M., Statistické vyhodnocovací metody pro inženýry, Springer-Verlag, 2001] Image Analysis: ### Image Analysis #### 1. Localization and Attribution - **Image Identification**: This is the sole image provided. - **Image Numbering**: Image 1. #### 2. Object Detection and Classification - **Detected Objects**: - Text blocks. - Numerals indicating sections (6 and 7). - Reference codes (VW 010 56, VW 010 57, VW 101 33, DIN 55319, ISO 5479). - Reference texts for literature sources [1] and [2]. #### 4. Text Analysis **Detected Text**: - **Section 6** (Související podklady): - VW 010 56 Zeichnungen; Form- und Lagetoleranzen [Výkresy; Tvarové a polohové tolerance] - VW 010 57 Statistische Toleranzrechnung von Maßketten [Statistické výpočty tolerancí rozměrových řetězců] - VW 101 33 Test auf Ausreißer [Test odlehlých hodnot] - DIN 55319 Qualitätsfähigkeitskenngrößen [Charakteristiky kvalitativní způsobilosti] - ISO 5479 Statistical interpretation of data - Tests for departure from the normal distribution [Statistická interpretace dat – testy odchylek od normálního rozdělení] - **Section 7** (Odkazy na literaturu): - [1] Graf, Henning, Stange, WIlrich, Formeln und Tabellen der angewandten mathematischen Statistik. Springer-Verlag. Dritte Auflage. 1987 [Graf, Henning, Stange, Wilrich, Vzorce a tabulky aplikované matematické statistiky, Springer-Verlag, Dritte Auflage, 1987] - [2] Kühlmeyer M., Statistische Auswertungsmethoden für Ingenieure, Springer-Verlag, 2001 [Kühlmeyer M., Statistické vyhodnocovací metody pro inženýry, Springer-Verlag, 2001] **Content Analysis**: - **Section 6** lists various standards and tests related to statistical tolerance calculation, quality capability indexes, and statistical data interpretation. Each item includes both the original German titles and Czech translations. - **Section 7** lists references to literature relevant to the topics discussed in Section 6. These references include detailed bibliographic information about books on applied mathematical statistics and statistical evaluation methods for engineers. #### 9. Perspective and Composition - **Perspective**: The image is a direct top-view scan of a document page, likely extracted from a technical or academic publication. - **Composition**: The text is structured into two main sections (Související podklady and Odkazy na literaturu) with bullets and references clearly listed and neatly formatted. #### 10. Contextual Significance - **Document Context**: This page appears to be part of a technical document or a standardization handbook related to statistical methods in engineering and manufacturing. - **Contribution to Overall Message**: The sections provide critical references and background information necessary for understanding statistical tolerance calculations and quality control measures. They also direct the reader to additional resources and literature for further reading. #### 12. Graph and Trend Analysis - **Type Designations**: Standards and references listed in Section 6 and Section 7 are designated by specific codes (e.g., VW 010 56, DIN 55319). - **Trend and Interpretation**: The listed standards indicate a trend towards rigorous, standardized approaches in statistical process control and quality management in manufacturing. ### Summary The image presents a well-structured reference page from a technical document, listing standards (in two languages) and literature sources related to statistical methods in engineering. It emphasizes scholarly references and standardized practices in statistical tolerance and quality assessment. #################### File: VW%2010130_CS.pdf Page: 34 Context: # 8 Seznam hesel | Heslo | Strana | Heslo | Strana | |------------------------------------------------|----------|------------------------------------------------|----------| | A | | O | | | a riziko | 20 | očekávaná hodnota v rozdělení 𝑖 | 17 | | absolutní činnost a | 10, 17 | odběr namátkových vzorků | 24 | | absolutní distribuční funkce 𝑓 | 17 | odhad / odhadované hodnoty | 8,9 | | alternativní hypotéza | 20 | odlehlé hodnoty | 20,26 | | B | | omezená MFU | 25 | | b riziko | 20 | opravný faktor | 29 | | C | | P | | | capability | 3 | parametr rozdělení | 3 | | D | | podmínky pro MFU | 24 | | distribuční