A Standardised Way of Applying Six Sigma to Increase the Yield of Quality of a Production Process

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A Standardised Way of Applying Six

Sigma to Increase the Yield of Quality

of a Production Process

Thesis MSc. Technology Management

Faculty of Economics and Business

University of Groningen

April 2013

Name: Zinzy Hordijk

Details: Gedempte Zuiderdiep 37a

9711 HB Groningen +31 6 1364 5368

zinzyhordijk@hotmail.com

Student number: 1685899

Supervisor University of Groningen: Dr. X. Zhu Co-assessor University of Groningen: Dr. J. Riezebos Supervisors Fokker Aerostructures B.V. Rutger van Galen

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Preface

In July 2012, I started this research in order to complete my Master Technology Management at the University of Groningen. Now, I can proudly present the findings of this investigation. For me, this investigation was challenging but a great experience.

After being an intern at Fokker Aerostructures, I was lucky to find such an interesting and challenging research question that suited so well with the MSc. TM. Robby, thanks again for investing in me and introducing me to the right people.

Next, I want to thank all the interviewees for their expertise-sharing, openness and responsiveness. This truly made it a valuable educational experience both for the research and for my personal development.

From the university I want to thank dr. Zhu for helping me with finding the right direction for this research and keeping it between boundaries of the MSc thesis. Besides this, I want to thank dr. Riezebos with the format for this research and the last points of feedback to provide me with the chance to bring this research to a higher level. I look forward to working with you the next months. Chantale, thank you for the quick responses to my questions and for helping me when I got stuck. Assisting you with your Green Belt project was besides insightful and interesting, a lot of fun!

Last, but certainly not least, I want to thank my supervisors at Fokker Aerostructures: Rutger van Galen and Jan Luijten. You gave me the opportunity to validate my conclusions with my own project. This did not only make my research more interesting and valuable, it also gave me the confidence to fully stand behind my conclusions. Rutger, thank you for your enthusiasm, for challenging me to think bigger and for bringing this research to the next level. Your input has been of great importance to me.

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Management Summary

This report is written with the intention to find out a standardised way of applying Six Sigma to increase the yield of quality at Fokker Aerostructures. Two main problems are identified at this organisation:

1. The number of defects in the assembly process of the G550 tail (empennage) is relatively high. The program has been running for around 20 years now, and still many defects occur. 2. There is no standard document or procedure on how to execute a Six Sigma DMAIC process

for reducing defect within Fokker Aerostructures. Next to this, the results in literature are contradicting and creates confusion in which way is best to increase quality.

To help Fokker Aerostructures solve these problems, this investigation attempts to answer the following research question:

How can (1) the yield of quality for assembly of the G550 empennage program be improved and (2) how can this be used to create a standard and practical DMAIC improvement process on how to set up, implement and monitor the NC reduction process for other programs? To answer this question, a series of steps are planned in the methodology. First, initial research is done, which consists of literature, interviews and own observations. Second, conclusions are drawn which are, in turn, validated to draw new and adjusted conclusions. This is an iterative process. During the different parts of this iterative process several analyses are done. Per step in the Six Sigma improvement method, both a theoretical and practical meta-analysis are performed. In literature this concept is new as no meta-analysis of tools per phase has ever been done before. It is a unique way of looking at the phases in a Six Sigma DMAIC process and an interesting contribution to the academic world. With these meta-analyses it was possible to create lists of steps to take, or tools to use, per phase. To make sure these tools are the right ones, the list of tools are validated in different ways. First, a small quality improvement project is done and interviews ware held with employees with expertise on Six Sigma methods. Here, the order and the specific use and benefit of each tool is discussed. Next, a visual validation is done, with the help of validation maps, linking tools to goals and a risk analysis is done to find out the risk that one takes when skipping steps or the use of tools. All of these inputs together, yields a list of tools that are essential per phase and list of optional tools to use per phase. These lists can be seen in section 6.7.

