Tolerance Design and Processes for Fabricated Jet Engine ...1024832/FULLTEXT01.pdf · A final thank you to all the people at Volvo Aero that contributed in one way or another to this

MASTER’S THESIS2010:089 CIV

Universitetstryckeriet, Luleå

Mia Westin

Tolerance Design and Processes for Fabricated

Jet Engine Components

MASTER OF SCIENCE PROGRAMME Industrial Design Engineering

Luleå University of TechnologyDepartment of Human Work Sciences Division of Industrial Product Design

2010:089 CIV • ISSN: 1402 - 1617 • ISRN: LTU - EX - - 10/089 - - SE

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Acknowledgements In this chapter would I like to take the opportunity to thank a few people that has made this work possible through participation to the final result. This thesis work was conducted by Mia Westin at Volvo Aero Corporation in Trollhättan, Sweden. It is the final work for the Master of Science degree in Industrial Design Engineering (specialization in Product Development). It was made under the supervision of the Department of Human Work Science at Luleå University of Technology, Sweden. I would first like to direct a special thank you to my supervisor at Volvo Aero, Tor Wendel, who has helped and guided me a lot through all the different phases of the project. He has contributed with wisdom and knowledge and also a lot of effort and time. For that I am forever grateful. A big thank you is directed to Malin Rosenius, Johan Lööf, Peter Thor, Ola Isaksson and Alejandro Vega Galvez at Volvo Aero, for their support and guidance through this work. I want to thank Gunnar Marke, Magnus Arvidsson and Olof Lewin who have showed interest and support regarding information to the case study. I would also like to thank my supervisor at Luleå University of Technology, Stig Karlsson, for the support that he has shown towards this project. A final thank you to all the people at Volvo Aero that contributed in one way or another to this thesis work regarding interviews, surveys, drawings, working material etc. Trollhättan, (2009-12-28) ________________________________ Mia Westin

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“This thesis work is dedicated to my grandfather (1924 -2005).”

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Abstract Understanding the causes and effects of dimensional and geometric variation is a major concern in the design and manufacturing of products. Geometry assurance is a generic name for different activities with the aim to secure the quality of the companys geometry definition and verification process, which includes both virtual and physical processes. Methodology and support for a robust design, simulation and visualization of variation is important to be able to make the product as insensitive to manufacturing variation as possible. It is important to have an internal overall picture of the geometry process to become more effective and achieve higher quality on the products and an efficient manufacturing process. To be more competitive in the market Volvo Aero has launched the concept of Make it light. This design objective is partly met by fabrication, i.e. designing products with an increased number of subparts. Fabrication leads to new/increased demands on the ability to break down geometrical requirements to subparts and to be able to sum up the expected variation from subparts to a top level to assess producibility/quality. It is important to be able to take control of geometrical variation in an early stage of product development, and this requires new tools and working methods. Volvo Aero is currently developing several products that will enter into service in the near future, and several other product development projects are in the planning. When this happens, and production volume increase, the number of deviations might increase many times compared to the present levels according to internal estimations. This will result in increased cost of poor quality (non-conformance handling, tied up material and scrap). This thesis work has through analysis, of Volvos GDP (Global Development Process) and Geometry Assurance processes in the automotive industry, worked towards a description on how this method can be used at Volvo Aero. An interview study was made to be able to form a description of how the Geometry Assurance process could be visualized today. Suggestions of improvements of today’s Geometry Assurance process was discussed and visualized through a future Geometry Assurance process, which shows the possibilities for what Volvo Aero could achieve. Through the studies and the interviews it became quite clear that improvements regarding handling and visualizing variation is something that is needed at Volvo Aero. A case was used to show the possibilities of improvements with a method to analyze and visualize stability, contribution of locating points, variation envelope and stack-ups, this all in 3D environment, which could be implemented early into the design process. The reccomendations is that Volvo Aero should implement the suggested Geometry Assurance process, because it is a good way of visualizing the working process and highlights problem/improvement areas for further discussions. The process is in line with Volvo Aero’s current strategy regarding producibility and fabrication. A 3D visualization stability and variation simulation tool should be aquired since it shows a lot of potential of minimizing deviations and creating a better connection between tolerance chains and the 3D model. The tool is also most likely to improve the efficiency of the Product Development process, because of the few hours it takes to perform the analysis. If the Geometry assurance process and a 3D visualization tool are implemented at Volvo Aero, future work is needed regarding easy access and search ability of capability data and Geometry Assurance process support for the projects etc.

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Table of Contents

TABLE OF FIGURES........................................................................................................................................... 1

ABBREVIATIONS.............................................................................................................................................. 3

1. INTRODUCTION...................................................................................................................................... 5

1.1 DISPOSITION...................................................................................................................................................5 1.2 BACKGROUND.................................................................................................................................................5 1.3 THE COMPANY: VOLVO AERO ............................................................................................................................6 1.4 GEOMETRY ASSURANCE ....................................................................................................................................7 1.5 AIM AND GOAL................................................................................................................................................8 1.6 DELIMITATIONS ...............................................................................................................................................9 1.7 PROJECT PLANNING..........................................................................................................................................9

2. THEORY................................................................................................................................................ 11

2.1 PROCESS STABILITY.........................................................................................................................................11 2.2 VARIATION ...................................................................................................................................................12

2.2.1 Special cause........................................................................................................................................12 2.2.2 Common cause.....................................................................................................................................13

2.3 TOLERANCE ALLOCATION.................................................................................................................................13 2.4 SIX SIGMA....................................................................................................................................................14

2.4.1 Role of the 1,5 sigma shift ...................................................................................................................15 2.4.2 Sigma levels .........................................................................................................................................16

2.5 STACK-UP ....................................................................................................................................................16 2.5.1 Worst Case (WC) ..................................................................................................................................16 2.5.2 Root Sum Square (RSS).........................................................................................................................18 2.5.3 Monte Carlo Simulation (MCS).............................................................................................................19

2.6 HOW TO USE A TARGET SYSTEM........................................................................................................................21

3. METHODOLOGY ................................................................................................................................... 23

3.1 INTERVIEWS..................................................................................................................................................23 3.1.1 Unstructured interview ........................................................................................................................23 3.1.2 Structured interview ............................................................................................................................23 3.1.3 Half structured interview .....................................................................................................................23 3.1.4 Analyzing interview material (qualitative data analysis).....................................................................24

3.2 SURVEY (QUESTIONNAIRES) .............................................................................................................................24 3.3 MATRIX .......................................................................................................................................................25 3.4 BRAINSTORMING ...........................................................................................................................................25 3.5 CASE STUDY (DEMONSTRATION).......................................................................................................................25 3.6 SIMULATION .................................................................................................................................................25 3.7 MOVIE ........................................................................................................................................................26

4. IMPLEMENTATION ............................................................................................................................... 27

4.1 RESEARCH METHOD.......................................................................................................................................27 4.1.1 Literature study....................................................................................................................................27 4.1.2 Interviews and analysis........................................................................................................................27

4.2 CASE ...........................................................................................................................................................28 4.2.1 Brainstorming ......................................................................................................................................28 4.2.2 Case description and problem definition .............................................................................................29 4.2.3 Simulation and analysis .......................................................................................................................32 4.2.4 Survey...................................................................................................................................................34 4.2.5 Movie sequence ...................................................................................................................................34

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5. CURRENT STATE DESCRIPTION .............................................................................................................. 35

5.1 PHI .............................................................................................................................................................35 5.2 DESIGN FOR ROBUSTNESS (DFR).......................................................................................................................35 5.3 OPERATIONAL MANAGEMENT SYSTEM (OMS) ...................................................................................................36

5.3.1 Global development process (GDP)......................................................................................................36 5.4 VOLVO AERO GEOMETRY ASSURANCE PROCESS...................................................................................................36

5.4.1 Concept phase:.....................................................................................................................................37 5.4.2 Verification phase: ...............................................................................................................................38 5.4.3 Production phase: ................................................................................................................................38

6. RESULTS............................................................................................................................................... 41

6.1 INTERVIEWS..................................................................................................................................................41 6.1.1 Improvement areas..............................................................................................................................41

6.2 VARIATION ANALYSIS AT VOLVO AERO ...............................................................................................................43 6.3 CASE STUDY..................................................................................................................................................44

6.3.1 Stability analysis ..................................................................................................................................44 6.3.2 Variation envelope...............................................................................................................................45 6.3.3 Addition of profile tolerances...............................................................................................................46 6.3.4 Clearance analysis................................................................................................................................46 6.3.5 Measuring points and stack-up simulations ........................................................................................47 6.3.6 Interpreting the results ........................................................................................................................49 6.3.7 Study of data/knowledge “needed”.....................................................................................................49 6.3.8 Time study............................................................................................................................................50

7. SUGGESTIONS AND RECOMMENDATIONS ............................................................................................. 51

7.1 A FUTURE GEOMETRY ASSURANCE PROCESS AT VOLVO AERO.................................................................................51 7.1.1 Concept phase......................................................................................................................................52 7.1.2 Detail definition & virtual verification..................................................................................................52 7.1.3 Production............................................................................................................................................53 7.1.4 Verification...........................................................................................................................................54

7.2 VARIATION SIMULATION ROAD MAP ..................................................................................................................55 7.3 THE BENEFITS OF IMPLEMENTATION OF THE VARIATION SIMULATION METHOD ...........................................................56

8. DISCUSSION ......................................................................................................................................... 57

9. FUTURE WORK ..................................................................................................................................... 59

REFERENCES.................................................................................................................................................. 61

APPENDIX ..................................................................................................................................................... 65

APPENDIX A: Engine parts produced at Volvo Aero

APPENDIX B: Gantt chart

APPENDIX C: Z-values for normal distribution

APPENDIX D: Unstructured interview material

APPENDIX E: Structured interview material

APPENDIX F: General description of the different software

APPENDIX G: Specification of requirements for RD&T

APPENDIX H: Survey and analysis

APPENDIX I: Movie sequence

APPENDIX J: Road map of Volvo Aero’s working process

APPENDIX K: Plot over what and when

APPENDIX L: Identified problems based on interview material

APPENDIX M: Problem and solutions in tree diagrams

APPENDIX N: Total analysis of the NEWAC case

APPENDIX O: Step-by-step walkthrough of RD&T

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Table of figures

Figure 1: Illustration by Mia Westin. Figure 2: Illustration by Mia Westin. Figure 3: R. Söderberg (2006). Virtual Geometry Assurance for Effective product realization. 1st Nordic Conference on Product Lifecycle Management – NordPLM’06, Göteborg Figure 4: Volvo Aero Presentation: Volvo Aero processduglighet (kapabilitetspasset). Figure 5: Volvo Aero Presentation: Volvo Aero processduglighet (kapabilitetspasset). Figure 6: Rolls-Royce. A guide to the component proving process GQP C.4.59 How to achieve an on-target process with minimum variation. PIROS reference: 26050. Figure 7: K. L Hsieh (2005), The Study of cost-tolerance model by Incorporating process capability Index into product lifecycle cost. Department of Information Management, National Taitung University. Springer-Verlag London Limited. Figure 8: R. Söderberg (2006), Virtual Geometry Assurance for Effective product realization. 1st Nordic Conference on Product Lifecycle Management – NordPLM’06, Göteborg Figure 9: Presentation Six sigma Teamcenter (2009): Volvo Aero Six sigma för nya chefer. Figure 10: A. Gálvez Vega, 1D/2D Tolerance Analysis, VOLS:10045916, version 02. Figure 11: A. Gálvez Vega, 1D/2D Tolerance Analysis, VOLS:10045916, version 02. Figure 12: A. Gálvez Vega, 1D/2D Tolerance Analysis, VOLS:10045916, version 02. Figure 13: J. Shah and G. Ameta. Navigating the Tolerance Analysis Maze, Vol 4, No 5, pp 705-718. Arizona State Uneversity. Figure 14: Illustration by Tor Wendel from Excel. Figure 15a-c: Illustration by Mia Westin. Figure 16: Illustration by Mia Westin. Figure 17: Illustration by Mia Westin. Figure 18: Illustration by Mia Westin. Figure 19: Illustration by Mia Westin Figure 20: Illustration by Mia Westin from RD&T. Figure 21: Illustration by Mia Westin from RD&T. Figure 22: Illustration by Mia Westin from RD&T. Figure 23: Illustration by Mia Westin from RD&T. Figure 24: Volvo Aero document PHI (2009): Volvo Aero’s product philosophy. Figure 25: Illustration by Mia Westin. Figure 26: Illustration by Mia Westin. Figure 27: Illustration by Mia Westin. Figure 28a-b: Illustration by Mia Westin from RD&T. Figure 29: Illustration by Mia Westin from RD&T. Figure 30: Illustration by Mia Westin from RD&T. Figure 31: Illustration by Mia Westin from RD&T. Figure 32: Illustration by Johan Lööf from RD&T. Figure 33: Illustration by Johan Lööf from RD&T Figure 34: Illustration by Mia Westin from RD&T. Figure 35: Illustration by Mia Westin from RD&T. Figure 36: Illustration by Mia Westin from RD&T. Figure 37: Illustration by Mia Westin. Figure 38: Illustration by Mia Westin. Figure 39: Illustration by Mia Westin Figure 40: Illustration by Mia Westin

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Figure A.1: Wikipedia turbofan (2009): http://en.wikipedia.org/wiki/File:Turbofan_operation.svg Figure A.2: Volvo Aero document components (2009): http://www.dream-project.eu/volvo-aero.aspx Figure D.1: Illustration by Mia Westin. Figure J.1: Illustration by Mia Westin. Figure H.1: Illustration by Mia Westin Figure K.1: Illustration by Mia Westin. Figure N.2: Illustration by Mia Westin from RD&T etc. Figure N.3: Illustration by Mia Westin from RD&T etc. Figure N.4: Illustration by Mia Westin from RD&T etc. Figure N.5: Illustration by Mia Westin from RD&T. Figure N.6: Illustration by Mia Westin from RD&T. Figure N.7: Illustration by Mia Westin from RD&T. Figure N.8: Illustration by Mia Westin from RD&T. Figure N.9: Illustration by Mia Westin from RD&T. Figure N.10: Illustration by Mia Westin from RD&T. Figure N.11: Illustration by Mia Westin from RD&T. Figure N.12: Illustration by Mia Westin from RD&T. Figure N.13: Illustration by Mia Westin from RD&T. Figure N.14: Illustration by Mia Westin.

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Abbreviations ASME American Society of Mechanical Engineers Cp Process capability index Cpk Corrected process capability index CAD tool Computer Aided Design tool DfR Design for Robustness DPMO Defects per Million Opportunities DP Design Practice FAI First Article Inspection FAIR First Article Inspection Report GA Geometry Assurance GDP Global Development Process GD&T Geometric Dimensioning and Tolerancing DP Design Practice CoE Center of Excellence KPS Kvalitet och Produktionssystem (Inspection and Process Control System) LSL Lower Specification Limit LL Lessons Learned MCS Monte Carlo Simulation MP Measure Point NC-program Numerical Control program OMS Operational Management System PD Product Development R Rotation RD&T Robust Design and Tolerancing RMS Root Mean Square RSS Root Sum Square T Translation TSV Tolerances Stack-up Validation USL Upper Specification Limit VAC Volvo Aero Corporation VAN Volvo Aero Norway VisVSA Visualization VSA WC Worst Case ZLSL Describe how many standard deviation from the nominal value to the

lower specified limit Zlt Describes how many standard deviations occurs for a long term Zst Describes how many deviations that occurs for a short term ZUSL Describe how many standard deviation from the nominal value to the

upper specified limit

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1. Introduction This chapter will give the reader a better understanding of why this work has been initiated. The chapter consists of an introduction of the project background and the concept of geometry assurance, but also information of delimitations, aim and goal. In the beginning a disposition is created to give the reader a quick study of how to read this thesis work.