funkce 𝑓(𝑥) | 5 | poloha | 3 | | dokumentace | 27 | polohy výroby | 3,28 | | druh charakteristiky | 4,25 | poruchy stroje | 24 | | E | | pořadí výroby | 28 | | efektivní rozsah vzorku 𝑛𝑒 | 10, 24 | posun nulového bodu | 6 | | Epps-Pulleyův test | 20,26 | použití zkušebních prostředků | 24 | | extrakce z | 7 | prahová hodnota | 20 | | F | | pravděpodobnost 𝑝 | 5 | | funkce hustoty 𝑓(𝑥) | 24 | pravděpodobnost sítě | 27 | | funkce hustoty pravděpodobnosti 𝑓(𝑥) | 5 | průběh trendu | 26 | | H | | R | | | Hamplevit test | 20 | radiální odchylka | 7 | | hladina významnosti a | 20 | Rayleighovo rozdělení | 7, 13 | | hodnota charakteristiky | 17 | rozdělení | 4 | | hraniče konfidenčního intervalu | 18 | rozdělení četností | 10, 17 | | hranice oblasti rozptylu | 3, 10 | rozdělení či kvadrát | 18 | | K | | rozptyl 𝑐² | 4 | | charakteristiky způsobilosti 𝑐𝑚, 𝑎 | 3, 9 | rozptyl výroby | 3,8 | | koeficient spolehlivosti | 20, 26 | rozsah vzorků | 24 | | kvalita předběžně obhospodařené kvantili | 24 | rozšíření tolerance | 29 | | L | | Run test | 20 | | maximální rozměr 𝐺𝑜 | 3, 9 | | | | medián | 16 | standardizované normální rozdělení | 26,32 | | metoda měření | 24 | - U transformace | 5 | | mezičinné hodnoty pro způsobilost stroje | 18,28 | - distribuční funkce 𝑓(𝑥) | 5 | | minimální rozměr 𝐺𝑢 | 3,9 | - funkce hustoty pravděpodobnosti 𝑓(𝑢) | 5 | Image Analysis: 1. **Localization and Attribution:** - The entire content forms a single image, analyzed as Image 1. 4. **Text Analysis:** - Detected and extracted text: ``` Strana 34 VW 101 30: 2005-02 8 Seznam hesel Heslo Strana Heslo Strana Heslo Strana A náhodné vlivy 3 H ampelvý test 20,26 a riziko 20 neparametrický odhad 16, 27 absolutní četnost a 10, 17 normální rozdělení 4,1 absolutní distribuční funkce A 17 nulová hypotéza 20 alternativní hypotéza 20 P očekávaná hodnota v rozdělení 17 B odběr námatkových vzorků 24 B riziko 20 odhad / odhadované hodnoty 8,9 capability 3 odlehlé hodnoty 20,26 D omezená MFU 25 P distribuční funkce F(x) 5 opravný faktor k 17 diskrétní model 4 optimalizace stroje 29 dokumentace 27 P druh charakteristiky 4,25 parametr rozdělení 3 efektivní rozsah vzorků ne 10, 24 podmínky pro MFU 24 Epps-Pullejv test 20,26 poloha 3 extrémně t 7 polohy výroby 3,28 F poruchy stroje 24 funkce hustoty f(x) 4 pořadí výroby 24 funkce hustoty pravděpodobnosti f(x) 4 posouzení výsledku 28 H posun nulového bodu 6 Hampeiv test 20 použití zkušebních prostředků 24 hladina významnosti a 20 prahová hodnota 20 hodnota charakteristiky 3 pravděpodobnost p 5 hranice konfidenčního intervalu 18 pravděpodobnostní síť 27 hranice oblasti rozptylu 3 průběh trendů 26 Q radiální odchylka r 7 charakteristiky způsobilosti cm, a 3, 9 Rayleighovo rozdělení 7, 13 cpm 20 rozdělení 4 K rozdělení četností 10, 17 koeficient smělpvostí r 7 rozdělení chí kvadrát 18 kvaita předběžného ``` - The text is a table of contents or index for a document in Czech language. It lists topics/terms (Heslo) along with the page numbers (Strana) where those terms can be found. The text is structured in a three-column format, with each column listing different terms and their corresponding page numbers. 5. **Diagram and Chart Analysis:** - There are no diagrams or charts present in the image. 8. **Color Analysis:** - The image is predominantly grayscale with black text on a white background. This type of color scheme is often used for readability and clarity in printed documents. 9. **Perspective and Composition:** - The image is taken from a straight-on perspective, typical for scanned or digitally created documents. - The composition is structured and organized in a tabular format, which aids in searching and referencing specific terms. #################### File: VW%2010130_CS.pdf Page: 34 Context: **Overall Summary:** - The image provides a list of terms and their corresponding page references from what appears to be a technical or academic document. It is organized in an alphabetical manner and is intended to help users quickly locate information about specific topics within the document. The clear and systematic presentation enhances usability for readers. #################### File: VW%2010130_CS.pdf Page: 35 Context: # Heslo | Heslo | Strana | Heslo | Strana | |--------------------------------------------|--------------|-------------------------------------------|--------------| | Standardní odchylka σ | 4, 10 | - jednozdanné dolu | 9, 16 | | statistická podlož pod oblast | 18 | - oboustranně | 9, 16 | | statistické testy | 20 | upravené hranice způsobilosti | 19, 28 | | stroj zahřátí na provozní teplotu | 24 | V | | | střední hodnota m | 4.1 | vyhodnocení dat | | | stupeň volnosti | 18 | Výjimka / přenastavení nářadí | 29 | | Swed-Eisenhardtův test | 20 | výpočet statistických tolerancí | | | šířka trůnu Δx | 17 | v rozdělení | | | T | | Weibullovo rozdělení | 5,11 | | test | | | | | - odlehlých hodnot | 20, 26 | zakrouhlo­vání hodnot | 28 | | - stanoveného distribučního modelu | 20, 26 | způsobilosti | | | - změny polohy výroby | 20, 26 | zatříděné naměřené hodnoty | 29 | | toleranční interval | 3, 8 | zjištění způsobilosti | 20 | | tolerovaná charakteristika | 4 | zkušební hodnota | 28 | | - jednozdanně nahoru | 9, 16 | zkušební veličina | 20 | Image Analysis: ### Image Analysis 1. **Localization and Attribution:** - There is only one image on the page. - It is referred to as **Image 1** for the purpose of this analysis. 2. **Text Analysis:** - The image contains a structured list in two columns. - The left column headers translate to "Word" and "Page" in English, and the right column lists numerical values. - The right column headers translate to "Word" and "Page" in English as well, with corresponding values. - The headers suggest this might be a table of contents or an index for a document, as they list terms and corresponding page numbers. - **Detailed Content:** - **Left Column:** - "Standardní odchylka σ" appears on pages 4, 10. - "statistická podílova oblast" appears on page 18. - "statistické testy" on page 20. - Items related to manufacturing processes, tolerance intervals, etc. - **Right Column:** - "jednostranně dolu" and "oboustranně" each appear on pages 9, 10, 16. - "upravěné hranice způsobilotí" spans pages 19, 28. - "výhodnocení dat" is on page 25, among other terms related to data analysis and testing. 3. **Object Detection and Classification:** - The primary object in this image is a textual document, specifically a table. - The main features include headers, rows, and columns filled with text and numerical data. 4. **Color Analysis:** - The image is mostly black text on a white background. - The simplicity of the color scheme ensures high contrast and readability. 5. **Perspective and Composition:** - The perspective is a straightforward, head-on view of the table. - The image is composed of two main columns of text, neatly arranged for clarity. 6. **Contextual Significance:** - This image likely serves as a reference or index within a larger document, possibly a technical manual or a statistical report. - It helps readers locate specific information within the document efficiently. ### Summary: **Image 1** presents a structured table of contents or an index from a document, listing terms related to statistics and manufacturing processes along with their corresponding page numbers. The simple black and white color scheme ensures readability, and the organized composition aids in quick reference. The contextual placement within a larger document implies its role in assisting readers to navigate the contents efficiently. #################### File: 240910_Skoda_Automation_MGH_Portal_direkt.pptx Page: 1 Context: # Skoda SSP Motorgehäuse (MGH) Automation **Date:** 2024-09-13 **Author:** Ralf Haug --- ## Companies Involved - VDF Boehringer - CORCOM - DMC - Feelers - Hessapp - IMRAS - JOBS - Leadwell - AG - Meccanodora - MORARA - Pffiffer - Ramboud - Sackman - Sigma - SMS - SNK - Tacchella - Witzig & Frank Image Analysis: ### Image Analysis #### 1. Localization and Attribution: - **Image 1**: Only one image present on the page, taking up the entire canvas. #### 2. Object Detection and Classification: - **Image 1**: - **Detected Objects**: - Logos of multiple companies/brands at the bottom (e.g., VDF BOEHRINGER, CORCOM, DMC, FEELER, etc.). - A large, complex industrial layout in the background, possibly a factory or manufacturing plant. #### 3. Scene and Activity Analysis: - **Image 1**: - **Scene Description**: The image appears to show an industrial