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6.6.1 Feedback sessions ... 57 6.6.2 Visual validation ... 58 6.6.3 Short conclusion ... 59 6.7 Results ... 60 6.7.1 Results ‘Define’ ... 60 6.7.2 Results ‘Measure’ ... 60 6.7.3 Results ‘Analyse’ ... 61 6.7.4 Results ‘Improve’ ... 61 6.7.5 Results ‘Control’ ... 61 7 Conclusion ... 62

7.1 Conclusion and recommendation ... 62

7.1.1 Conclusion ... 62 7.1.2 Recommendation ... 63 7.2 General applicability ... 63 7.3 Reflections/Limitations ... 63 7.4 Further Research ... 64 References ... 66 Appendices ... 71

Appendix I – Meta-analysis ‘Define’ matrix ... 71

Appendix II - Meta-analysis ‘Measure’ matrix ... 72

Appendix III - Meta-analysis ‘Analyse’ matrix ... 73

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Appendix V - Meta-analysis ‘Control’ matrix ... 75

Appendix VI – Combined meta-analysis ‘Define’ matrix ... 76

Appendix VII – Combined meta-analysis ‘Measure’ matrix ... 77

Appendix VIII – Combined meta-analysis ‘Analyse’ matrix ... 78

Appendix IX – Combined meta-analysis ‘Improve’ matrix ... 79

Appendix X – Combined meta-analysis ‘Control’ matrix ... 80

Appendix XI – Visual validation and FMEA; ‘Define’ ... 81

Appendix XII – Visual validation and FMEA; ‘Measure’ ... 82

Appendix XIII – Roadmap ... 83

Appendix XIV – Visual validation and FMEA; ‘Analyse’ ... 84

Appendix XV – Visual validation and FMEA; ‘Improve’ ... 85

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List of Figures

Figure 1: Assembled G550 tail ... 12

Figure 2: G550 aeroplane ... 12

Figure 3: Data gathering method ... 19

Figure 4: DMAIC method ... 22

Figure 5: Meta-analysis 'Define' theory ... 24

Figure 6: Meta-analysis 'Measure' theory ... 27

Figure 7: Meta-analysis 'Analyse' theory... 28

Figure 8: Meta-analysis 'Improve' theory... 30

Figure 9: Meta-analysis 'Control' theory ... 33

Figure 10: Combined meta-analysis 'Define' ... 36

Figure 11: Combined meta-analysis ‘Measure’ ... 38

Figure 12: Combined meta-analysis 'Analyse' ... 39

Figure 13: Combined meta-analysis 'Improve' ... 41

Figure 14: Combined meta-analysis 'Control' ... 43

Figure 15: Final validation map - 'Define' ... 48

Figure 16: Final validation map – ‘Measure’ ... 51

Figure 17: Final validation map - 'Analyse' ... 54

Figure 18: Final validation map – ‘Improve’ ... 56

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List of Tables

Table 1: Six Sigma change agents and their characteristics (Pyzdek, 2003) ... 22

Table 2: Short overview of DMAIC method... 23

Table 3: Variables and their phases ... 26

Table 4: Tools of the 'Improve’ phase - random ... 31

Table 5: Tools of the 'Improve' phase - in order ... 31

Table 6: Tools of the 'Control' phase - random ... 33

Table 7: Tools of the 'Control' phase - in order ... 34

Table 8: Combined tools of the ‘Improve’ - random ... 41

Table 9: Combined tools of the ‘Improve’ - in order ... 42

Table 10:Combined tools of the 'Control' - random ... 44

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List of Abbreviations

ANOVA Analysis Of Variance

BB Black Belt

CTQ Critical To Quality CpK Process capability index

DMAIC Define, Measure, Analyse, Improve, Control DOE Design Of Experiments

DPMO Defect Per Million Opportunities FMEA Failure Mode and Effects Analysis

GB Green Belt

GE General Electrics

KPI Key Performance Indicator MSA Measurement System Analysis

MSc Master

NC Non Conformance

PDCA Plan, Do, Check, Act PpK Process performance index

SC Scrap Conformance

SIPOC Supplier, Input, Process, Output, Customer

TM Technology Management

TQM Total Quality Management VOC Voice Of the Customer

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Chapter 1 Introduction

1.1 Research Context

Fokker is a Dutch aircraft manufacturer named after its founder, Anthony Fokker, who set up the first factory in 1912. Since then Fokker has been operating under several different names, but was taken over by Stork B.V. in 1996. From that year Fokker was renamed into Fokker Technologies with four different divisions under it, namely:

 Fokker Aerostructures

 Fokker Landing Gear

 Fokker ELMO (all electrical wiring)

 Fokker Services (service and maintenance for the flying fleet)

This research will focus on Fokker Aerostructures only, that are now specialized in producing complex components for all types of aeroplanes, from commercial aircrafts to highly advanced military programs. Also, business jets are part of the manufacturing processes at Fokker Aerostructures and this is what this research is about.