1.1 Disposition

To get the most out of this thesis work depending on knowledge and experience a quick guide of how the work is presented can be seen in figure 1. Figure 1: Disposition of the report and reading suggestions To get as much as possible out of the content in this thesis, the reader is recommended to follow the bold lines in figure 1, reading the report in its presented order. If the reader has only an interest from a scientific perspective, the reading time can be shortened by reading according to the dashed line, chapters 1 and 4-9. A reader acquainted with the company and only interested in the result should follow the dashed-dot line, chapters 1 and 6-9.

1.2 Background

Every company has an interest to ensure that the customer needs are understood and that the design, production, delivery and supporting service are satisfying those needs better than any other competitor. Volvo Aero should offer solutions that meet the customer’s needs, but at the same time they must reach certain qualities e.g. quality, low price and on time delivery. The cost may rise and Volvo Aero will lose capital if the variations in the process result in deviations and reduced on time delivery. This requires internal efficiency and quality of the working process. It is important to satisfy customer needs through processes that are consistent and produce high quality components, and at the same time are profitable. Variation is the “enemy” of quality and

1. Introduction

2. Theory 3. Methodology

5. Implementation

4. Current state

7. Recommendations

9. Future work 8. Discussion

6. Result

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therefore also the enemy of customer satisfaction. Variation adds to the customer’s lack of confidence in the ability of the internal process and its supply chain to deliver customer satisfaction. Variation increases the risk that the product or service supplied will not meet the customer’s expectations.

Variation is a key driver of defects

Understanding the causes and effects of dimensional and geometric variation is a major concern in the design and manufacturing of high-tech products. Designers are essentially concerned with the following geometric dimension and tolerance issues:

• Functionality and/or easy of assembly • Tolerance analysis: consequence of proposed Geometric Dimensioning and Tolerancing

(GD&T) • Tolerance allocation: determine how to distribute the allowable variation on the

dimension of interest among all the independent contributors. Tolerance decisions have a strong connection to capability in the manufacturing, i.e. how the product will be produced. It’s very rare, in an early stage, that the product has a detailed description of the design shape which is needed for traditional product analysis such as mount sequence, tolerances, machine capability, supplier situation, etc. In practice the designer is forced to reactively examine what kind of problems previous design decisions have resulted in further along the process. In order to make a product resistant to geometrical variation and to be able to prevent deviations to occur, the company should have good knowledge about its geometry assurance process (GA process) and work to manage variation in early stages of the design process.

1.3 The company: Volvo Aero

Volvo Aero is located in Trollhättan, Sweden and is a subsidiary of AB Volvo. In cooperation with the world’s leading engine manufacturers, they develop and produce components for aircraft (appendix A), rocket and gas turbine engines with high technology content. (Volvo Aero homepage, 2009) The company’s specialization strategy has proven highly successful and more than 90 percent of all new commercial aircraft with more than 100 passengers are equipped with engine components from Volvo Aero. Volvo Aero has been an integral part of the aviation and aerospace industries since it was founded in 1930 (Volvo Aero homepage, 2009). To be less sensitive in the market Volvo Aero has strategically since the 1970’s moved its focus from military to civilian products and on these increased the focus on product development in addition to the existing manufacturing programs. This means, that instead of only receiving drawings from the client and produce what is on it, Volvo Aero also has the responsibility for the design.

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Volvo’s core values are Quality, Environment and Safety, which are all important aspects in the aviation industries. Volvo Aero is therefore focusing on developing lightweight solutions for aircraft engine structures and rotors, including a range of technologies. Make it light describes the essence of that mission. To reduce weight it is needed to have a good understanding of where material is needed and where it can be reduced without affecting the safety and satisfaction of the customer. If Volvo Aero can reduce the engine weight and at the same time retain the level of safety and performance of the engine, it will give the company a competitive edge. Reduction of component weight, in combination with larger parts, has led to new requirements on the manufacturing process. In some cases the solution has been to choose fabrication. Fabrication is to replace the large, components (castings) with smaller sub parts that consist of castings, forgings and sheet metal. Volvo Aero therefore needs a good Geometry assurance process (GA process) so they can be sure that, what they design also can be produced with a profit.

1.4 Geometry assurance

Geometry assurance process (GA process) is a generic name for different activities with the aim to secure the quality on the companies’ geometry process, which includes both the virtual and the physical processes. Methodology and support for a robust design, simulation and visualization of variation is important to be able to make the product as insensitive to manufacturing variation as possible. An important part is to have an internal overall picture of the geometry process to become more effective and achieve higher quality. (SWEREA|IVF, 2009) All manufacturing processes are affected by variation (figure 2) which implies that the nominal value of a manufacturing dimension may not be expected at all times. The manufacturing dimension may rather be described by an expected range and a probability distribution. For most processes the production cost rises with decreasing variation. This is the main reason why design concepts with functionality based on small manufacturing variation must be avoided. (R.Söderberg, 2006) Nominal Variation Figure 2: Component in nominal state and state affected by variation The means of managing variation and secure function, form and assembly, is by assigning tolerances that restrict the permitted variation of a geometrical feature. Properly done, tolerances are allocated in a top-down fashion where overall product constraints are broken down into component constraints and finally into tolerances for individual geometrical features. This is a

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complex process (figure 3), where function and quality aspects must be balanced against manufacturing constraints and cost aspects. (R. Söderberg, 2006)

Figure 3: Geometry assurance process for a car industry (R. Söderberg, 2006).

• In the Concept phase the product and the production concepts are developed. Product concepts are analyzed and optimized to withstand the effects of manufacturing variation, and tested virtually against available production data. In this phase, the concept is optimized with respect to manufacturing robustness and verified against the assumed production system by statistical tolerance analysis. The visual appearance of the product is optimized and product tolerances are allocated down to part level.

• In the Verification phase and Pre-production phase the product and the production system is physically tested and verified. Adjustments are made to both product and production system to adjust errors and prepare for serial production. In this phase inspection preparation takes place. This is the activity when all inspection strategies and inspection routines are decided.

• In the Production phase all production process adjustments are completed and the product is in full production. Focus in this phase is to control production and to detect and correct errors

1.5 Aim and goal

The aim of this thesis work is to understand how the GA process works at other companies, but also how this model can be implemented at Volvo Aero. The goal is to visualize how the GA process would be described today and suggest a future GA process at Volvo Aero. A case study should be performed to show the possibilities of the suggested working method to be used in the GA process in early stages of the product development (PD).

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1.6 Delimitations

The thesis work has not made a detailed description on how it should be made possible to go from today’s GA process to the future GA process, especially in terms of:

• Necessary changes to the current process description. • Organizational impact (roles, necessary education…) • Choice of software

or a Business Case for the above. Because of the limited edition of the software and available time, the Case study included basic simulations and analysis.

1.7 Project planning

In the beginning a Gantt chart (appendix B) was made to ensure a well planned thesis work. The thesis work had the duration of twenty weeks and the Gantt chart shows the activities made during the entire work, but also the duration for each activity. During this project some adjustments have been made to the Gant chart. Every week a report was written to secure that the project was going on as planned. This also helped to create an overall picture of what had been done and what was planned the week after. It also worked as an information channel towards the supervisors which made them conversant in the process of the project.

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2. Theory To get a better understanding of this work, the following chapter summarizes and describes all the theory that has some connection to this work, i.e. process stability, variation, tolerance allocation, six sigma, stack-ups and target system.

2.1 Process stability

A stable process looks at the variability of the process and eliminates special causes of variation. The aim is to match the process mean against the specification target. Figure 4 describes an unstable process or a process out of control as it also is called. The total variation in an unstable process is much larger compared to a stable or an in control process (figure 5). Figure 4: Unstable process (Volvo Aero presentation). Figure 5: Stable process (Volvo Aero presentation). A stable process alone is not enough to have a good working process; it also has to be taken under consideration if the process is capable or not. Process capability looks at the variability of the process and eliminates common causes of variation. The aim is to match the process spread to the specification limits and it is illustrated in figure 6.

Total Variation

Target Target

Time Time

Total Variation

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Figure 6: Process capability (Volvo Aero Green Belt Training material). Process capability measures have been useful for many years to quantitatively assess the capability of a process to achieve required performance. It is also well known that the concepts of process control and process capability have been the key to the success of statistical process control in modern manufacturing. Although there have been numerous measures proposed for process capability, there are many fewer quantitative summaries to use as a starting point to assess the overall in-control performance of a process. (B. Ramirez, 2006)

2.2 Variation

Variation means uncertainty or losses and it is commonly known that everything is effected by variation (B. Bergman, 2007). In reality there is no ideal working process that can be repeated exactly over and over again without any form of variation. The important part is to be able to identify what factors that influence variation in the process. (B. Milivojevic) There are two types of variation common cause variation, which depends on random changes and can be predicted using statistics methods, and special cause variation that are special, distinguished, causes and can therefore not be predicted using statistic methods (B. Bergman, 2007).

2.2.1 Special cause

The special cause variation in the working process depends on many different causes that are possible to identify and control (B. Milivojevic). The causes that affect the special cause variation can usually not be predicted, but when it occurs it is possible to find the source to the variation (B. Bergman, 2007).

Special cause variation always arrives as a surprise. It is the signal within the system.

Factors that contribute to special cause variation could be: a change of raw material, new staff, operator falls asleep, operator absent, machine malfunction, computer crashes, etc.

In control and capable of meeting specifications (variation from

common cause have been reduced)

In control but not capable of meeting specifications (variation from common cause is excessive)

Upper specified limit

Lower specified limit

Time

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(B.Bergman, 2007) It can be hard to find and identify all the causes to the special cause variation, but identification of as many causes of variation as possible will increase the stability and reliability of the process (B. Milivojevic).

2.2.2 Common cause

Common cause variation depends on a number of different factors that are inherent in the system. Each factor contribution to the variation cannot separately be distinguished from the total variation affect. Often the result of these factors follow a normal distribution and the outcome can be predicted through statistic methods. (B. Bergman, 2007)

The outcomes of a roulette wheel are a good example of a common cause variation.

Factors that contribute to common cause variation could be: inappropriate procedures, poor design, poor maintenance of machines, lack of clearly defined operating procedures, poor working conditions, etc. (Wikipedia common cause, 2009) The common cause variation is a natural part of life and cannot be affected. The only thing that will be left when the special variations has been defined and eliminated is the common cause variation. When that happens the process is in statistical balance. (B. Milivojevic)

The goal with controlling variation is to come as close a possible to the nominal value. (B.Bergman, 2007)

2.3 Tolerance allocation

Optimizing quality, performance and cost often requires tolerance allocation considerations. The question is how to allocate the available product tolerances down to parts and features. In a complex product, due to different geometrical sensitivities, variation in individual part dimensions contributes differently to fulfillment of the product characteristics. Figure 7: Tolerances with respect to cost and quality (K. L Hsieh, 2005). Since tight tolerances are related to high quality but also in many cases high cost (figure 7), allocation of tolerances must be done with respect to the situation (R. Söderberg, 2006).

Cost

Tolerance

Total Cost

Quality Loss

Manufacturing Cost

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According to Rickard Söderberg (2006) there are three approaches that can be used when considering tolerance allocation. These are illustrated and described below in figure 8.

Figure 8: Tolerance allocation strategies (R. Söderberg, 2006).

1. Allocation of contribution: When costs is of little importance or when all included parameters have about the same cost, one strategy could be to strive for equal contribution, i.e. all part tolerances contribute equally to the product tolerances with respect to their individual sensitivities.

2. Minimizing cost: When parts are of different types with different tolerance/cost curves,

the overall strategy is to fulfill the product tolerance requirement with tight tolerances on parts where it is less expensive and where the sensitivity is high. This can be formulated and optimized using both continuous and discrete optimization routines.

3. Minimizing “total loss”: In many situations a holistic approach, including both

manufacturing cost and “quality loss” can be strategic. Since bad quality not only generates loss for the costumer but also for the company in the end, the sum of the manufacturing cost and the “quality loss” should be minimized. This strategy can be optimized using both continuous and discrete optimization routines but requires data about cost and expected loss.

2.4 Six Sigma (6σ) Six Sigma is a business management strategy initially implemented by Motorola. Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and variability in manufacturing and business processes. (Wikipedia six sigma, 2009) The term Six Sigma process comes from the notion that if one has six standard deviations between the process mean (y) and the nearest specification limit (LSL or USL), as shown in figure 9, there will be practically no items that fail to meet specifications. This is based on the

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calculation methods employed in process capability studies. In a capability study, the number of standard deviations between the process mean and the nearest specification limit is given in sigma units. As process standard deviation goes up, or the mean of the process moves away from the center of the tolerance, fewer standard deviations will fit between the mean and the nearest specification limit, decreasing the sigma number and increasing the likelihood of items outside specification. (Wikipedia six sigma, 2009)

Figure 9: The normal distribution, which underlies the statistical assumptions of the Six Sigma model (Presentation Six sigma Teamcenter, 2009).

2.4.1 Role of the 1,5 sigma shift

Experience has shown that in the long term, processes usually do not perform as well as they do in short term, as the mean value tend to shift (due to environment, tool wear etc). As a result, the number of sigmas that will fit between the process mean and the nearest specification limit is likely to change over time, compared to an initial short-term study. To account for this real-life increase in process variation over time, an empirically-based 1,5 sigma shift is introduced into the calculation. It is said to have been introduced by Arthur Bender Jr. as a result of a work done in the automotive industry. According to this idea, a process that fits six sigmas between the process mean and the nearest specification limit in a short-term study will in the long term typically only fit 4,5 sigmas – either because the process mean will move over time, or because the long-term standard deviation of the process will be greater than that observed in the short term, or both. The widely accepted definition of a six sigma process is one that produces 3.4 defects per million opportunities (DPMO). This is based on the fact that a process that is normally distributed will have 3,4 parts per million beyond a point that is 4,5 standard deviations above or below the mean (one-sided capability study). So the 3,4 DPMO of a "Six Sigma process” does in fact correspond to 4,5 sigmas, namely 6 sigmas minus the 1,5 sigma shift introduced to account for long-term variation. This is designed to prevent underestimation of the defect levels likely to be encountered in real-life operation. (Wikipedia six sigma, 2009)

±1,5σ shift

LSL

USL

Mean

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2.4.2 Sigma levels

Table 1 below gives DPMO values corresponding to various Sigma levels. Note that this table consider that the process mean might shift by 1,5 sigma towards the side, with the critical specification limit. The defect percentages only indicate defects exceeding the specification limit that the process mean is nearest to. Defects beyond the far specification limit are not included in the percentages.

Table 1: DPMO values corresponding to various Sigma levels

Cpk DPMO Defect level (DPMO) 1,5 4σ 3,4 to 6,8 1,33 3,5σ 32 to 64 1,167 3σ 233 to 466 0,833 2,5σ 1350 to 2700 0,67 2σ 6200 to 12400 0,5 1,5σ 22750 to 45500

The Cpk value is a statistical measure of the process capability and it is preferable, when designing, to try to optimize against the Cpk value. This is because that the Cpk value also considers the sigma shift which is commonly known to occur in a manufacturing process. From table 1 it can be read that, if the designer optimize the design towards a Cpk of 1,33 it could be expected that 32 to 64 DPMO could occure.

2.5 Stack-up

Tolerance stack-ups can be evaluated either by analytical methods or by simulation. Analytical methods are traditional approaches to predict tolerance accumulation by summing the component variations. A simulation is a quantitative approach and the accuracy in the result depends on the quality of the assumptions of the number of iterations performed. (A. Gálvez Vega) In the following sections some of the most common methods used to assess stack-ups are introduced.