or manufacturing environment. The background consists of a detailed layout of machinery and equipment, possibly automation lines or production zones. - **Activities**: The focus is on automation within the manufacturing industry. #### 4. Text Analysis: - **Image 1**: - **Detected Text**: - "Skoda SSP Motorgehäuse (MGH) Automation" - "2024-09-13, Ralf Haug" - Various brand and company names at the bottom. - **Text Significance**: - The title "Skoda SSP Motorgehäuse (MGH) Automation" suggests that the image pertains to automation in the manufacturing of Skoda engine housing. - The date and name ("2024-09-13, Ralf Haug") likely indicates the creation date of the document and the author’s name. - Company logos and names indicate collaboration or sponsorship by multiple manufacturers and technical solution providers. #### 5. Diagram and Chart Analysis: - **Image 1**: - The background industrial layout could be considered a form of diagram, representing a factory or production setup. #### 8. Color Analysis: - **Image 1**: - **Dominant Colors**: Shades of teal and white. - **Impact on Perception**: The use of teal creates a professional, calm, and industrially focused feel, aligning with the theme of automation and manufacturing. #### 9. Perspective and Composition: - **Image 1**: - **Perspective**: The layout image in the background is depicted from an overhead/bird’s-eye view, providing a comprehensive view of the industrial setup. - **Composition**: - The text and logos are centrally placed overlaid on the complex industrial layout in the background. - Important informational text is positioned centrally to immediately draw attention. #### 10. Contextual Significance: - **Image 1**: - **Overall Message**: - The image aims to provide an overview of an automation project related to Skoda SSP engine housing, associating it with various industry collaborators. - Emphasizes technological integration and automation in manufacturing. ### Conclusion: This image illustrates the automation efforts for Skoda SSP engine housing, prominently featuring a layout of the automation setup and highlighting collaboration with multiple industrial partners. Dominant teal hues and professional composition underscore the technological and industrial focus of the content. #################### File: 240910_Skoda_Automation_MGH_Portal_direkt.pptx Page: 2 Context: # Projektdaten **Kunde:** Skoda, Mlada Boleslav **Werkstück:** Motorgehäuse (MGH) SSP **Taktzeit:** 75s **Terminplan:** TBD **Referenzdokument:** TZ. Linka ebrbnai mactryve skrine elektrophonu SSP v5 DE ## Others **Kontakt MAG EK:** Sonja Haas: [sonja.haas@mag-ias.com](mailto:sonja.haas@mag-ias.com) **Kontakt MAG Planung:** Ralf Haug: [ralf.haug@mag-ias.com](mailto:ralf.haug@mag-ias.com) Image Analysis: ### Localization and Attribution: - **Image Position and Number:** - This is a single image on the page, labeled as **Image 1**. ### Object Detection and Classification: - **Image 1:** Contains text and company logos. - **Company Logos:** VDF BOEHRINGER, MAG, FFG. - **Text Blocks:** Various project-related information. ### Text Analysis: **Image 1:** - **Detected Text (Translated where possible):** - **Projekt Daten (Project Data):** - **Kunde:** Skoda, Mlada Boleslav - **Werkstück:** Motorgehäuse (MGH) SSP (Engine Housing SSP) - **Taktzeit:** 75s (Cycle Time: 75 seconds) - **Terminplan:** (Schedule:) - **Reports:** T.Z. Linka obrábění motorové skříně elektropohonů SSP v5 DE (Production Line for Machining Electric Motor Housings SSP v5 DE) - **Others:** - **Kontakt MAG EK:** Sonja Haas; sonja.haas@mag-ias.com - **Kontakt MAG Planung:** Ralf Haug; ralf.haug@mag-ias.com - **Additional Details:** 18.09.2024 (Date: September 18, 2024) - **Analysis of Text Content and Significance:** - The image presents essential project data for a client named Skoda, related to the production of motor housings with a cycle time of 75 seconds. - Contact information for key personnel involved in the project is provided. - The text elucidates the entities responsible for the project and their roles. ### Color Analysis: **Image 1:** - **Dominant Colors:** - **Teal/Green:** Used predominantly for text. - **Red:** "vorab" (preliminary) watermark. - **Blue:** Logos (VDF