One of these business jets is the Gulfstream G550. Fokker Aerostructures produces several parts for this aeroplane, which is a technologically advanced business jet, and this investigation is about the tails, or empennages, of this particular type.

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12 Figure 1: Assembled G550 tail

Figure 2: G550 aeroplane

1.2 Problem Statements

At Fokker Aerostructures two problems arise:

1. The number of defects in the assembly process of the G550 tail is relatively high. The program has been running for around 20 years now, and still many defects occur.

During the assembly of the G550 empennage mistakes can be made. These can be very diverse, from a small mistake which has little impact on the process to bigger mistakes that have a substantial impact on the assembly line. Also the causes of the errors are diverse. However, for all of these mistakes a so-called non-conformance (NC) needs to be written. NC means that what is produced deviates from the drawing that states the specifications of that particular part or product. An NC is an error that can be fixed or repaired, but there are also mistakes that cannot be repaired. When this happens, a so-called scrap-conformance (SC) is written. Within Fokker Aerostructures the overall term of defects is NC’s, but this includes both NC’s and SC’s.

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and increase the number of man hours needed per product. Overall, it is possible to say that a reduction in the number of NC’s will directly and indirectly reduce costs for the organisation.

To reduce these costs and the number of NC’s, Fokker Aerostructures makes use of the Six Sigma method. This method can be very effective and academic literature shows many illustrations of how this can help an organisation. Six Sigma can be applied in many different sectors, from reducing the discharge time in hospitals (Allen et al., 2010) to improving the yield in manufacturing (Anthony et al., 2012) from 85% to 99,4%, with an annual reduction of US$70,000. Many gains can be seen after the implementation of the Six Sigma method, including financial savings, increase in operational profitability, increase in capacity, and reduction of stock and cycle times (Orbak, 2012). Due to the above result, Fokker Aerostructures decided to use this method in their organisation to increase the yield of the assembly process of the G550 tail.

Fokker Aerostructures is already working on implementing this way of improving into the company’s culture by training Black Belts (BBs, experienced Six Sigma project leaders) and Green Belts (GB, Six Sigma project leaders) to execute projects. A BB is usually a full-time employee that works on a big improvement project and potentially makes great improvements to the process. A GB is usually a part-time occupation that is done next to the regular jobs of employees. The aim of Fokker Technologies is to train many GBs in all sorts of departments within all four of the divisions, so that it will be embedded in their culture and continuous improvement can help move the company forward.

2. There is no standard document or procedure on how to execute a Six Sigma Define, Measure, Analyse, Improve, Control (DMAIC) process for reducing NC’s within Fokker Aerostructures.

Another problem that Fokker Aerostructures faces is that a standardised process to reduce the NC’s is not complete. The reason for this is because there is a lack of consistency in literature. When looking at the existing literature, many authors shows the DMAIC steps in a case study, but the steps taken differ very much. For example, Thomas & Barton (2006) execute a case study and in a certain phase five different tools were used. However, Rasis et al. (2002:2) also executes the phases with the help of a case study and uses five tools. Only one of the tools overlap, all others are different. These contradicting results make that there is a gap between what is presented in literature and what is the best way to executing a Six Sigma project.

Next to this, there is an internal standard on how to execute a DMAIC process, but different people, have different interpretations of the phases. The focus is on the method on how to execute the phase, but the actual practical applicability of the tools is lacking. Due to this, it would be more efficient to make a one-sided way to execute a project. In this way, no time is lost on thinking about the structure of the project. A standard document, which can be used in practice, will help all future projects leaders that try to reduce the amount of NC’s.

1.3 Research Objectives

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The first aim is to find out how to increase the yield of quality for the assembly of the G550 empennage program using the DMAIC method. The scope of this investigation reaches from the start of the assembly process up and until the packaging, or crating, so that the product is ready for transport. This scope is chosen because this is the process where the NC’s can occur which are created by Fokker Aerostructures. Other NC’s which, for example, are created by an external supplier are not within the direct scope of this investigation, as this is a variable that cannot be controlled as easily as an internal variable. However, when these NC’s are identified, feedback will be given to this party so that they can try and solve that particular NC.