2.5.1 Worst Case (WC)

Worst-case analysis assumes that ALL parts lie within the specified and at their worst limits when used for tolerance allocation, often results in tight (and hence, expensive) tolerances on part dimensions.The method is the simplest and the most conservative one of the traditional approaches and does not take into account the laws of probability. The WC method is essentially necessary when an assembly is made out of few parts (5 or less) that cannot be allowed to interfere or be spaced too far apart. Worst Case analysis is used by designers to assure that all assemblies will meet the specified assembly limit. However, as the number of parts in the assembly sum increases, the component tolerances must be greatly reduced in order to meet the assembly limit. This can result in higher production costs, more non-conformances, etc. (A. Gálvez Vega)

Calculation: The parts in figure 10 should be assembled together and each of the parts (P1 to P5) has its own tolerances (T1 to T5) and nominal value (X1 to X5). From the calculations that will be

17

made below it can be answered how big the gap (Ynom) is, but also create an understanding of the tolerance distribution and how many deviations will occur.

Figure 10: Illustration of assembly stack-up (A. Gálvez Vega). The calculations below will show how WC is calculated for a typical case. Output mean: Ynom is the total nominal value for the assembly in figure 11.

nnom XXXY +++= ....21 , where X is the nominal value for each part (eq.1)

WCtoly is the WC total tolerance for each part in figure 10.

ny TTTWCtol +++= ....21 , where T is the tolerances (eq.2)

ynom WCtolYY ±=minmax/ (eq.3)

Figure 11: Graphical presentation of a possible calculated result (A. Gálvez Vega). Evaluating the results from the calculating analysis (eq.1-3) give the WC limits that are in conflict with the specified Ynom limit (outside LSL and USL) , which is illustrated in figure 11 (A. Gálvez Vega). The problem in figure 11 can either be solved by tightening the tolerances for each part of the assembly (figure 10) or by expanding USL/LSL. The Worst Case (WC) analysis gives no indication on how the results are distributed over the tolerance range or the probability of not meeting stack-up requirements (figure 11).

Ynom

P5

X5±T5

X2±T2 X3±T3 X4±T4 X1±T1

P3 P1 P2 P4

Ynom LSL USL

WCtolmin WCtolmax

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2.5.2 Root Sum Square (RSS)

Root Sum Square (RSS) is an analytical method to statistically predict the accumulation of tolerances in an assembly or a system. The RSS assumes that the components/parts are combined in a random manner. This means that the method exploits the probability that all the input distributions is at their highest or lowest limits at the same time. The RSS approach is exact only for linear transfer functions with component/part dimensions as input and that fit a normal distribution. The method requires nominal values, tolerance limits and process data such as distribution and standard deviation. It is also necessary to specify if these parameters are considered as short or long term data. (A. Gálvez Vega)

The RSS method divided into five steps:

1. Gather process data for input variables, type of distribution, position and scale parameters.

2. Verify that part distributions are independent, if not calculate correlation coefficient. 3. Calculate output mean and variance/standard deviation. 4. Calculate the RSS tolerance limits 5. Assess probability of an outcome outside specified limits.

The correlation coefficient measure if a linear relationship exists between two variables. If the correlation coefficient is 1 or -1 there is a perfect linear relationship between two variables. If the coefficient is 0 there is no linear relationship at all. For these calculations programs such as Minitab, Excel, Matlab, Crystalball, etc. can be used. (A. Gálvez Vega)

Calculation: With respect to figure 10 the calculations below are made with the RSS method. Output mean:

nnom XXXY +++= ....21 , where X is the nominal value for each part (eq.4)

Standard deviation:

∑=

=n

iiy

1

2σσ , if the input distributions are independent (eq.5)

∑ ∑= <

+=n

i jijiiy XX

1

2 ),cov(2σσ , if the input distributions are dependent (eq.6)

RSS tolerance limits:

∑=

=n

iiy TKRSStol

1

2 , is used if it is short term data K is usually 1.3 or 1.5 (eq.7)

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RSS tolerance limits:

ynom RSStolYRSSY ±=minmax/ (eq.8)

Using eq.4-8 you get figure 12. With the RSS method the distribution is also considered, as can be seen in figure 12. This gives more information compared to the WC method (figure 11). Figure 12: RSS show the gap distribution dimensions without consideration for 1.5σ shift (A. Gálvez Vega).

Calculate the probability that the result will end up outside USL and LSL:

y

nomLSL

YLSLZ

σ−

= (eq.9)

and y

nomUSL

YUSLZ

σ−

= (eq.10)

The Z value means that the upper and lower specified limit lie ZLSL or ZUSL standard deviations from the mean value (Ynom). If the process is considered as a short term, then Z=Zst. Before calculating the probability associated with the Z value it is necessary to transform Zst to Zlt (long term) by using eq.11 (A. Gálvez Vega).

5,1−= stlt ZZ (eq.11)

From appendix C DPMO can be read for a specific Z value.

2.5.3 Monte Carlo Simulation (MCS)

Monte Carlo Simulation is a probabilistic/statistical technique based on random number generation. The method uses probability distributions to represent the variability in component dimensions. It also assumes that components are combined in random manner. The method requires nominal values, tolerance limits, process data such as statistical distribution and standard deviation. (A. Gálvez Vega) The simulation calculates numerous scenarios of a model by using a random number generator to apply a small variation to each dimension (figure 13). The resulting assembly dimension is calculated by means of the

USL LSL

WCtolmin RSStolmax RSStolmin

Ynom

WCtolmax

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d1 d2

transfer function and compared to the assembly limits to determine if it is within specification (J. Shah). Figure 13: Principle of Monte Carlo simulation (J. Shah). MCS does not need to have a normal distribution as the method of Root Sum Square (RSS) to do simulations. The MCS is used to visualize different distributions (figure 14).

Figure 14: Distribution result of Monte Carlo simulation. Which tolerance analysis method that should be used depends on the situation e.g. number of tolerances, accessibility to process data, what should be analyzed, etc. The purpose of tolerance analysis is to study the accumulation of variation on geometric attributes of interest (dimension, location, orientation, etc). The most common case is analysis of clearance in assemblies. All dimensions and tolerances that affects the final variation is called contributors. The stack path, also called a tolerance chain, datum flow chain or dimension loop, is the shortest, continuous, series of specified dimensions from one feature of interest to another (start and end of stack). The analysis can involve multiple parts in an assembly or variations on a single part. WC analysis is done to determine the maximum and minimum values resulting from the limits specified on the contributors. Statistical analysis is used to determine the full frequency distribution of the computed frequency distribution of the contributors. Whether tolerances are allocated on the basis of WC or statistical analysis is a matter of economy. WC design guarantees 100% interchangeability and assemble-ability of parts but is costly. By relaxing the requirement to say 99,97% acceptance, tolerances can be more liberal, thus reducing manufacturing cost. However, one must look at the cost of rejected parts (or selective assembly) to see if the reduced manufacturing cost result in a net gain. (J. Shah)

A= f(d1, d2, d3) P(A)

A d3

p(d2)

p(d3) p(d1)

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2.6 How to use a Target system

The purpose of a target system is to lock a part or a sub assembly to its six degrees of freedom in space (Translation X, Y and Z and Rotation X, Y and Z). A number of different target systems exist and they are used in various industrial situations. figure 15a-c shows an orthogonal 3-2-1 target system with six locating points. The three primary locating points, A1, A2 and A3 (figure 15a), control three degrees of freedom, translation in Z (TZ), rotation around X (RX) and rotation around Y (RY). (R. Söderberg, 2006) Figure 15a: Locating points A1, A2 and A3 The two secondary locating points, B1 and B2 (figure 15b), control two degrees of freedom, translation in X (TX) and rotation around Z (RZ) (R. Söderberg, 2006).

Figure 15b: Locating points B1 and B2 The last locating point, C1 (figure 15c), controls one degree of freedom, translation in Y (TY) (R. Söderberg, 2006). Figure 15c: Locating point C1

Y

Z

X A3

A1

C1

B1

B2

A2

Y

Z

X A1

A3

B1

B2

A2

X

Y

Z

A3 A1

A2

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The fundamental problem with all types of target systems is that they are coupled by nature, i.e. one locating point controls more than one degree of freedom. The orthogonal 3-2-1 target system is the least coupled among the locating systems since it enables the translations and the rotations to be decoupled. (R. Söderberg, 2006) The placement (definition) of the locating points in the target system will affect the robustness of a part or assembly. The main idea when working with locating points is to place all the points, in each plane, as far away from each other this to make the part robust/stable (figure 16).

Figure 16: Optimal placement of the locating points for a box (2D and 3D view). In the manufacturing industry, with its complex shapes and definitions of a product, it is not always possible to use the theoretical optimal setup of the locating points. But it is always possible to study and optimize the locating points so they are placed in the best way possible.

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3. Methodology This chapter will inform about the methods being used in this thesis work. Since the challenge includes capturing the current ways of working, the means of identifying current practices should significantly influence the quality of the results.

3.1 Interviews

Interviews are often the easiest way to achieve information about a person perspective of a certain experience. An interview can be organized in different ways but it is a discussion between two or more people. An interview is divided into categories depending on its structured level, which means that an interview can be unstructured, structured or half structured. (A. Lantz, 1993)

3.1.1 Unstructured interview

In an unstructured interview the person who is leading the interview asks wide open questions allowing the person who is being interviewed to answer freely. This also gives the person doing the interview a chance to make an attendant question and obtain a deeper understanding in the subject. This interview method is very good when the person making the interview does not have much knowledge about the subject. Since the interview is time consuming, this method is best used on a few numbers of people. (A. Lantz, 1993)

3.1.2 Structured interview

In a structured interview there are pre-made questions in a predefined order, asked by the one making the interview. The person being interviewed can either answer freely or by specific alternatives. To know what areas that should be explored and how to develop the questions so that desired information is obtained, a lot of knowledge is needed. This kind of interview method is usually used on a larger number of people and is often short interviews. An alternative for structured interviews is questionnaires. (A. Lantz, 1993)

3.1.3 Half structured interview

Half structured interviews is a combination of the structured interview and the unstructured interview methods. The person making the interview knows in advance what area that is of interest and partly what kind of questions that is going to be asked. Some knowledge is necessary about the subject area. The questions can be open or specified, and thereby the person being interviewed can answerer freely or by specified answers. This gives a better opportunity to ask attendant questions in comparison to the structured interview method. (A. Lantz, 1993)

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3.1.4 Analyzing interview material (qualitative data analysis)

According to A. Bryman (2004), coding is the starting point for most forms of qualitative data analysis, although some writers prefer to call the process indexing rather than coding. The principles involved have been well developed by writers on ground theory and others. Some of the considerations in developing codes are as follows:

• Of what general category and topic is this item of data an instance? • What does this item of data represent? • What is this item of data about? • What question about a topic does this item of data suggest? • What sort of answer to a question about a topic does this item of data imply? • What is happening here? • What are people doing? • What do people say they are doing? • What kind of event is going on?

Steps and considerations in coding:

• Code as soon as possible • Read through initial set of transcript, field notes, documents, etc. without taking any

notes. • Do it again. Make marginal notes of significant remarks and observations (coding) • Review your coding. Look after the same codes and connections between codes. • Consider more general theoretical ideas in relation to codes and data. Outline

connection between concepts and categories. Develop hypotheses about the linkages and go back to data to confirm.

• Remember that any one item or slice of data can and often should be coded in more than one way.

• Do not worry about generating what seem to be too many codes. It can be tidied up later.

• Keep coding in perspective. Do not equate coding with analysis. The coding is a part of the analysis.

One commonly mentioned criticisms of the coding approach to qualitative data analysis is the possible problem of losing the context within which they appeared, such as a particular interview transcript. The social setting can be lost. (A. Bryman, 2004)

3.2 Survey (questionnaires)

A survey is used to systematically map relevant information within a specified group and identify their point of views when the same questions are asked to a number of people. The survey contains predefined questions with answers and questions where the target group can give their own opinions.

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3.3 Matrix

A matrix is used to compare different criteria against each other (two and two) (Table 2). When comparing two criteria they will share the value of two, for example criteria A is compared with criteria C. If they are evaluated to be of equal importance, then both of them will get the value of one. But if one criterion is more important than the other, that criterion will get the value of two while the less important gets the value of zero. (Sommardesignkontoret Valdemarsvik, 2004) So it can bee read from table 2 that criteria A is less important then criteria C Table 2: Matrix (Sommardesignkontoret Valdemarsvik, 2004).

Criteria A B C D Total Rank A 1 2 0 0 3 3 B 0 1 1 2 4 2 C 2 1 1 1 5 1 D 2 0 1 1 4 2

Total 5 4 3 4 16

3.4 Brainstorming

Brainstorming is a method that is used to solve problems or generate new ideas. The method is usually carried out in a group of five to twenty people that are encouraged to generate ideas surrounding a problem, and how it should be solved. In this way a lot of ideas are brought out to the table even though not all of them are applicable. (D. Ullman, 2008) Concept:

• Ideas cannot be criticized until the brainstorming is done. • Spontaneity is encouraged. The starting point is that all ideas are good ideas and an idea

that does not seem so good can be developed into a great idea. • Quantity of ideas is important since it often generates quality. • All participants develop and improve each other’s ideas.

Brainstorming practice is a common way to generate many ideas in a short period of time and it is also effective for evaluation of existing ideas.

3.5 Case study (Demonstration)

Rather than using samples and following a rigid protocol to examine limited number of values, case study methods involve an in-depth examination of a single instance or event: a case. They provide a systematic way of looking at events, collecting data, analyzing information and reporting the results. As a result the researcher may gain a sharpened understanding of why the instance happened as it did, and what might be important to look at more extensively in future research. Case studies lend themselves to both generating and testing hypotheses. (Wikipedia case study, 2009)

3.6 Simulation

A computer simulation is an attempt to model a real-life or hypothetical situation on a computer so that it can be studied to see how the system works. By changing variables, predictions may be made about the the system. Computer simulation has become a useful part of modeling many

26

natural systems in physics, chemistry and biology, and human systems in economics and social science (the computational sociology) as well as in engineering to gain insight into the operation of those systems. Traditionally, the formal modeling of systems has been via a mathematical model, which attempts to find analytical solutions enabling the prediction of the system from a set of parameters and initial conditions. Computer simulation is often used as an adjunct to, or substitution for, modeling systems for which simple closed form analytic solutions are not possible. There are many different types of computer simulation, the common feature they all share is the attempt to generate a sample of representative scenarios for a model in which a complete enumeration of all possible states would be prohibitive or impossible. (Wikipedia simulation, 2010) Several software packages exist for running computer-based simulation modeling (e.g. Monte Carlo simulation, stochastic modeling, multimethod modeling) that makes the modeling almost effortless. (Wikipedia simulation, 2010)

3.7 Movie

A movie is an easy way to show a sequence that could be hard to visualize with only pictures.

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4. Implementation The following chapter describes how the thesis work has been implemented to receive satisfying results regarding literature study, interviews, simulation of the case and a chapter describing the case problems.

4.1 Research Method

The work method through this thesis work can be described with help from figure 17. The six different part segments have been conducted in a linear way of working, though some parallel work has been done.

Figure 17: The different part segments throughout the thesis work

4.1.1 Literature study

To get a better understanding and a deeper knowledge about Geometry Assurance (GA) and the Global Development Process (GDP) at Volvo Aero, a literature study was made. A study of the automotive industry was conducted since they have the GA process well implemented in their process. The literature study consisted of reading books and articles about the different subjects. The internet and the company’s intranet (Violin) was also used to gather as much information as possible.