BOEHRINGER, MAG). - **White:** Background. - **Impact on Perception:** - The use of teal/green is calming and professional, suggesting reliability. - The red watermark "vorab" indicates the document might be a draft or preliminary version. - The white background ensures readability and a clean presentation. ### Perspective and Composition: **Image 1:** - **Perspective:** Straight-on view, typical of document presentations. - **Composition:** - The image is neatly organized with text aligned to the left and logos positioned on the top right. - Contact information and other details are distributed logically, making the document easy to navigate. - **Element Arrangement:** - Hierarchical presentation of project data, making it simple to understand at a glance. ### Contextual Significance: **Image 1:** - **Contextual Analysis:** - The image appears to be a slide from a professional presentation deck related to automotive manufacturing. - It contributes to the overall theme by highlighting crucial project details and contacts associated with the Skoda engine housing project. ### Typen Bezeichnung (Type Designations): - **Project-Related Types:** - The type of material/workpiece involved is designated as "Motorgehäuse (MGH) SSP,” indicating a focus on engine housings for a specific Skoda project. ### Summary: **Image 1** provides a detailed overview of a project involving Skoda and the machining of engine housings. Key details include project data, cycle time, involved parties, and contact information. The professional layout and color scheme support clarity and ease in conveying essential information, while the red "vorab" watermark suggests it is a preliminary document. #################### File: 240910_Skoda_Automation_MGH_Portal_direkt.pptx Page: 3 Context: # Werkstück ## Gussteil ![Gussteil](image_url_gussteil) ## Bearbeitetes Teil ![Bearbeitetes Teil](image_url_bearbeitetes_teil) ### Details | Bauteil | Motorphänotyp SSP HA LX34 | |----------------------- |-----------------------------| | Zeichnungsnummer | 000.910.13B | | Gewicht des bearbeiteten Teils | (inkl. der Lagerböden 0.369 kg) | | Gehäuse | GEA 903 100 108 (z.B. CNC 18.3600 - ASSI/JS3 [F]) | | Lagerböden | 0A 902 151 A DIN 30910-SINT-D11 | | Material | - | | Grundfläche | - | ### Datum 18.09.2024 ### Hinweis Skoda SSP MGH Automation Image Analysis: ### Localization and Attribution: - **Image 1**: Located in the top-left area, showing "Gussstück." - **Image 2**: Located in the top-center area, showing "Bearbeitetes Teil." - **Image 3**: Located in the top-right area, showing a technical diagram. - **Image 4**: Located in the bottom area, showing a table chart. ### Object Detection and Classification: - **Image 1**: - **Object**: "Gussstück" (casting) of an engine part. - **Key Features**: Metallic, unprocessed engine part with ridges and complex structure. - **Image 2**: - **Object**: "Bearbeitetes Teil" (machined part) of an engine part. - **Key Features**: Similar to Image 1 but highlighted areas are blue, indicating machining or finishing processes applied. - **Image 3**: - **Object**: Technical drawing/diagram of an engine part. - **Key Features**: Contains labels and dimensions that detail the structure of the same part shown in the previous images. - **Image 4**: - **Object**: Table chart. - **Key Features**: Contains detailed information about the part, including weight, materials, and standards. ### Scene and Activity Analysis: - **Image 1**: Depicts the raw, unprocessed version of the engine part ("Gussstück"). - **Image 2**: Shows the same part after machining processes ("Bearbeitetes Teil"), suggesting a transformation or enhancement process. - **Image 3**: Provides a technical blueprint of the part, suitable for engineering or manufacturing use. - **Image 4**: Displays a table with specifications and details about the engine part, aiding in technical documentation. ### Text Analysis: - **Image 4**: - **Extracted Text**: ``` Bauteil: Motorgehäuse SSP HA LX34 Zeichnungsnummer: 00A.901.108 Gewicht des bearbeiteten Teils: 14.675 kg (davon ca. 10 Lagernabe 0.369 kg) Gehäuse 00A 901 108 rot Material: EN AC-AlSi10CuMg-40000 - AlSi1Cu3 (Fe) Lagerbuchse 00A 901 215 A DIN 390101-SINT-D-11 Grundmaße folgt der Zeichnung ``` - **Content