4.1.2 Interviews and analysis

For a big overall picture of the company and how they are working in general at Volvo Aero, seven unstructured interviews were made (appendix D). This method was chosen because of its ability to gather as much general information and knowledge as possible about the subject and Volvo Aero. The more structured interview material (appendix E), used in the half structured interviews, was created based on the information of the GA process in chapter 1.4. This method was chosen because of its ability to collect much information of a more specific area. The half structured interviews were used on 19 people with different backgrounds and experience from the company. From the half structured interview material a qualitative data analysis was performed to gather and select the key problems (figure 18). The analysis of the data was performed directly after each interview to secure as much information as possible.

Planning and formulation of the assignment

Literature study

Modeling and validation

Analyzing Data collecting Suggestion for improvement

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Interview notes

Making a fair copy of the notes

Dividing into comparable data Create a detailed problem selection table

Making a problem/needs flow chart Select the key problems

Figure 18: Interview notes breakdown strategy From the interviews a GA process circle was created to evaluate if the theoretical description of the GA process in chapter 1.4 could be transferred into a GA process for Volvo Aero. A problem matrix and a problem diagram were constructed to select the final problem for further work and solution suggestions. After some discussion the thesis work was delimitated to focus on visualization regarding variation and stability in early stages of the GA process.

4.2 Case

A case was defined and analyzed to show on the possibilities of the suggested improvements in early stages of the GA process. To choose a case and a tool some steps were run through to secure their quality.

4.2.1 Brainstorming

After analyzing the interview material a few problems were selected for potential improvement. A group of people (that was well-grounded in the subject) was gathered for a brainstorming to find suggestions of what kind of case and tool that could be used to be able to show the method of the analysis. Three software were potential thought of for possible further use; TSV, RD&T and VisVSA. For a more detailed description of each program see appendix F. A few different cases were gathered (Table 4) and discussed regarding pros and cons, and what would be possible to research in the remaining amount of time and still give a satisfactory result.

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Table 4: Brainstorming for cases and tools.

Case Description Problem Tool

Case 1 Mount a tube in a strut

A tube has one variation and a strut has another variation. The problem is to see if the tube can be mounted in the strut despite the effects of the variations.

RD&T, VisVSA or TSV

Case 2 Mount a shifting gear to

another part

Two different reference planes, one for the casting and one for the finished part. Need to analyze the consequence of a proposed change of casting drawing.

RD&T or VisVSA

Case 3 Mount an air tube

An air tube should be mounted inside a combustor structure near a wall without contact. How should the necessary drawing requirements be defined with regards to minimal effect of variation?

RD&T, VisVSA or TSV

Case 4 Fixture assemblies Long and difficult tolerance chains where it is hard to see the total variation.

RD&T, VisVSA or TSV

Through analysis of the case information and considering the available time/possibility to achieve a satisfactory result, Case 3 with the Computer Aided tolerancing Tool RD&T was chosen. A Specification of requirements was written for the software (RD&T) to evaluate if it supported the requirements of Volvo Aero (appendix G).

4.2.2 Case description and problem definition

NEWAC is a program financed jointly by the European Community and the participating companies. The focus is to work towards one of the ACARE goals (reduce CO2 emission by 50% by year 2020) by improving the efficiency of the engine core. NEWAC SP4 is a subprogram led by MTU. Volvo Aero participates in the design of the combustor case for the engine with active air cooling. (Volvo Aero Corporation, 2009)

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The idea is to use air that passes through the fan (appendix A) and lead it through the combustor case, using a pipe construction. This technique could be used to cool down the temperature inside the engine and improve the efficiency (figure 19).

Figure 19: Cooling pipe inside the combustor structure The pipe consists of four parts (OC, mid strut pipe, middle sect pipe and piping) that are mounted inside the combustor case (figure 20). There is a need to get an understanding for and predict how the variation and stability of the whole part could affect the final result. This would help to forecast if it is possible to mount this pipe or not in the combustor case.

Figure 20: Set up for pipe construction Definition of the critical area After some research regarding the pipe structure, three critical areas where found. Only one area was investigated and analyzed in this thesis work. The critical area is described below.

OC

Mid strut pipe

Middle sect. pipe

Piping

Slide

31

The middle sect pipe and the piping need to be as far away from combustor chamber as possible, without touching the surface of the combustor case. This is to ensure that the heat in the combustor chamber has as little affect on the air in the pipe structure as possible (figure 21).

Figure 21: Middle sect pipe with min. and max. distance from the combustor case and the combustor chamber. To get an answer to the problem described above four questions had to be investigated:

1. Does the rotation of the middle sect pipe increase the number of deviations, and make it more difficult to meet the requirements of not touching the combustor case (figure 22).

Figure 22: Rotation of the Middle sect pipe.

Minimum

Maximum

Combustor chamber

Combustor case

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2. Does the parallelism and surface finish contribute to the final deviation (figure 23)?

Figure 23: Parallelism and surface finish.

3. How big is the profile variation?

4. How much clearance is needed to handle the vibration that occurs?

The last thing that has to be taken under consideration during the analysis is how all parts should be verified. It is important to be able to verify the results so they can be used for Lessons learned (LL) and create better conditions in upcoming projects.

4.2.3 Simulation and analysis

Before starting the analysis a few assumptions had to be made:

• The parts are considered to be rigid and guided in the locating points. • No consideration is taken regarding how the thermal expansion would affect the final

result. • Vibration effects on the final result are taken under consideration and are assumed to

be 5± mm. • In the optimization of the process capability, the Cpk was set and optimized to 1,33.

This to achieve a 4σ process (99.994% of the manufactured parts should be inside the specified tolerance limit).

• Only critical area 1 of the NEWAC project is investigated in this analysis which means that simulations have only been made on the middle sect pipe.

A research study regarding how previous pipes have been defined and manufactured earlier at Volvo Aero was made by talking to people in production and by analyzing drawings from

33

the archive. From the drawings DWG NO 9295M10 and DWG NO 9220M87, target system setups where defined and profile tolerances were assumed and used in the NEWAC case.

• Stability analysis

A stability analysis is used to define the target system and to be able to compare the connection between the input and output variation of different setups. A lower number means better stability. The stability analysis was made on the middle sect pipe in X, Y and Z-axis, but also for the entire part. To perform and visualize the stability analysis, the locating points was defined to lock the rotations and translations of the part in X, Y and Z-axis (figure 15c).

1. Locking RY, RZ and TX with A1, A2 and A3. 2. Locking RX and TY with B1 and B2. 3. Locking TZ with C1.

After preliminary locking every degree of freedom, the locating points were moved around to find the setup that gives the most stability.

• Variation envelope

After the stability analysis, a variation envelope was created to be able to visualize the total volume the parts require. This was done with respect to allowed tolerances and defined target system. The variation envelope is generated through the MCS.

1. Choose part for simulation. 2. Define the number of iterations. 3. Run simulation.

After running the variation envelope the tolerances were adjusted until a satisfying result was obtained. The result is then used to perform clearance analysis.

• Profile tolerance

To be able to visualize the profile tolerances a clearance was added to the variation envelope. This way, the WC could be visualized for e.g. vibration, profile tolerances or other added variations that needs to be considered.

1. Choose the variation envelope that the clearance should be added to. 2. Specify the clearance.

• Clearance analysis

Clearance analysis uses the variation envelope to evaluate the distance from the varied part to its surroundings. With help of color coding the clearance analysis shows the areas that can cause problems.

1. Choose part 1 that has the variation simulation. 2. Choose the part that the clearance is going to be calculated against, compared to

part 1.

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3. Select area of importance to be analyzed. 4. Run simulation.

After running the clearance analysis the tolerances were adjusted to receive a satisfying result.

• Measure points and stack-up simulations/analysis The stack-up simulation/analysis is based on the same ideas as the variation envelope. But, instead of running MCS on the whole nominal 3D model, the stack-up simulation runs MCS only for a specific point assigned to the surface of the 3D model. Measure points (MP) were assigned to be able to run a stack-up simulation.

1. Choose the nominal part with the target system. 2. Create a new point on the part. 3. Create a Measure and assign it on the new point (MP). 4. Assign a Range for the point MP (if other tolerances need to be considered e.g.

vibration, part variation). 5. Run the analysis.

After running the analyses the tolerances were adjusted until the requirements were met.

• Interpreting the results The results of each simulation and analysis was interpreted and discussed with the employees in the NEWAC project. These discussions were held to feed back information, but also to confirm or point out flaws of the assumptions that have been made.

Parallel to the simulations and analysis, a research study was made to understand what data and knowledge that should be needed if an implementation of the software (RD&T) should be implemented into the Volvo Aero working system (chapter 6.3.7).

A suggested roadmap was created that describes how it is possible to work with the variation and stability analysis method in general (chapter 7.2). Also if the RD&T software should be chosen, a quick walkthrough was created so that the “beginner” quickly can run the different simulations that have been described above (appendix O).

4.2.4 Survey

A survey (appendix H) was conducted on 11 employees to get their perception of the work load divided among three areas; 3D modeling, generating drawings/analysis and handling rework.

4.2.5 Movie sequence

A movie sequence was created to increase the understanding of the visualization of the variation method. The movie sequence can be found in appendix I.

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5. Current State Description For a deeper understanding of the problem this chapter contains information about the current state at Volvo Aero regarding Design for Robustness, the Global Development Process and the Geometry Assurance process.

5.1 Phi

Volvo Aero has a product philosophy (figure 24) named Phi. The philosophy describes the importance “to balance and optimize between fulfillment of Product Cost, Technical Requirements and Producibility”. (Volvo Aero document PHI, 2009)

Figure 24: Volvo Aero’s product philosophy (Volvo Aero document PHI, 2009).

5.2 Design for robustness (DfR)

Volvo Aero is working with Design for Robustness which means the ability to manage variations so that Volvo Aero is able to balance and fulfill customer requirements. (Volvo Aero documents DfR, 2009)

• Internal customers (profitability, producibility) • External customers (reliability, functions)

The DfR vision is to consistently and efficiently design and produce a product that;

1. Supports the customers’ expectations of functionality and quality, and 2. meets expectations for producibility – generating revenue, and 3. has minimal sensitivity to all sources of variations (noise factors)

Volvo Aero has defined different Centers of excellence (CoE), but recently a few new have been created, among them Design for Robustness (DfR). Even though different CoE have been defined, they are not obvious and it is hard to point directly at one CoE for a certain problem/question.

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5.3 Operational Management System (OMS)

In order to live up to Volvo Aero’s goal as Best Partner the company must have quality work from all employees, which lies in the workers responsibility. The Operational Management System (OMS) is an important tool for employees to get an understanding of what Volvo Aero does, how it is done and how all the pieces and processes fit together. Having a true understanding of the employee’s interactions with each other and each other’s working processes will help Volvo Aero reach their goals the best way possible. (Violin homepage, 2009) In OMS a description of the Global Development Process (GDP) can be found, which describes the Volvo Aero development process.

5.3.1 Global development process (GDP)

At Volvo Aero, the product development process is a gated process, named GDP. The GDP is divided into six phases (eight gate phases), each of which is intended to indicate a certain focus in the project work. Among the six phases five decision points and eight gates are defined in the Volvo Aero GDP. The GDP is the full model, to be applied differently to different projects/companies. Gates and gate criteria can be combined, added or deleted to suit the unique needs of each project/company. (VOLVO)

The GDP is described as a linear working process. It illustrates the functionality at Volvo Aero (what should be done, who does what, how is everything executed and why), but not when an activity starts or ends.

This is how Volvo Aero’s GDP works in theory, but according to the employees this is not always how it works in practice. The gates are more used to check what the project has done and not what the project should have done. If the gate reviewers are not aware of what they should check, than it can be difficult for the project to progress if some work has been started earlier then necessary, but is not completed. This work will then be subject for questioning even if it is supposed to be checked at a later gate. It can also result in that work that should have been done is missed.

5.4 Volvo Aero Geometry Assurance process

The GA process is used in the automotive industry, including other companies within the Volvo Group, but has not yet been established at Volvo Aero. Although some employees at Volvo Aero have experience/knowledge of the GA process from earlier employment in the automotive industry. The GA process is not intended to replace the GDP, but rather help the discussion around the subject from a holistic view. A description of how the GA process at Volvo Aero works today (figure 25) was formed from the employee’s point of view and may not reflect the whole truth. This was done using the performed interviews (appendix L) and the general description of the GA process found in chapter 1.4.

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Figure 25: The geometry assurance process

5.4.1 Concept phase:

In the concept phase the project works with their requirements (tolerances) in different approaches i.e. bottom-up, top-bottom or from one interface to the other. It is not clear in what way the requirements should be handled and it is therefore hard to obtain a good picture of how the employees at Volvo Aero are working with this. It can be analyzed that the most common strategy used at Volvo Aero is the bottom-up approach; this means that they first put all the subparts together and then verify the total part to see if it is within the requirements that have been set. The tolerance breakdown is based on earlier drawings, experience and knowledge from the designer and the manufacturing leader.

When generating drawings the designer has a drawing portal (under construction) which is based on the ASME (American Society of Mechanical Engineers) and Volvo Aero standards. The portal is used to support the designer and is supposed to minimize the variation of drawings and target system. The locating points (target system) are set by the designer and are primarily intended for verification of the assigned measurements in the 3D model. The target system cannot always be used for that purpose in manufacturing (measure operators). The target system is neither optimized for fixturing.

Further on in the concept phase the tolerance analysis (stack-ups) is performed. The variation analysis that is made in the computer aided design tool (CAD tool) is usually done through adding extra material “manually” to the model and concluded if the requirements are fulfilled or not. This way the analysis is based only on the worst case (WC) and no statistical result will be visualized. Most stack-ups, that are calculated, are made in 2D outside the CAD tool and methods such as WC and root sum square (RSS) are used. The stack-ups are mostly done by the designer, with help from the manufacturing leader and are based on knowledge and experience. The designers do not use experience captured in the inspection and process control system (KPS) because they feel that there is “no data” that can be used, even though Volvo Aero has been measuring parts during all its years in the aviation industry.

When the concept phase goes into the verification phase, a detailed operation sequence and an inspection document are created. The documents contain information about how the component should be manufactured, for example which tools to use for measuring, what and how it should be measured. These documents are based on knowledge and the requirements that have been generated from the designer according to his/hers own experience.

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5.4.2 Verification phase:

In the verification phase the tooling manufacturer creates fixtures using drawings, CAD tools, operation plans and people’s experience/knowledge. In this process they try to use the same locating points that have been defined by the designers. However, this is not always possible, and a new target system has to be created. The tooling manufacturers work together with designers in the concept phase, but experience that they have little influence on the decisions that are made.

Measuring tools are defined at Volvo Aero but manufactured by a supplier. Since external resources are used when creating tools, old tools are reused to the extent possible. However, this is not always possible and often specialized measuring tools have to be ordered, which cost money.

In the end of the verification phase a numerical control program (NC-program) is created offline and all the steps in the operation sequence are visualized and animated. This is done to verify and reflect on operating sequences and visualize potential problems such as collision between tools and material/fixture, possibility to remove material etc. The work is based on a nominal model, operation sequence, knowledge/experience, CAD tool (UG), an operation simulation (Vericut) and a database where all the machines (in Volvo Aero’s manufacturing line) are visualized in 3D. It also contains all the tools that can be used in manufacturing. The database includes 3D models of the fixturing/machine table, but they are not detailed enough to be used by the tooling manufacturer when creating fixtures. With the aid of this database the NC-programmer can assign certain values i.e. material, diameter, radius, etc. and the system responds with which tool that is best suited for the planned operation. To verify the NC-program the programmer tests it in the machine that it was programmed for to see if any last adjustments need to be made. Offline programming has minimized the need to program directly into the machines, which has saved time and money for the company. Today a lot of mistakes are found when the NC-program is created, which often results in delays and money loss. Volvo Aero can also perform robot simulation to visualize the operating sequence of a robot. This is a relatively new method at Volvo Aero.

5.4.3 Production phase:

During the manufacturing of a component in the production phase, deviations can occur which can cost a lot of resources for Volvo Aero. This causes frustration between the designers and people in production when a change has to be made, especially if it is discovered late in the projects. When the component reaches the start of production (in-house) an inspection database (KPS) capture the measurements that are described on the inspection plan document. The operators approving the measurements are certified to assure that the measurements are executed in the right way. An inspection document is used by the certified operators. All the data that is gathered is stored in a database, but when several measurements are taken towards one requirement, only the value that most deviate from the nominal value is registered in the KPS statistics. Also, tools for “go/no go” measurements are used to check if the result is within the tolerances and does not result in a numerical value in

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the statistics. It is possible to access the inspection data and get statistics for all the measuring points manually, and not only for the values that are registered in the KPS statistics.

If a problem (deviation from requirement) occurs in the production phase, a root cause problem analysis is made to locate the problem and find solutions. This is done based on data and experience. The reuse of knowledge/experience, information and data is not satisfying at Volvo Aero according to the employees. It is hard to know how and when experience can be saved and reused. The project has a white book where experience should be documented. However, the white book is often closed as confidential, even to the author if he/she changes project or the project is closed. It is thereby not often used. Volvo Aero is however working towards, and is getting closer to, a better reuse of experience regarding variation. In the cases of components being manufactured outside Volvo Aero, the design is set in the same way and with the same consideration to manufacturing as for in-house components. Here the designers also rely much on supplier experts for support.

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6. Results This chapter displays the final results of the interviews, visualization of the improvement areas and the final result of the case study.

6.1 Interviews

From the unstructured and half structured interviews a roadmap was created to show the link between all the steps in Volvo Aero’s working process (appendix J). A plot of which activities that are preformed when was generated from the structured interview material (appendix K). Appendix K shows that people have different opinions about when an activity is performed. This indicates that more communication and understanding regarding the GDP needs to be implemented at Volvo Aero. Figure 26 was created to visualize how the GA process loop, which has been described in chapter 1.4 could be applied on Volvo Aero. The picture is based on the interview material and current state description (chapter 5.4).

Figure 26: Volvo Aero’s GA process today. Todays GA process (figure 26) has now been visualized with four arrows instead of three (figure 25). Todays GA process circle is visualized as not fully closed, this because of the insufficient reuse of LL, no searchable database and not optimal use of the white books (figure 26).

6.1.1 Improvement areas

After the qualitative data analysis based on the half structured interviews, it was clear that the employees experienced areas that needed improvements. The improvement areas were divided into four different groups: Concept, Verification, Production and General process problems (appendix L).

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From appendix L seven problems/improvement areas were chosen for continued work and they are described in the list below (A-J).

A. In some areas of the process standards and design practice (DP) are not defined. B. Difficult to handle the requirements break down (tolerance chains). C. The methods of working with variation analysis are not satisfying. D. Problems with continuity of target system throughout the process. E. Tolerance analysis and stack-ups are based mostly on experience. F. Root cause analysis is made but not much support for it. G. Insufficient reuse of inspection data. H. The way of saving experience and knowledge is not satisfying. I. Communication problems. J. The projects rely too much on experience and knowledge when developing

components.

Appendix M describes, in tree diagrams, possible solutions for each problem area. It is shown that I and J seem to be the results of problems A and H than actual problems them selves. This means that if A and H can be improved, then I and J could automatically benefit from this. A problem matrix (Table 5) was created to select the problem that seems to be most critical. Table 5: Problem matrix.

Problem A B C D E F G H I J Total Rank A 1 2 2 2 2 2 2 2 2 2 19 1 B 0 1 1 2 1 2 0 0 2 2 11 4 C 0 1 1 1 1 2 0 1 2 2 11 4 D 0 0 1 1 1 2 0 0 2 2 9 5 E 0 1 1 1 1 1 0 0 2 2 9 5 F 0 0 0 0 1 1 0 1 2 2 7 6 G 0 2 2 2 2 2 1 1 2 2 16 2 H 0 2 1 2 2 1 1 1 2 2 14 3 I 0 0 0 0 0 0 0 0 1 1 2 7 J 0 0 0 0 0 0 0 0 1 1 2 7

Total 1 9 9 11 11 13 4 6 18 18 100

From the problem matrix (Table 5) problems A, G and H seem to be the most important problem areas at Volvo Aero today. However, Volvo Aero is already working with these areas in one way or another (see the list below).

A. Volvo Aero is developing the GDP so it will contain more and better described standards.

G. A project is in progress to develop the KPS to be more useful for the designer. H. The DP is frequently growing with more instructions, for every project that is

completed/in progress.

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0

5

10

15

20

A B C D E F G H I J

Main problem

Middle problem

Lowest problem

Figure 27: Problem values.

After A, G and H the main problem areas seem to be B, C, D, E and F (figure 27).

With the aim to improve the chances of a successful fabrication process, minimize costs through reduction of deviations and improve the relation (understanding) between designer and 3D model, the thesis work was delimitated. Focus became visualization of variation, stability and tolerance analysis (C and E). Especially implementation in an early stage of the GA process (early concept phase).

6.2 Variation analysis at Volvo Aero

Today 2D stack-ups and/or 3D WC manual visualizations are made, which leads to problems regarding understanding the big picture of a component and its tolerance chains. To go from 2D stack-ups and try to visualize it in 3D is not an easy task and may cause confusion. Table 6 shows a basic description of how the process works today and what Volvo Aero should strive to achieve when working with variation analysis. It can be read from table 6 that Volvo Aero has support regarding variation analysis from designers, manufacturing leaders, 2D stack-ups etc. However, the company lacks support from a potential GA process and the possibility of 3D stack-ups, 3D variation and stability analysis in product development projects (PD projects). These three could increase the possibilities of decreasing deviation if used in the right way. Table 6: Variation analysis.

Current situation at Volvo Aero Future ambition at Volvo Aero 3D model 3D model 2D drawing 2D drawing Designer Designer Manufacturing leader Manufacturing leader Support by the GA process 3D Variation envelope and Stability analysis 2D Excel Stack-ups WC and RSS 3D Stack-ups MCS DP and Standards DP and Standards Capability Database (Not used by the Designer)

Capability Database (searchable by the Designer)

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6.3 Case study

The analysis of the case study has been focused on the first problem regarding the distance between the middle strut pipe and the combustor case. The analysis below describes the approach that was used for solving the problems in the NEWAC case. The full analysis can be found in appendix N.

6.3.1 Stability analysis

From the stability visualization it is possible to find and choose the locating points that will help to find the optimum to a robust design. The result from varying locating points in the stability analysis is presented in figure 28a and b. Figure 28b also shows that the simulation of stability can be performed not only for the total part but also in X, Y, Z-axis. These simulations are run with locating point tolerances of 1 mm and the bigger the blue area the more stable is the component. The Root mean square (RMS) value also describe the robustness of the component and as it can be read from below has the spawn decreased in figure 28b copared to figure 28a. RMS: 1,39-57,04 RMS: 1,41-23,69

Figure 28a: Stability analysis for the first set of

locating points.

Target system

Locating point

A1 P1 A2 P2 A3 P3 B1 P2 B2 P3 C1 P3

Target system

Locating point

A1 Own defined x, y and z coordinates for A1

A2 Own defined x, y and z coordinates for A2

A3 Own defined x, y and z coordinates for A3

B1 P2 B2 P3 C1 P3

Figure 28b: Stability analysis for the second set of locating points.

X-axis

Y-axis

Z-axis

P2

P3 P1

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As shown in figure 28b the locating point can be changed to optimize the stability result. In this way many concepts can be evaluated in a short period of time. The stability analysis is used to investigate the connection between the input and output variation. This means that the stability analysis only consider the placement of the locating points and not the assigned tolerances.

6.3.2 Variation envelope

After the stability analysis, a variation envelope was performed (figure 29) to be used for further clearance visualization. The variation envelope was performed using Monte Carlo simulation (MCS), with 1000 iterations and 1 mm tolerance at the locating points. The variation envelope gives a statistical indication of the total volume that the pipe could move within, with the specified setup of locating points.

Nominal- Variation- model envelope

Figure 29: Total variation envelope of the pipe. Changing the positions of the locating points will have an effect on the variation envelope. The more robust the locating scheme is, the smaller the volume will be from the variation envelope. Figure 30 shows how the variation envelop simulation could differ when two different location scheme has been defined, but have the same tolerances (the right picture get a smaller variation envelope compared to left). In figure 30 the variation envelope was performed with 10000 iterations, using MCS, with 1 mm tolerance at the locating points.

Figure 30: Variation envelope with respect to stability of the locating points.

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6.3.3 Addition of profile tolerances

To generate a more accurate picture of the reality, profile tolerances should be added to the analysis. In the variation envelopes above only the variation created by the target system has been taken under consideration. In figure 31 a 2 mm profile tolerance has been added.

Figure 31: Cut through with added clearance on the volume analysis. From this the WC of the volume variation can be visualized with profile tolerance. This simulation can also be used to visualize other contributors to variation e.g. vibration. The simulation only generates a WC result and a different, maybe better, result could be achieved if the profile tolerance was statistically added.

6.3.4 Clearance analysis

The clearance analysis, shown in figure 32, visualizes the gap between the combustor case and the simulated volume with added profile tolerances of the middle sect pipe. The color coding is: red for 0 mm or “clash” (intersection) between the middle sect pipe and the Combustor case, yellow for 0 - 5 mm clearance and green for a clearance of 5 - 10 mm. The gray area represents a distance that is more than 10 mm away from the combustor case.

Figure 32: Color simulation of the distance from the middle sect pipes to the combustor case. Figure 33 shows another way to visualize the collision with the combustor case. Two results are imposed on each other (gray and purple) where the gray pipe has a tolerance of 2 mm and

Volume analysis Volume analysis with added profile tolerance

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the purple pipe has a tolerance of 1 mm at the locating points. The yellow area inside the middle sect pipe shows the intersection with the combustor case.

Figure 33: Pipe collision with combustor structure.

6.3.5 Measuring points and stack-up simulations

Because of the critical area between the middle sect pipe and the combustor case a measure point (MP) is placed on the middle sect pipe (figure 34) for variation simulation and stack-ups.

Figure 34: Measuring point placement. A Cpk of 1,33 has been assumed and used when generating stack-ups in this case. It is described in Volvo Aero’s standards that the process needs to have a capability of at least Cp =1,5. A Cp value is not a good reference because it does not take the 1,5σ shift under

Measure point (MP)

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consideration. In these stack-up analyses (figure 35) it is possible to steer the tolerances to a specified goal, in this case Cpk =1,33.

Figure 35: Stack-ups for different cases. Different stack-ups (with different locating point setups and tolerances) can quickly be generated for one measure point (MP) with assigned lover specified limit (LSL) and upper specified limit (USL) of ±1 (figure 38). It can then be calculated how many defects per million opportunities (DPMO) each case generates using Excel documents that are available at Volvo Aero or by calculating (eq.9 and eq.11) and using the Z-tables (appendix C). Through the contribution analysis it is possible to identify which locating point/tolerance that contributes most to the variation result (figure 36).

Figure 36: Contribution of each point. Depending on what is desired, each locating point contribution can either be optimized so that all the tolerances contribute equally or that one tolerance contributes entirely to the

NOT OK OK

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variation. In this way the distribution of the variation can be chosen to be able to focus on the most contributing tolerances. This is done by changing the tolerances so the required result is achieved.

6.3.6 Interpreting the results

Using the simulations the following questions where analyzed:

• Which setup of locating points that generates the highest stability to the part? • Which case that generates a total volume that will not clash with the combustor

structure? • Which case fulfills the assumed Cpk? • How many DPMO each case generates? • Which tolerance/tolerances contribute most to the variation? • Does the rotation of the middle sect pipe afflict the final result? • Does the surface finish/ parallelism have any contribution to the final result?

After answering the questions above, a discussion was held together with the designers of the NEWAC project to introduce the information achieved of the analysis. It was concluded that if this case study should be continued, a discussion should be held with people from production to find the best solution from a manufacturing point of view and establish the assumptions that has been made during the analyses.

6.3.7 Study of data/knowledge “needed”

From the study of what data/knowledge is needed the following areas were found to be important when working with the variation analysis method. Knowledge:

• Experience of 3D-modelling • Knowledge about target systems (3-2-1) • Experience and knowledge about Six sigma and Cp/Cpk-values

Data:

• Education material (Instruction manual) about the program (need to be developed to fit the needs on Volvo Aero)

• Montage sequence of the component • Drawings with description of the target system (if not known they can be estimated) • 3D-model in VRML-format (needed for RD&T and can be exported directly from UG) • Critical requirements • Process capability data • Tolerances for each part (if not known they can be estimated) • Producibility goal (DPMO)

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6.3.8 Time study

The working time used to analyze the NEWAC case is estimated below: Working time: Learning the program 4 days Importing the 3D-models 20 min Collecting data 1 week Locating points 1 day Volume variation 20 min Clearance analysis 20 min Stack-ups 20 min Interpreting the results 1 week A total time of 120 hours was used for the case study, but only 9 hours was actual simulation time. However, even without the method/tool, many of the steps that are included in the working time are already done today at Volvo Aero, e.g. collecting data, stack-ups and interpreting results. From the working time it can be deduced that time consuming work is to collect data and analyze the results, not to perform the actual analysis. Appendix O shows a quick step-by-step walkthrough to show the work process in the RD&T software.

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7. Suggestions and recommendations This chapter describes in detail what Volvo Aero should strive to achieve regarding the Geometry assurance process, but also where to implement the improvements and how the method can be used.

7.1 A future Geometry Assurance process at Volvo Aero

The variation simulation method that has been tested in this thesis work should be implemented starting in the concept phase (G2-G3) when concepts are generated and 3D-models are formed. The simulation can then be used throughout the whole process for testing and optimizing of the final result. The car industry has been working with Geometry Assurance (GA) for a long time and now it is time for Volvo Aero to follow. Figure 37 shows a suggestion of what a GA process could look like at Volvo Aero in the future, if adopting the method from the case study.

Figure 37: The Geometry assurance process that Volvo Aero should strive to achieve. Instead of only having three phases as in figure 25, a fourth phase regarding verification and reuse of information should be implemented in the Volvo Aero GA process. The verification phase, in figure 25, is changed to detailed definition & virtual verification (figure 37) to give a better representation to the Volvo Aero organization.