Analysis**: - **Bauteil**: Part name, "Motorgehäuse SSP HA LX34" (engine casing). - **Zeichnungsnummer**: Drawing number. - **Gewicht des bearbeiteten Teils**: Weight of the machined part. - **Material**: Specified materials used. - **Lagerbuchse**: Bearing specifications. - **Grundmaße**: Base dimensions. ### Diagram and Chart Analysis: - **Image 3**: - **Axes and Scales**: N/A (technical diagram) - **Legends**: Contains labels indicating different sections and measurements of the engine part. - **Key Insights**: Offers detailed schematics for manufacturing or quality control. ### Process Descriptions: - Images depict the transformation of an engine part from raw casting to a finished machined part. The table and technical diagram provide supplementary information useful in manufacturing or engineering contexts. ### Type Designations: - **Image 1**: "Gussstück" (casting) - **Image 2**: "Bearbeitetes Teil" (machined part) ### Trend and Interpretation: - The images collectively show a progression in manufacturing from raw material to finished product, indicating the stages and technical specifications involved in the process. ### Tables: - **Image 4**: Presents crucial information about the engine part, such as weight, material composition, and relevant standards. ### Color Analysis: - **Image 1**: Dominated by shades of grey, indicating raw metal. - **Image 2**: Includes blue highlights, emphasizing machined areas. - **Image 3**: Predominantly black and white, standard for technical diagrams. ### Perspective and Composition: - **Image 1 and Image 2**: Angled view highlighting different planes of the part. - **Image 3**: Standard flat perspective used for technical clarity. - **Image 4**: Tabular format, focusing on detailed information. ### Contextual Significance: - These images likely serve an engineering or manufacturing document, providing detailed information necessary for the production and quality control of an engine part. ### Metadata Analysis: - **Date**: 18.09.2024. - This date might represent the creation or revision date of the document, giving context to the currency and relevance of the information provided. #################### File: 240910_Skoda_Automation_MGH_Portal_direkt.pptx Page: 4 Context: # Terminplan ## 7. Terminplan | Activity | 2024 | 2025 | 2026 | 2027 | |-----------------------------------------------|----------|----------|----------|----------| | Bestellungen | | 01/25 | 04/26 | | | Lieferung, Inbetriebnahme und Übergabe | 1. BaP/OP → komplette Automatisierung | 1.8/26 | | | | TB/PVS | | | | | | Nielsen | | | | | | SOP | | | | | **MAG TP folgt** Image Analysis: ### Analysis of the Provided Visual Content #### 1. Localization and Attribution: - The visual content consists of a single image. - **Image 1:** The image fills the entirety of the provided visual space. #### 4. Text Analysis: The text within the image includes several elements: - **Header:** - "Terminplan" (translated: "Schedule") - "7. Terminplan" (translated: "7. Schedule") - **Table:** - **Columns:** Yearly markers 2024, 2025, 2026, 2027 - **Rows/Activities:** - **"Bestellungen"** (translated: "Orders"): 2024 - **"Lieferung, Inbetriebnahme und Übergabe"** (translated: "Delivery, Commissioning and Handover"): 01/25 - 04/26 - **"1.BA/2.BA OP + komplette Automatisierung"** (translated: "1st Phase/2nd Phase OP + complete automation"): 6/25 - 1/26 - **"TBT-PVS"**: 1/8/26 - **"Nul/serie"**: 4/7/26 - **"Primäre Inbetriebnahme LKS-Taktlauf TUZ und Materialwirtschaft"** (translated: "Primary Commissioning LKS Cycle Time TUZ and Material Management"): 1/27 - **"2 Tage Produktion"** (translated: "2 Days Production"): 01/27 - **"SOP"**: 06/27 - **Additional Text:** - "MAG TP folgt" (translated: "MAG TP follows"), which seems to indicate that additional details about the MAG TP will follow. - Footer indicates "Skoda SSP MGH Automation" and the date "18.09.2024". #### 5. Diagram and Chart Analysis: - The chart presents a timeline of activities scheduled from 2024 to 2027. - **X-axis:** Represents the timeline in years. - **Y-Axis:** Represents various activities related to project execution. - **Activities:** Noted in rows, providing a clear timeline for when each activity will commence and conclude. - **Data