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7.1.1 Concept phase

Handle requirements – In the breaking down of the requirements, a top-down approach in a 3D environment should be used instead of today’s bottom-up 2D approach. The bottom-up approach can be ineffective since the designer has to loop over and over again until the requirements are met. This is time/resource consuming, but it is also a risk that tighter tolerances are set than what is necessary. The top-down method can be a faster way of handling tolerance requirements, but it can also mitigate the effects of putting too tight tolerances than necessary. Robust design – When taking robustness under consideration in a 3D environment and in an early stage of the process, it is possible to predict how good or bad a concept is regarding to its stability. This will have a great impact on the design process and will help when Volvo Aero goes towards fabrication. When working with the target system, a standard needs to be defined early in the concept phase and designers need to check with tooling manufacturing, to be able to proceed with the project. This may result in “better” relation between the designer and the tooling manufacturer compared to today when tooling manufacturing feel as they do not have any influence on the decisions. It may also minimize the fixture design cost. Variation Simulation – Variation simulation made in a 3D environment gives the designer a better understanding of how the variation (tolerance chains) affects the entire assembly. The good thing about the variation simulation is that it can be used as soon as the 3D-model is created (early in the concept phase), and then easily be updated when more information (data) is gathered. Today, no 3D variation simulations are made at Volvo Aero and that makes it difficult for the designer to create a understanding between the tolerance chains from 2D calculations to a 3D model. Tolerance allocation – Working with tolerance stack-ups in a 3D-enviroment instead of in 2D will make it easier for the designer to understand the connection between the 3D-model and stack-ups (tolerance chains). It is a quick way of changing and testing different concepts (with different tolerances) and visualizes the effects. To create a design with high quality from the beginning, education regarding working with six sigma is needed. A document where expected production variation is compiled should be created and used. From such document it could be possible to ensure the accuracy of the tolerances.Optimization of the tolerance allocation regarding cost, quality and performance needs to be taken under consideration. Access for the designers to a searchable capability data base containing Volvo Aero’s and different suppliers’ capability is needed. This will make it easier for the designers to base their decisions on data and not only on previous drawings and knowledge from the manufacturing leader.

7.1.2 Detail definition & virtual verification

Production and inspection preparation – A production and inspection preparation is made and checked in an early stage of the detailed definition & virtual verification. This is to secure and verify that the production and inspection plans are well thought through when it reaches the next stage of the process. When the plans are verified it has been checked that the production plan is the one best suited for the component and that it is possible to measure the specified measuring points with the technique that is available at the company.

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Tooling Manufacturing – Creating fixtures using target system that has been defined from the robust design in the concept phase, could decrease the extra work and time that tooling manufacture spends today on creating a new target system. This requires good communication between tooling manufacture and the designers, but also well defined standards and design practice (DP) on how this communication should be established. Tooling manufacture should have access to the same model database that is used for the NC-programming; it should include not only the machine model but also the fixture/machine table. This will minimize the variation compared to today when all the tables are measured by hand which can result in different measurements depending on who is measuring. The person creating the fixture should be present when the first product is mounted to verify and get feedback straight away. NC-programming – Working on the basis of the production plan with support from the 3D-model database that contains all the machines and tools in 3D. Each operation can be defined and what its outcome should be, and from that tools can automatically be suggested for the operation. Simulation regarding material removal can be done, as well as verification of the operation sequence (i.e. no tool intersects with the fixture or the material in an incorrect way). A robot simulation is also made to visualize what the whole process will look like. For the final adjustments and verification, the person creating the NC-program is present when it is tested in the NC-machine (direct feedback).

7.1.3 Production

Inspection database – During manufacturing, all measurements are stored in an inspection database that can be used by the designer when working with tolerances and stack-ups (compared to today when it is not used by the designer). The database should be searchable regarding Volvo Aero’s capability and includes, or is connected to, a database where the suppliers’ capability can be found. To be able to create such a database Volvo Aero needs to require the suppliers to deliver capability data and create standards and also create DP for this working process. A system/information of “how to” handle the supplier data also needs to be defined. Educated operators measure according to the inspection plan, but are also supported by standards on how and when the components should be measured. Especially standards on how components should be measured need to be improved. Today the operators are able to measure in their own “special” way. A first article inspection (FAI) is today performed on the first product (totally measured) and then later on a “FAI2” should be made (e.g. after a minimum of 25 products). This is to verify the process capabilities. This way it could be possible to reduce the number of measurements if it can be assured that the process capability is high.

Process evaluation – Continuously during the production, an analysis of the process should be done to locate any problems. Today, the problem for the designer that needs capability data is not that it does not exist, but its relevancy can be questioned. Even if the designer would start using the KPS, the manufacturing process behind the data is not defined so it is

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difficult to know if the data is relevant. The KPS only shows the final result, not the effort to get there. At the end of the manufacturing process, a last evaluation should be made to understand the process and identify lessons learned (LL). This could make the process more stable.

7.1.4 Verification

White book – Inspection data should be compared with the simulated data to see if what was predicted in the simulations actually became the output. This is to verify the input data and the model. The information created in the white book should be open, totally or partly, for all employees at Volvo Aero so it can be used in upcoming projects and for lessons learned (LL). This would close the GA process circle when more information can be reused to the next generation of projects.

According to the interviews, a lot throughout the working process is based on experience and knowledge, which is not good if the process should be stable. Therefore, more focus should be put on LL throughout the GA process. This could be done by implementing an easier way of using and updating LL information for each employee. Also, standards and DP should be improved on how, when and where saving and reuse of LL should take place. The employees need support regarding the GA process during the different phases, which can be done in different ways. Either, an employee in each project has the responsibility to check that the GA process is followed, or that CoE Design for Robustness has the support and responsibility to verify that the projects are following the GA process. Maybe both.

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7.2 Variation simulation road map

To visualize and get a better understanding of how the working process will work using variation simulation, a road map was created (figure 38).

Figure 38: Road map of the working steps of variation simulation. The roadmap is a general concept of how the stability and variation working process should be run. It is based on the analyses performed in this thesis work with the use of the software RD&T. To be able to run the simulations, a 3D analysis tool is recommended. The analysis might be

Data research - Generate mounted sequence - Identify key factors

no Redesign

Can tolerances

be changed?

yes

yes no

yes

no Is the result

satisfying?

Can locating points be changed?

Continue with stack-ups

Are tolerances known?

Are locating points

known?

yes

no

yes

Assume locating points

Assume tolerances

no

Receive the 3D-modell

Change tolerances Run clearance

analysis

Change locating points

Run variation analysis

Run stability analysis

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done without a 3D tool, but it would probably not give the effect of a better relation between the designer and the tolerance chains, which is needed. The rest of the road map is a general description and can be used without a 3D analysis program.

7.3 The benefits of implementation of the variation simulation method

Now that Volvo Aero is entering a fabrication era, improvements of designing in producibility should be prioritized to be able to handle deviations before they occur. Fabrication is belived to be a big part of the future at Volvo Aero and it is therefore of great importance to have a good GA process. This is to be able to create robust designs and handle variations in an early stage of the design process. A big change is needed and therefore it is recommended to implement a new method that can make this analysis in an early stage, with the ability to visualize in a 3D environment. The Geometry Assurance process (GA process) is believed to primarily result in the following benefits:

• A more efficient Product Development process o A better understanding of how to achieve Built In Quality. o Better tools enable some work to be performed faster. o Virtual verification enables earlier detection of problems, reducing rework loops.

• Improved ability to break down requirements o Tolerances being “balanced” (based on necessity/manufacturing process

capability), and not on earlier solutions such as previous drawings, etc. � Possibility of lower manufacturing costs

o Estimation of producibility � Fewer non-conformances, more products right-the-first-time (Yield or

First Time Through). The GA process and the simulation tool is in line with Volvo Aero own strategy of 2010. The GA also fits into Volvo Aero’s product philosophy and may create a stronger connection between technical requirements and producibility. It is recommended to purchase the stability and statistical analysis tool; it can be assumed that the tool will minimize deviations and increase the precentage of first time through. The tool may also give the designer a better understanding for the connection between variation effects, tolerance chains and stack-ups. This may also result in improved cooperation between the designers and the people in production. In the long term, it might also be possible to merge the method with welding simulation.

57

8. Discussion During my time at Volvo Aero a big interest and a need has been shown towards geometry assurance. My personal opinion is that these possibilities are something that Volvo Aero needs to prioritize to be able to grow as a company. In the past, focus lay on products with high performance, but that has changed. Today focus has been on generating high quality in faster processes and with lower costs, still maintaining high performance. To do this, more attention has been focused on creating stable products that can withstand variation. That is why this suggestion of a GA process for Volvo Aero should be implemented as a compliment to the GDP. As a first step the company should aim to introduce the variation simulation to be able to reach the final goal of a complete GA process. Of course, it will take time to implement a new way of thinking and new software, and there are other things that also have to be in place before the software can be fully used, i.a. support and a description of the working process. The description of the “future” GA process circle is a good start for a representation of what Volvo Aero could achieve, and what needs to be done to reach the goal. However, the future GA process and today’s GA process should be worked on further to become more specified. The interviews that were made to understand today’s GA process and the future GA process became rather extensive. A lot of information was gathered, and it is possible (because of the size of the half structured interview form) that some information may have been misinterpreted or lost during the analysis. This is a commonly known weakness of the interview form. A lot of data was collected from the analysis of the case. However, some input data that was used was assumed data which could have had some effect on the final result. The profile tolerance is simulated in WC, so the result may improve if a statistical profile had been used instead. Figure 39: Biggest opportunity for impact in the design stage It is hard to visualize defects in early stages, but they are easy to fix if spotted. At the end of a process, the defects may easily be spotted, but may be expensive to fix. This concludes; that if it is possible to eliminate defects in an early stage, they would be cheaper to fix compared to if they are spotted in the end (figure 39). A case study was performed to see if it is possible to predict defects in early stages of a project. The case that was used shows the possibilities of

Research Planning Design Prototype Production Customer

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Big opportunity for impact if defects could be found

58

considering the variation and its effect on a part in an early stage of the process. One locating point setup may create the best stability setup, but may not be optimal for fixturing so it is of great importance that people from production is consulted, this to find the optimal solution. From the clearance analysis it can be concluded if any of the tolerances that have been assigned are too tight and need to be opened. This is an advantage that is needed at Volvo Aero to be able to minimize recourses and deviations that can increase because of too tight tolerances. It was concluded that this working method raised questions and points out flaws in the design. The method can also be used in an early stage of the process, because of the small amount of data that was actually needed to perform the simulations and analysis. Of course more statistical data can be added quickly into the analysis when it is gathered further on in projects. The case study has also shown on the ease of working and visualization of the connection between the variation simulations and the 3D model. Even I, with no prior experience of the program could perform the analysis and simulations after a few days of practice. It is easy to make changes and visualize the result. Because of the limited RD&T version and lack of time, a small part of the programs functions and possibilities were tried out in the case study. It is possible to perform even more advanced simulations than those presented in this thesis work. If the implementation and the use of the Geometry Assurance process and the tool is done in the

right way it will be worth the money.

59

9. Future work To understand what needs to be done if Volvo Aero decides to implement the geometry assurance process and a variation visualization tool, this chapter deals with some future work. The topics treated are tools, people, processes and organisation. There are two different ways to think about the future. The first way is to think, what the goal is and then understand how to make it realistic. The other way is to look at the history (what has happened before) and predict what could be a realistic goal and how it is reached (figure 40). Figure 40: Future thinking. If Goal 2 represents AS IS (the GA process today) and Goal 1 represents COULD BE (future GA process), there are a few steps that need to be considered before the final goal is achieved. In other words, if Volvo Aero will implement a geometry assurance process and a simulation tool, some things have to be considered. These are: Tools:

• A 3D-analysis and visualization program is needed to be able to perform the different analyses. This means that an investigation to find the best 3D analysis tool for Volvo Aero needs to be conducted.

• The designer needs support regarding capability from a manufacturing leader, but also from a searchable capability database. This database needs to be created and it should include capability from Volvo Aero and its suppliers.

People:

• It needs to be decided who is going to perform the analysis. A specialist, the designer or another department? It also has to be decided if the analysis should be made in the project team or by some external department.

?

?

Past Future

Goal 2!

Goal 1!

Present

?

What is the goal and what should be done to reach it?

What has been done in the past and what can be a realistic goal?

60

Processes: • To be able to use the data in the KPS a close investigation of the manufacturing process

should be performed to define most of the variations that can occur. • The manufacturing process need to have more influence in the design decisions that are

made in the early stages. This means that it has to be more difficult for the designer to proceed with the project if the person in charge of creating the fixture is not satisfied. With help from standards and design practice (DP) it could be possible to give them more influence.

• It is needed to focus more on a working method that collects and distributes LL throughout the GA process. This method has to be easy to use and to change if necessary.

• When everything is implemented a follow up is needed to secure that the result are satisfying.

• It needs to be created a method for how to put requirements on the suppliers in terms of process data feedback and how to handle the information returned.

Organization: • Education material regarding the software and methods need to be created and taught to

the employees that will perform the analysis. • The designer/project need to have support around the GA process. This could be done

either through the CoE Design for Robustness, or that someone has the responsibility in every project to handle the GA process.

• DP and standards need to be written about HOW, WHEN and WHAT should be done regarding the simulations. A suggestion of which steps (WHAT) that should be included in the analysis can be read in chapter 7.2. The description should start in the concept phase (G2-G3) and can be used through the design process.

• Just as design work towards standardization of design solutions, manufacturing need to develop standardized manufacturing solutions (which will define manufacturing requirements of the design)

• More information (education) about the six sigma method is needed to create a better understanding of why it is important that it is considered and used.

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References Literature: A. Bender Jr. Statistical tolerancing as it relates to quality control and designer. 680490 A. Bryman (2004). Social Research Methods, second edition. OXFORD university press. ISBN 10: 019-926446-5. A. Gálvez Vega. 1D/2D Tolerance Analysis, VOLS:10045916, version 02 A. Lantz (1993). Intervjumetodik – Den professionellt genomförda intervjun. Lund: Studentlitteratur AB. ISBN 91-44-38131-X. B. Bergman and B. Klefsjö (2007). Kvalitet från behov till användning. Studentlitteratur AB. ISBN10: 914404416X B. Milivojevic. Implementering av automatiska mätprocesser på Volvo Aero Corporation. Högskolan Trollhättan/Uddevalla, Institution för teknik, matematik och datavetenskap. Number: 2004:E000. B. Ramirez and G. Runger (2006). Quantitative Techniques to Evaluate Process Stability. ©Taylor and Francis LLC. ISSN: 0898-2112. D. Ullman (2008). The mechanical design process, Forth edition. ©McGraw-Hill. ISBN 978-0-07-297574-1 K.L. Hsieh (2005). The Study of cost-tolerance model by Incorporating process capability Index into product lifecycle cost. Department of Information Management, National Taitung University. Springer-Verlag London Limited. J. Shah and G. Ameta. Navigating the Tolerance Analysis Maze. Arizona State Uneversity. Vol 4, No 5, pp 705-718. Presentation Six sigma Teamcenter (2009): Volvo Aero Six sigma för nya chefer. RD&T software manual (2009). Software evaluation and tolerances analysis. Ver 1.07. R. Söderberg, L. Lindkvist and J. Carlsson (2006). Virtual geometry assurance for effective product realization. 1st NordPLM’06, Göteborg, Sweden. Volvo Aero Corporation (2009). Concept file for NEWAC SP4 Combustor Case, RM12 demo phase. VOLS: 10081002. Volvo Aero document PHI (2009). Volvo Aero’s product philosophy.