presentation:** Green bars indicate expected task completion phases, and red markers pinpoint specific events or milestones. #### 12. Graph and Trend Analysis: - **Trend:** The activities are sequentially organized, following a strict timeline indicating progressive project phases. - **2024:** Project initiation with order placements. - **2025-2026:** Delivery, commissioning, handover, and automation setup. - **2026:** Specific operation activities such as TBT-PVS and initial series run. - **2027:** Completion activities including material management commissioning and the start of production. #### 13. Graph Numbers: Detailed dates and sequences for each activity: - **Orders:** Projected in 2024. - **Delivery, Commissioning, Handover:** 01/25 - 04/26. - **1.BA/2.BA OP + Complete Automation:** 6/25 - 1/26. - **TBT-PVS:** 1/8/26. - **Nul/serie:** 4/7/26. - **Primary Commissioning LKS cycle-time TUZ and Material Management:** 1/27. - **2 Days of Production:** 01/27. - **SOP:** 06/27. ### Additional Aspects: #### Ablaufprozesse (Process Flows): The image details a timeline of process flows, highlighting key stages from the initial order to the start of production. It outlines the transition from order placement to final commissioning, emphasizing on significant milestones such as delivery, automation, and testing phases. #### Prozessbeschreibungen (Process Descriptions): - **Bestellungen (Orders):** Initial stage of placing orders. - **Lieferung, Inbetriebnahme und Übergabe (Delivery, Commissioning, Handover):** Transition from equipment delivery to operational status. - **Automation Phases (1.BA/2.BA OP):** Implementation of automation systems. - **Testing and Validation (TBT-PVS):** Ensuring systems function as intended. - **Production Initiation (Nul/serie and 2 Days Production):** Beginning of manufacturing operations. - **SOP (Start of Production):** Final commissioning marking the official start of production. #### Contextual Significance: The image provides a detailed schedule for implementing automation in Skoda SSP MGH. It serves as a project management tool to track progress and ensure all phases are completed on time, highlighting significant milestones and timelines critical for stakeholders. --- This examination offers detailed insights into the visual content, covering various aspects from process flows to textual analyses, contextual relevance, and trend identification. ########## """QUERY: Summarize context""" Consider the chat history for relevant information. Use all information included. Use as much tokens as needed. Important: If you find information separated by a | in the context, it is a table formatted in Markdown.Important: Take a look at the QUERY and only the QUERY. If this is vague or unclear, please ignore everything and ask a follow-up question instead! Final Files Sources: 0qa_901_108-sspha_mg_ftz%281%29.pdf - Page 1, 0qa_901_108-sspha_mg_ftz%281%29.pdf - Page 3, 0qa_901_108-sspha_mg_ftz%281%29.pdf - Page 4, 0qa_901_108-sspha_mg_ftz%281%29.pdf - Page 5, 0qa_901_108-sspha_mg_ftz%281%29.pdf - Page 6, 0qa_901_108-sspha_mg_ftz%281%29.pdf - Page 7, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 1, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 2, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 3, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 4, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 5, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 6, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 7, 240911_Skoda_Automation_GGH_Portal_direkt.pptx - Page 8, VW%2010130_EN%281%29.pdf - Page 1, VW%2010130_EN%281%29.pdf - Page 2, VW%2010130_EN%281%29.pdf - Page 3, VW%2010130_EN%281%29.pdf - Page 4, VW%2010130_EN%281%29.pdf - Page 5, VW%2010130_EN%281%29.pdf - Page 6, VW%2010130_EN%281%29.pdf - Page 7, VW%2010130_EN%281%29.pdf - Page 8, VW%2010130_EN%281%29.pdf - Page 9, VW%2010130_EN%281%29.pdf - Page 10, VW%2010130_EN%281%29.pdf - Page 11, VW%2010130_EN%281%29.pdf - Page 12, VW%2010130_EN%281%29.pdf - Page 13, VW%2010130_EN%281%29.pdf - Page 14, VW%2010130_EN%281%29.pdf - Page 15, VW%2010130_EN%281%29.pdf - Page 16, VW%2010130_EN%281%29.pdf - Page 17, VW%2010130_EN%281%29.pdf - Page 18, VW%2010130_EN%281%29.pdf - Page 19, VW%2010130_EN%281%29.pdf - Page 20, VW%2010130_EN%281%29.pdf - Page 21, VW%2010130_EN%281%29.pdf - Page 22, VW%2010130_EN%281%29.pdf - Page 23, VW%2010130_EN%281%29.pdf - Page 24, VW%2010130_EN%281%29.pdf - Page 25, VW%2010130_EN%281%29.pdf - Page 26, VW%2010130_EN%281%29.pdf - Page 27, VW%2010130_EN%281%29.pdf - Page 28, VW%2010130_EN%281%29.pdf - Page 29, VW%2010130_EN%281%29.pdf - Page 30, VW%2010130_EN%281%29.pdf - Page 31, VW%2010130_EN%281%29.pdf - Page 32, VW%2010130_EN%281%29.pdf - Page 33, VW%2010130_EN%281%29.pdf - Page 34, VW%2010130_EN%281%29.pdf - Page 35, VW%2010130_EN%281%29.pdf - Page 36, Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf - Page 1, Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf - Page 2, Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf - Page 3, Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf - Page 4, Interni%20smernice%20-%20komponenty%20SZ_CZ.pdf - Page 5, Interni%20smernice%20-%20komponenty%20SZ_DE%281%29.pdf - Page 2, Interni%20smernice%20-%20komponenty%20SZ_DE%281%29.pdf - Page 3, Interni%20smernice%20-%20komponenty%20SZ_DE%281%29.pdf - Page 4, Anfrage%20Mail.pdf - Page 1, Anfrage%20Mail.pdf - Page 2, MGH%20Anlage%2014.pdf - Page 1, MGH%20Anlage%2014.pdf - Page 2, MGH%20Anlage%2014.pdf - Page 3, MGH%20Anlage%2014.pdf - Page 4, MGH%20Anlage%2014.pdf - Page 5, MGH%20Anlage%2014.pdf - Page 6, MGH%20Anlage%2014.pdf - Page 7, MGH%20Anlage%2014.pdf - Page 8, MGH%20Anlage%2014.pdf - Page 9, Standardanschreiben%281%29.pdf - Page 1, Standardanschreiben%281%29.pdf - Page 2, Standardanschreiben%281%29.pdf - Page 3, Interni%20smernice%20-%20komponenty%20SZ_DE.pdf - Page 1, Interni%20smernice%20-%20komponenty%20SZ_DE.pdf - Page 2, Interni%20smernice%20-%20komponenty%20SZ_DE.pdf - Page 3, Interni%20smernice%20-%20komponenty%20SZ_DE.pdf - Page 4, VW%2010130_CS.pdf - Page 1, VW%2010130_CS.pdf - Page 2, VW%2010130_CS.pdf - Page 3, VW%2010130_CS.pdf - Page 4, VW%2010130_CS.pdf - Page 5, VW%2010130_CS.pdf - Page 6, VW%2010130_CS.pdf - Page 7, VW%2010130_CS.pdf - Page 8, VW%2010130_CS.pdf - Page 9, VW%2010130_CS.pdf - Page 10, VW%2010130_CS.pdf - Page 11, VW%2010130_CS.pdf - Page 12, VW%2010130_CS.pdf - Page 13, VW%2010130_CS.pdf - Page 14, VW%2010130_CS.pdf - Page 15, VW%2010130_CS.pdf - Page 16, VW%2010130_CS.pdf - Page 17, VW%2010130_CS.pdf - Page 18, VW%2010130_CS.pdf - Page 19, VW%2010130_CS.pdf - Page 20, VW%2010130_CS.pdf - Page 21, VW%2010130_CS.pdf - Page 22, VW%2010130_CS.pdf - Page 23, VW%2010130_CS.pdf - Page 24, VW%2010130_CS.pdf - Page 25, VW%2010130_CS.pdf - Page 26, VW%2010130_CS.pdf - Page 27, VW%2010130_CS.pdf - Page 28, VW%2010130_CS.pdf - Page 29, VW%2010130_CS.pdf - Page 30, VW%2010130_CS.pdf - Page 31, VW%2010130_CS.pdf - Page 32, VW%2010130_CS.pdf - Page 33, VW%2010130_CS.pdf - Page 34, VW%2010130_CS.pdf - Page 35, 240910_Skoda_Automation_MGH_Portal_direkt.pptx - Page 1, 240910_Skoda_Automation_MGH_Portal_direkt.pptx - Page 2, 240910_Skoda_Automation_MGH_Portal_direkt.pptx - Page 3, 240910_Skoda_Automation_MGH_Portal_direkt.pptx - Page 4 ================================================== **Elapsed Time: 0.00 seconds** ================================================== FINAL ANSWER Answer: The context provided is a collection of documents related to the automation of Skoda SSP Motorgehäuse (MGH) and Getriebegehäuse (GGH) production. The documents include: - **Technical specifications:** These documents detail the components, materials, and processes involved in the manufacturing of MGH and GGH. They include information on clamping procedures, tolerance limits, and statistical analysis methods. - **Project data:** These documents outline the project scope, timelines, and key personnel involved in the automation project. - **Communication:** This includes emails and presentations, showcasing the collaboration between various companies and the communication flow within the project. The documents are written in German and Czech, with some sections translated into English. They are likely internal documents used by Škoda Auto a.s. and MAG IAS GmbH for project management, quality control, and communication. ================================================== **Elapsed Time: 7.89 seconds** ==================================================