62

Volvo Aero document DfR (2009). VOLVO AERO Design for robustness. Volvo Aero Green Belt Training material: Processduglighet stabilitet Volvo Aero Presentation: Volvo Aero processduglighet (kapabilitetspasset). VOLVO (Volvo Aero & Volvo 3P): GDP Global Development Process. Internet/intranet: GE homepage (2009): http://www.geae.com/education/engines101/ Illinois state university (2009): http://lilt.ilstu.edu/dasacke/eco148/ZTable.htm Siemens (2009): http://www.plm.automation.siemens.com/en_gb/products/tecnomatix/quality/vis_vsa.shtml Sommardesignkontoret Valdemarsvik (2004): http://www.valdemarsvik.se/upload/N%C3%A4ringliv/Design%20valdemarsvik/NC%20M%C3%B6bler_a3mapp.pdf SWEREA|IVF (2009): http://www.ivf.se/ivfTemplates/WorkAreaDescription____300.aspx Violin homepage (2009): http://violin.volvo.net/violinaero/corporate/en/projects_processes/processes/operational_management_system/Pages/processes.aspx. Volvo Aero document components (2009). http://www.dream-project.eu/volvo-aero.aspx Volvo Aero homepage (2009): www.volvoaero.com Volvo Aero server (TSV intro) (2009): File://X:\PeterT\quickstack\intro.html Wikipedia case study (2009): http://en.wikipedia.org/wiki/Case_studies. Wikipedia common cause (2009): http://en.wikipedia.org/wiki/Common-cause_and_special-cause Wikipedia simulation (2010): http://en.wikipedia.org/wiki/Simulation Wikipedia six sigma (2009): http://en.wikipedia.org/wiki/Six_Sigma#Sigma_levels Wikipedia turbofan (2009): http://en.wikipedia.org/wiki/Turbofan

63

Oral sources: Alejandro Vega Galvez Anders Gustafsson Anders Olofsson Camilla Englund Dan Gustafsson David Landgren Eva Dahl Gunnar Marke Henrik Lindström Fredrik Kullenberg Ingela Larsson Jan-Erik Andersson Johan Lööf Johan Vallhagen Jörgen Karlsson Lars Lundgren Lars-Olof Svensson Magnus Arvidsson Malin Rosenius

Markus Andersson Mats Leijon Morgan Sjögren Niklas Hultman Ola Isaksson Olof Lewin Patric Nilsson Patrik Karlsson Patrik Linusson Peter Thor Petter Andersson Pher-Ola Carlson Simon Samskog Sven-Åke Svensson Tomas Andersson Tomas Johansson Tor Wendel Torbjörn Norlander Yvonne Månsson

Appendix Appendix A Engine parts produced at Volvo Aero (3 pages) Appendix B Gantt chart (1 page) Appendix C Z-values for normal distribution (2 pages) Appendix D Unstructured interview material * (1 page) Appendix E Structured interview material * (4 pages) Appendix F General description of the different software (2 pages) Appendix G Specification of requirements for RD&T (1 page) Appendix H Survey and analysis* (1 page) Appendix I Movie sequence (1 page) Appendix J Road map of Volvo Aero’s working process * (1 page) Appendix K Plot over what and when (1 page) Appendix L Identified problems based on the interview (1 page)

material Appendix M Problems and solutions in tree diagrams (5 pages) Appendix N Total analysis of the NEWAC case (1 page) Appendix O Step-by-step walkthrough of RD&T (1 page) * Swedish material

Appendix A: Engine parts produced at Volvo Aero

A jet engine’s one purpose is to create enough thrust to zip you and your luggage across the sky. What is thrust? It’s power, the force that pushes you deep into your seat as you speed down the runway for takeoff. A turbofan (Figure A.1) is a type of aircraft gas turbine engine that provides thrust using a combination of a ducted fan and a jet exhaust nozzle. (GE homepage, 2009) In its simplest form, a jet egine has three major components, called the core: Compressor: A series of blades or airfoils, som rotating (rotors) som stationary (stators), that draws air in and conpress it. More complex engines will have many rows of blades. As the air moves through these rows, its preassure will increase by as much as 40 times and the temperature will rise dramatically. Combustion chamber: the compressed air is then pusched rearward into the combustion chamber. In the combustor, fuel injectiors mix jet fuel with the air and it is ignited. The flow and burn of the air/fuel mixture is controlled to ensure that the engine sustains a continuous flame. The expanding exhaust gases flow quickly toward the rear of the engine. Turbines: The speeding gases that exit the combustor exert force against the turbine blades (airfoils), similar to the way a gust of wind spins a windmill. The turbine is connected to the compressor by a shaft. The force – or enegry – created by the turbine spins the compressor, which pulls in more air, beginning the whole cycla again. The compressor is actually powered by the air it has already fed through.

Figure A.1: Turbofan (Wikipedia turbofan, 2009).

Figure A.2 and the information below describe the parts that are designed and/or manufactured by Volvo Aero. (Volvo Aero homepage, 2009)

Figure A.2: Components in a civil engine that is manufactured at Volvo Aero (Volvo Aero document components) 2009). Fan Case: At Volvo Aero’s US-based Volvo Aero Connecticut facility are large fan cases manufactured. This includes the world's largest casing at 3,5 meters diameter for the GE90 engine. Compressor rotor: Compressor rotors are highly stressed engine parts. This calls not only for effective and robust machining operations, but also for dedicated non-destructive testing procedures. As the rotors are made of titanium, particular care must be taken when machining them so that excessive heat generated by the cutting processes is diverted properly. Fan/compressor structure: Volvo Aero manufactures fan and compressor casings for several engine programs. Manufacturing routes range from steel fabrications to machining of large one-piece titanium castings.

Shaft: Shafts must be able to withstand severe loads and torques. The slender, hollow shafts are intricately machined. Precision manufacturing of Low Pressure Turbine Shafts for a number of turbofan engines is an important area of specialization at Volvo Aero and they have delivered more than 5,000 turbine shafts for military and commercial engine programs. The shaft

manufacturing shop is equipped with state-of-the-art lathes and grinders for external and internal machining. The shafts are manufactured at Volvo Aero Norway. Combustor structure: Volvo Aero manufactures combustor structures for several different engine programs. They are involved in re-design projects to produce new engine derivatives with higher component temperatures, or to reduce cost. LPT-Case: More than 10,000 low pressure turbine cases have been delivered for commercial and military engines. Volvo Aero dedicated turbine case flow-line employs a specially-designed pallet system for optimal manufacturing operations. Vanes: Turbine Nozzle Guide Vanes are complex airfoils made of special materials to cope with extreme conditions. Volvo Aero is the sole supplier of specific turbine vanes for engines in the CFM56 family. Volvo Aero has extensive vane production experience for military engines, commercial engines, and industrial gas turbines. The shafts are manufactured at Volvo Aero Norway. Turbine structure: Volvo Aero is a cost-effective supplier of turbine structures based on flexible manufacturing processes. They have extensive experience in fabricating turbine rear structures using a high degree of automation, such as automated welding.

Appendix B: Gantt chart

Table B.1: Gantt chart

v.24 v.25 v.26 v.27 v.28 v.29 v.30 v.31 v.32 v.33 v.34 v.35 v.36

Benchmarking V V V V

Problem definition A A A A

Interview and analysis C C C C

Specification of requirements A A A A

Case study T T T T

Validation of Case study I I I I

Movie O O O O

Report and presentation N N N N

v.37 v.38 v.39 v.40 v.41 v.42 v.43 v.44 v.45 v.46 v.47 v.48 v.49

Benchmarking

Problem definition

Interview and analysis

Specification of requirements

Case study

Validation of Case study

Movie

Report and presentation

Starting up the work Focusing on the working area

The Gantt chart (table B.1) shows when different activities starts and ends in this thesis work.

Appendix C: Z-values for normal distribution

The table C.1/C.2 shows the area to the left of a Z-value from total infinity to Z:1 Table C.1: Z-values table -3.4 - 0

Z 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 -3.4 .0003 .0003 .0003 .0003 .0003 .0003 .0003 .0003 .0003 .0002 -3.3 .0005 .0005 .0005 .0004 .0004 .0004 .0004 .0004 .0004 .0003 -3.2 .0007 .0007 .0006 .0006 .0006 .0006 .0006 .0005 .0005 .0005 -3.1 .0010 .0009 .0009 .0009 .0008 .0008 .0008 .0008 .0007 .0007 -3.0 .0013 .0013 .0013 .0012 .0012 .0011 .0011 .0011 .0010 .0010 -2.9 .0019 .0018 .0018 .0017 .0016 .0016 .0015 .0015 .0014 .0014 -2.8 .0026 .0025 .0024 .0023 .0023 .0022 .0021 .0021 .0020 .0019 -2.7 .0035 .0034 .0033 .0032 .0031 .0030 .0029 .0028 .0027 .0026 -2.6 .0047 .0045 .0044 .0043 .0041 .0040 .0039 .0038 .0037 .0036 -2.5 .0062 .0060 .0059 .0057 .0055 .0054 .0052 .0051 .0049 .0048 -2.4 .0082 .0080 .0078 .0075 .0073 .0071 .0069 .0068 .0066 .0064 -2.3 .0107 .0104 .0102 .0099 .0096 .0094 .0091 .0089 .0087 .0084 -2.2 .0139 .0136 .0132 .0129 .0125 .0122 .0119 .0116 .0113 .0110 -2.1 .0179 .0174 .0170 .0166 .0162 .0158 .0154 .0150 .0146 .0143 -2.0 .0228 .0222 .0217 .0212 .0207 .0202 .0197 .0192 .0188 .0183 -1.9 .0287 .0281 .0274 .0268 .0262 .0256 .0250 .0244 .0239 .0233 -1.8 .0359 .0351 .0344 .0336 .0329 .0322 .0314 .0307 .0301 .0294 -1.7 .0446 .0436 .0427 .0418 .0409 .0401 .0392 .0384 .0375 .0367 -1.6 .0548 .0537 .0526 .0516 .0505 .0495 .0485 .0475 .0465 .0455 -1.5 .0668 .0655 .0643 .0630 .0618 .0606 .0594 .0582 .0571 .0559 -1.4 .0808 .0793 .0778 .0764 .0749 .0735 .0721 .0708 .0694 .0681 -1.3 .0968 .0951 .0934 .0918 .0901 .0885 .0869 .0853 .0838 .0823 -1.2 .1151 .1131 .1112 .1093 .1075 .1056 .1038 .1020 .1003 .0985 -1.1 .1357 .1335 .1314 .1292 .1271 .1251 .1230 .1210 .1190 .1170 -1.0 .1587 .1562 .1539 .1515 .1492 .1469 .1446 .1423 .1401 .1379 -0.9 .1841 .1814 .1788 .1762 .1736 .1711 .1685 .1660 .1635 .1611 -0.8 .2119 .2090 .2061 .2033 .2005 .1977 .1949 .1922 .1894 .1867 -0.7 .2420 .2389 .2358 .2327 .2296 .2266 .2236 .2206 .2177 .2148 -0.6 .2743 .2709 .2676 .2643 .2611 .2578 .2546 .2514 .2483 .2451 -0.5 .3085 .3050 .3015 .2s981 .2946 .2912 .2877 .2843 .2810 .2776 -0.4 .3446 .3409 .3372 .3336 .3300 .3264 .3228 .3192 .3156 .3121 -0.3 .3821 .3783 .3745 .3707 .3669 .3632 .3594 .3557 .3520 .3483 -0.2 .4207 .4168 .4129 .4090 .4052 .4013 .3974 .3936 .3897 .3859 -0.1 .4602 .4562 .4522 .4483 .4443 .4404 .4364 .4325 .4286 .4247 0.0 .5000 .4960 .4920 .4880 .4840 .4801 .4761 .4721 .4681 .4641

1 Illinois state university (2009)

Z

C.2: Z-value table 0 – 3.7

Z 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.0 .5000 .5040 .5080 .5120 .5160 .5199 .5239 .5279 .5319 .5359 0.1 .5398 .5438 .5478 .5517 .5557 .5596 .5636 .5675 .5714 .5753 0.2 .5793 .5832 .5871 .5910 .5948 .5987 .6026 .6064 .6103 .6141 0.3 .6179 .6217 .6255 .6293 .6331 .6368 .6406 .6443 .6480 .6517 0.4 .6554 .6591 .6628 .6664 .6700 .6736 .6772 .6808 .6844 .6879 0.5 .6915 .6950 .6985 .7019 .7054 .7088 .7123 .7157 .7190 .7224 0.6 .7257 .7291 .7324 .7357 .7389 .7422 .7454 .7486 .7517 .7549 0.7 .7580 .7611 .7642 .7673 .7704 .7734 .7764 .7794 .7823 .7852 0.8 .7881 .7910 .7939 .7967 .7995 .8023 .8051 .8078 .8106 .8133 0.9 .8159 .8186 .8212 .8238 .8264 .8289 .8315 .8340 .8365 .8389 1.0 .8413 .8438 .8461 .8485 .8508 .8531 .8554 .8577 .8599 .8621 1.1 .8643 .8665 .8686 .8708 .8729 .8749 .8770 .8790 .8810 .8830 1.2 .8849 .8869 .8888 .8907 .8925 .8944 .8962 .8980 .8997 .9015 1.3 .9032 .9049 .9066 .9082 .9099 .9115 .9131 .9147 .9162 .9177 1.4 .9192 .9207 .9222 .9236 .9251 .9265 .9279 .9292 .9306 .9319 1.5 .9332 .9345 .9357 .9370 .9382 .9394 .9406 .9418 .9429 .9441 1.6 .9452 .9463 .9474 .9484 .9495 .9505 .9515 .9525 .9535 .9545 1.7 .9554 .9564 .9573 .9582 .9591 .9599 .9608 .9616 .9625 .9633 1.8 .9641 .9649 .9656 .9664 .9671 .9678 .9686 .9693 .9699 .9706 1.9 .9713 .9719 .9726 .9732 .9738 .9744 .9750 .9756 .9761 .9767 2.0 .9772 .9778 .9783 .9788 .9793 .9798 .9803 .9808 .9812 .9817 2.1 .9821 .9826 .9830 .9834 .9838 .9842 .9846 .9850 .9854 .9857 2.2 .9861 .9864 .9868 .9871 .9875 .9878 .9881 .9884 .9887 .9890 2.3 .9893 .9896 .9898 .9901 .9904 .9906 .9909 .9911 .9913 .9916 2.4 .9918 .9920 .9922 .9925 .9927 .9929 .9931 .9932 .9934 .9936 2.5 .9938 .9940 .9941 .9943 .9945 .9946 .9948 .9949 .9951 .9952 2.6 .9953 .9955 .9956 .9957 .9959 .9960 .9961 .9962 .9963 .9964 2.7 .9965 .9966 .9967 .9968 .9969 .9970 .9971 .9972 .9973 .9974 2.8 .9974 .9975 .9976 .9977 .9977 .9978 .9979 .9979 .9980 .9981 2.9 .9981 .9982 .9982 .9983 .9984 .9984 .9985 .9985 .9986 .9986 3.0 .9987 .9987 .9987 .9988 .9988 .9989 .9989 .9989 .9990 .9990 3.1 .9990 .9991 .9991 .9991 .9992 .9992 .9992 .9992 .9993 .9993 3.2 .9993 .9993 .9994 .9994 .9994 .9994 .9994 .9995 .9995 .9995 3.3 .9995 .9995 .9995 .9996 .9996 .9996 .9996 .9996 .9996 .9997 3.4 .9997 .9997 .9997 .9997 .9997 .9997 .9997 .9997 .9997 .9998 3.5 .9998 .9998 .9998 .9998 .9998 .9998 .9998 .9998 .9998 .9998 3.6 .9998 .9999 .9999 .9999 .9999 .9999 .9999 .9999 .9999 .9999 3.7 .9999 .9999 .9999 .9999 .9999 .9999 .9999 .9999 .9999 .9999

Appendix D: Unstructured interview material

Figure D.1: Question formula for the unstructured interviews

44 tx ± 33 tx ± 22 tx ± 11 tx ±

TX ±

Appendix E: Structured interview material

Koncept

1 Förstudier: 1.1 Görs det någon form av förstudie där man kollar upp hur folk har jobbat med

toleranser och variation i tidigare utvecklingsarbeten? 1.2 Kollar vad maskiner klarar av (när görs detta i processen)? 1.3 Nämn tre risker som kan finnas i tidigt skede av projektet? 1.4 Hur kan riskerna undvikas?

2. Krav:

2.1 Hur jobbar ni med toleranskrav (byggs det uppifrån och ner eller nerifrån och upp)?

2.2 Hur flödar ni ut krav till de olika delarna? 2.3 Vad är bra resp. dåligt att göra på det sättet? 2.4 Skulle det kunna göras på något annat sätt? (varför/varför inte)? 2.5 Hur verifierar ni att det fungerar? 2.6 Vet ni vad VAC klarar av att producera (för att kunna sätta en viss tolerans)? 2.7 Hur vet konstruktören att leverantören har rätt kapabilitet för att kunna sätta en viss

tolerans (ställer ni krav på mätdata från leverantören)? 2.8 Hur fungerar diskussionen mellan konstruktion och produktion när det gäller kraven

på toleranser? 2.9 Sätter man några kapabilitetskrav på leverantören? 2.10 Vilka krav har ni på tillverkningsbarhet och hur utvärderar ni konceptet mot det? 2.11 Har ni några krav på gränssnitt från kunden när det gäller tillåtna variationer?

(t.ex. olika interface mot varandra)? 2.12 Hur och när får man krav på gränssnitt från kunden? 2.13 I vilket format får ni kraven på gränssnittet från kunden? 2.14 Händer det att kunden ändrar kraven och vad händer då?

- Hur sent i processen kan kunden ändra sina krav? - Hur frekvent brukar kraven ändras? - Hur verifieras det att de nya kraven uppfylls?

- Hur påverkas andra krav av ändringen? - Hur flexibel är VAC processer när det gäller att kraven ändras?

När i processen börjar ni bryta ner kraven till komponentnivå?

3. Target system: 3.1 Hur definierar ni datums/locating points? 3.2 Är locating points/datums definierade så att andra i processen kan använda sig av

samma punkter? Hur? Varför/varför inte? 3.3 Hur jobbar ni med target system? 3.4 Varför använder ni target systemet? 3.5 Har ni ett bra target system? 3.6 Är target systemet lätt att använda? 3.7 Vilken information krävs för att jobba med target system? 3.8 Har ni något som stödjer hur ni definierar target system? 3.9 Hur verifierar ni att det blev ett bra jobb? 3.10 Finns det något som ni saknar när ni jobbar med target system? 3.11 När ni bygger upp modellen räknas det bara nominellt?

När i processen börjar ni definiera target systemen?

4. Toleransanalys/ Stack-up: 4.1 Vad har ni för stöd för att sätta toleranser (erfarenhet, verktyg, leverantörer, etc.)? 4.2 Hur jobbar ni med toleransanalyser/ stack-up:er? 4.3 Hur prioriterar ni de mått/dimensioner som ska analyseras (säkerhet, tillförlitlighet,

kundnöjdhet, etc.)? 4.4 Vilka metoder använder ni (WC,RSS, MC eller nått annat)? 4.5 Varför använder ni den (de) metoderna? 4.6 Använder ni er av six sigma som en målsättning? 4.7 Hur tar ni hänsyn till produktion när ni gör era toleransanalyser? 4.8 Beräknar ni på Cp/Cpk värden när ni gör toleranssättningar? Varför/varför inte? 4.9 När låser (fryser) ni era toleranser i processen? 4.10 Hur verifierar ni att det blev ett bra jobb med toleranssättningen?

(produktionsutfall) 4.11 Några problem med analysen? 4.12 Något som saknas när analyserna ska utföras? 4.13 Vad skulle kunna förbättras? 4.14 Om du måste välja två ställen på produkten där det skulle vara kritiskt att utföra

toleransanalyser, vart skulle det då vara? Och varför? (bra fråga om det handlar om en specifik produkt)

4.15 Gör man toleransanalyser överallt eller bara på specifika krav på produkten? - om specifika: Hur väljer man ut de ställena i så fall?

När i processen börjar ni ta hänsyn till toleranser och hur länge räknar ni nominellt?

5. Ritningar: 5.1 I vilka olika stadier kan man släppa en ritning och vad ska ingå på ritningen med

respekt på toleranser? 5.2 Hur verifierar man att det som är på ritningen är korrekt? 5.3 När man avslutar ett projekt sparas data så de sedan kan verifieras mot data som

sparas i produktionen (verifierar om allt blev som det skulle)?

Verification och pre-production

6. Fixturer: 6.1 Hur jobbar ni med fixturer? 6.2 Hur bestämmer ni hur detaljen skall fästas/placeras i fixturen (använder ni er av

locating points/datums som är genererade i 3d-modellen)? 6.3 Vilken information som behövs för att skapa en fixtur? 6.4 Vilken information saknas idag? 6.5 Skulle ni kunna utföra arbetet på ett bättre sätt (andra metoder eller verktyg)? 6.6 Använder ni toleransanalyser på fixturkonstruktionen? 6.7 Utför ni en robusthetsanalys på fixturen? 6.8 Hur verifierar ni att fixturen är bra? 6.9 Vart sparas informationen om fixturer?

När i processen börjar man ta hänsyn till fixturer och när börjar man skapa fixturer?

7. Pre-production: 7.1 Hur verifierar man att något går att produceras? 7.2 Använder ni offline programming (varför varför inte)? 7.3 Använder ni några andra simuleringar? 7.4 Vad har ni för stöd när ni planerar hur den ska produceras? 7.5 Hur verifierar ni att jobbet är bra?

När börjar man ta hänsyn till pre-production?

8. Mätning: 8.1 Hur bestämmer man vart man ska mäta på produkten? 8.2 Finns det några stöd för hur man ska mäta? 8.3 Vad behöver ni för information när det ska planera för mätning? 8.4 Vad saknas vid mätning? 8.5 Något som skulle kunna förbättras (hur)? 8.6 Används samma fixtur vid mätning som vid tillverkning?

När börjar man planera mätning?

Produktion 9. Mätningsdata:

9.1 Hur mäter man i produktionen (linjal, automatiskt)? 9.2 Vad behöver ni för information för att utföra mätningen? 9.3 Använder ni någon ”Root cause analys” för att hålla koll på vad som kan vara den

felande länken i produktionen? 9.4 Vad är bra vid mätning? 9.5 Vad saknas vid mätning? 9.6 Vad kan förbättras vid mätning? 9.7 Finns det några stöd för hur man ska mäta?

10. Spara data:

10.1 Vart sparar ni mätdata? 10.2 Sparas mätdata kontinuerligt? 10.3 Kan alla komma åt mätdata? 10.4 Finns det någon databas som håller koll på mätdata och data från leverantören? 10.5 Använder ni samma mätpunkter som man definierar i pre-produktion

(varför/varför inte)? 10.6 Har ni någon ”white book” som lagrar och verifierar att det som har producerats

stämmer överens med det som har simulerats? 10.7 Kan man få veta exakt hur en detalj har blivit tillverkad (genom att läsa sparad

data), ej hur man har bestämt att den ska tillverkas utan hur det faktisktblev tillverkad (borra två hål för bättre toleranser, etc.)?

10.8 Återmatning till projektet/konstruktören: får man veta om en tolerans var bra, dålig, ändrad så att man inte gör samma misstag igen? Hur återmatar man informationen?

11. Övrigt: 11.1 Arbetar folk gentemot GDP:n? varför/varför inte?

Appendix F: General description of the different software

Table F.1: Description of the analysis tools

Program Description Benefits TSV2 TSV lets you predict and manage key

sources of variation to ensure an assembly meets fit, form and function specification. TSV predicts the variation in an assembly due to the combined effect of tolerances, assembly sequencing, and mating operations. It also calculates the contribution of each tolerance to the variation. Simulating types are WC or MC.

• Testing of the dimensions and tolerances has been properly applied.

• Giving clear indications of build and no-build conditions by identifying the minimum and maximum conditions and contributors.

• Providing means to remove sources of assembly and part variation problems early in the product and tooling design.

• Identify opportunities to loosen tolerances, thereby enabling manufacturing cost savings.

• Reduce volume of engineering changes, improved part yields, better fitting of parts and fixtures, and better overall assemblies that fit the first time.

RD&T 3 RD&T is a software for Robust Design and Tolerance Analysis that provides a number of analyze functions for different stages of the design process. In early concept phases, when manufacturing data is limited, the focus is set on optimizing the geometrical robustness of the design. The Stability Analysis analyzes the general robustness of the design, controlled by the positioning schemes. During product and process integration, when real manufacturing data (tolerances and distributions) is available, the focus is set on optimizing the selection of

2 Volvo Aero server (TSV intro) (2009) 3 RD&T software manual (2009)

tolerances to meet design, manufacture and cost constraints. The Variation Analysis analyzes variation in critical dimensions (measures) of the design. The Contribution Analysis presents a ranked list of points and tolerances, contributing to measure variation.

VisVSA4 Tecnomatix VisVSA is a powerful dimensional analysis tool used to simulate manufacturing and assembly processes and predict the amounts and causes of variation. VisVSA can help reduce the negative impact of variation on product dimensional quality, cost and time to market. Since VisVSA's foundation lies within Teamcenter® Visualization, it also extensively leverages the digital prototyping and visualization capabilities of Vis Mockup, Tecnomatix' powerful real-time visualization and digital prototyping solution.

• Identify tolerances and assembly processes that contribute to variation and perform quick "what-if" analyses to optimize tolerances, design and the assembly process.

• Create feature-based models before or after geometry is available. Creating models prior to geometry helps drive the design before parts are made or tooling is cut.

• Leverage the most powerful variation assembly constraint engine in the world.

• Perform comprehensive statistical or simulated worst-case analyses

• Incorporate component flexibility through linking with finite element analysis results.

• Display a variety of graphical reports tied to 3D geometry

• Represent tolerances with different types of distributions.

• Extend the analysis to support user-defined equations such as gear backlash, pressure, imbalance, etc.

• Capture knowledge and reuse models; morph features to new geometry

4 Siemens (2009)

Appendix G: Specification of requirements for RD&T

This appendix is company confidential and is only available for employees at Volvo Aero.

Appendix H: Survey and analysis

This appendix is company confidential and is only available for employees at Volvo Aero.

Appendix I: Movie Sequence

The movie sequence gives a quick look on how the stability and variation envelope could be visualized in the program RD&T. The movie sequence is company confidential and is only available for employees at Volvo Aero. The movie sequence can be found in the DMS version of this thesis work.

Appendix J: Road map of Volvo Aero working process

This appendix is company confidential and is only available for employees at Volvo Aero.

Appendix K: Plot over what and when

This appendix is company confidential and is only available for employees at Volvo Aero.

Appendix L: Identified problems based on the interview material

This appendix is company confidential and is only available for employees at Volvo Aero.

How to get better standards?

Document experience and knowledge

Easy to read and to understand

Send out information to all projects of why it is so important to secure

experience and knowledge

All standards should be written in the

same way

A standard of how the standards should

be written

Standards of WHEN, HOW, WHOM and WHY this should be

done

Should be in the system

Easy access Easy to understand

Search function for particular standards

Database

Easy access

Someone that handles the updating

of experience and knowledge

Easy to use

Good overview of the working process

Described when does an activity stat and when does it end

Description of all the activities that should be done between the

gates

Reminders through the entire process

How to improve the requirement break

down?

Top-down approach Capability possibilities

Detailed demands from the costumer

Database

Supplier capabilities

Standards of how to work

Easy to understand

Standards of how it is to be written

Visualization in 3D

Easy to find Program Person doing the work

Education Certified

VAC capabilities

Production stable Demands on the supplier

Put demands on the costumer

Standards of WHOM, WHEN

and WHERE

Used by production and design

Develop the old system

Create a new sub system

Minimizing variation

Study the process closely

Standards of how to work

Standard system to transfer interface

and demands

User friendly Give access to whoever is involved

in the project

Someone in charge (owner) for each

project site

Written standards on whom is taking that ”owner” title

Appendix M: Problem and solutions in tree diagrams

A: Standards B: Requirement break down

How to implement variation analysis?

Capability possibilities

Database

Supplier capabilities

Standards of how to work

Easy to understand

Standards of how it is to be written

Visualization in 3D

Easy to find Program Person doing the work

Education Certified VAC capabilities

Production stable Demands on the supplier

Used by production and design

Develop the old system

Create a new sub system

Minimizing variation

Study the process closely

Standards of how to work

Good demands break down process

Search function

How to improve the use of target system?

Uses in production

Fixture

Involved in an early stage

Stability analysis

Measurements Program Person doing the work

Education Certified

Good demands break down process

High rated values

System and rules that force design to prioritize fixtures demands for the

target system

Need to put hard demands on design

High rated values Need to put hard demands on design

Involved in an early stage

System and rules that force design to prioritize fixtures

demands for the target system

Good communication with design

Good communication with design

Start working in an early stage

Start with the same models that Aero and

Mechanics of Materials uses.

A system that automatically updates all the models, when Design

update their models.

C: Variation simulation D: Target system

How to improve Tolerances and Stack-

ups?

Capability possibilities

Database

Supplier capabilities

Standards of how to work

Easy to understand

Standards of how it is to be written

Visualization in 3D

Easy to find Program Person doing the work

Education Certified VAC capabilities

Production stable Demands on the supplier

Used by production and design

Develop the old system Create a new sub system

Minimizing variation

Study the process closely

Standards of how to work

Search function

Usage of Cp/Cpk and six sigma

Person doing the work

Education Certified

Good demands break down process

Simulation of MC

Documents to rely on in the beginning of the

project

Connection with the capability database

Document regarding the certainty of the

sigma level

How to improve the root cause analysis?

Standards of how to work

Easy to understand

Standards of how it is to be written

Analyze Program

Easy to find Person doing the work

Education Certified

Analysis continuously registered

Monitoring the results in windows on a screen

Connection with the inspection database

Production stable

Minimizing variation

Study the production closely (what can give

variation)

Standard of how to work

E: Tolerance analysis and stack-ups F: Root Cause Analysis

How to improve reuse of inspection data?

Inspection Database

Supplier capabilities

Standards of how to work

Easy to understand

Standards of how it is to be written

Tools for data use

Easy to find Program Person doing the work

Education Certified

VAC capabilities

Production stable Demands on the supplier

Used by production and design

Develop the old system Create a new sub system

Minimizing variation

Close research about the process.

Standards of how to work

Search function

Information and education on how to use

the database

Measurement study (How are it measured

and how the data saves?)

Fixture study in production

Target system use throughout the working

process

Verification between analysis/simulation and

measurement

Document with data regarding why and how certain a cp/cpk value is

put.

How to improve saving of experience and

knowledge?

Document experience and knowledge

Document experience and knowledge

Standards of WHEN, HOW, WHOM and WHY this should be done

Should be in the system

Easy access Standards of WHEN, HOW, WHOM and WHY this should be done

Reminders through the entire process

All standards should be written in the same way

A standard of how the standards should be written

Someone that handles the updating of experience and knowledge

G: Inspection data H: Experience and knowledge

Other reports that have been written about this subject area: Koistinen, F & Torså, S. (2007) Framtagning av standardiserad metod för kunskapsåterföring. Gustafsson, M & Sundblad, J (2004) Kontinuerlig kunskapsdelning inom och mellan projekt.

How to improve communication?

No stationary phones

Standards of WHEN, HOW, WHOM and

WHY it is important with communication

Should be in the system

Easy access Easy to understand

Reminders through the entire process

All standards should be written in the same

way

A standard of how the standards should be

written

Connection between phone and calendar

on the computer

Skype phones

Develop a standard site for

communication between teams/

costumer/ suppliers

Increase visualization possibilities

I: Communication J: The project uses most experience and knowledge when developing their components. It shows that I seem to be a result of the problems A and H, than an actual problem itself. This means that if A and H should improve so would I.

Appendix N: Total analysis of the NEWAC case

This appendix is company confidential and is only available for employees at Volvo Aero.

Appendix O: Step-by-step walkthrough of RD&T

This appendix is company confidential and is only available for employees at Volvo Aero.