The second objective of this research is to provide Fokker Aerostructures with a standard approach on how to set up, implement and monitor the reduction of NC’s, which can be used for other programs. The reason for this is that there is no literature that gives a clear-cut format on how to best execute the steps and in which order to tools should be used. An example of this inconsistency is already given in the previous section, but in chapter 2 this will be explained in more detail. The approach should be practically applicable. The aim is to provide Fokker Aerostructures with a well-considered document on how to perform an improvement project in the form of a Six Sigma DMAIC process. Here, the same scope will be used.

Overall the aim of this investigation is the following:

To (1) show how to improve the yield of quality for assembly of the G550 empennage program and (2) to provide a standard DMAIC improvement process on how to set up, implement and monitor the NC reduction process for other programs.

1.4 Research Question

With the above research objectives, the following research question can be conducted:

How can the yield of quality for assembly of the G550 empennage program be improved and how can this be used to create a standard DMAIC improvement process on how to set up, implement and monitor the NC reduction process for other programs?

A number of sub questions are created to help answer the main research questions and to reach the aim of this research.

1. What are the characteristics of the Six Sigma DMAIC process? 2. How can a quality improvement process be defined?

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1.5 Outline of thesis

This research is divided into seven chapters, each with its own research methods and goals.

Chapter 1 thru Chapter 3 are the initial parts of this investigation which is used as a starting point for this research. Chapter 1 gives an introduction to the company and discusses the aim of the investigation. Chapter 2 discusses previous theoretical research on this topic with the aim of showing how this research is relevant and a contribution to the academic world. Chapter 3 gives the methodology that is used to conduct this research.

The second big part of this investigation is the analysis part. This consists of Chapter 4, where a meta-analysis is done of the available theory and Chapter 5, where an meta-analysis of practice is done. The aim of this part is to find the tools used most commonly in a DMIAC improvement process.

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Chapter 2 Theoretical Background

Before starting this investigation, the relevance of this particular research will be determined in order to make sure that the research in new and relevant to the academic world. The Six Sigma DMAIC process is something that many academics have already done research on and, in general, three ways of doing this can be distinguished.

First, some researchers have simply described the method of Six Sigma DMAIC (Dreachlin, 2007; de Mast, 2007; Lucier, 2001; Plotkin, 1999; Sanders, 2010). These sources describe what the method entails and how it can be used.

Second, there is academic literature that compares the Six Sigma DMAIC to other methods for improving business processes. Especially the comparison between Six Sigma and Total Quality Management (TQM) is easily made (Cheng, 2009; English, 2004) as the principles behind these methods are similar. Next to that, comparisons are made between Six Sigma and Plan-Do-Check-Act (PDCA) (Lupan, 2005) and Supply Chain Operation Reference (Bolstroff, 2003), which provides a standard methodology for managing supply chains. Last, Andersson et al. (2006) highlights the similarities and differences between TQM, Six Sigma and the lean principles to give a complete overview of methods.

The third way in which research is done on Six Sigma DMAIC, is to show the method in practice in case studies. These case studies can be very diverse, which also highlights the variety of situations in which Six Sigma is applicable. To name a few, it is studied in manufacturing environments (Orbak, 2012), supply chain (Kumar et al., 2008), service environments (Wang & Chen, 2010), quality control (Anand et al., 2012) and IT (Erdmann, 2010). These case studies show real life examples on how a DMAIC process can be executed. However, others have chosen to show the DMAIC process with the help of a fictional problem and organisation. These have the sole purpose of showing how to execute a DMAIC project in a step-by-step way without looking at one particular organisation. (Johnson, 2006:1; Johnson, 2006:2; Rasis et al., 2002:1; Rasis et al., 2002:2).

All the above ways shows some research done in the area of continuous improvement with the help of Six Sigma, but the results are not consistent. No two sources use the exact same tools to execute a phase and also the numbers of tools that are used differ greatly. From three tools to seven tools when only looking at the articles that use a case study. This research aims to create order in the chaos and to show an original quality engineering solution. The new method is ready for immediate industrial application and can be seen as a Six Sigma method enhancement.

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To perform this meta-analysis, each relevant source is taken into account and used to answer the research question on how an improvement process can be defined, measured, analysed, improved and controlled. A similar approach is taken as in Zhang (2012) and Kampen et al. (2012) to help evaluate the sample of papers in a more quantitative way.

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Chapter 3 Methodology

3.1 Methodology

This research is divided into two parts each with their own aims and way of investigating. Chapter 4 is an analysis of theory and Chapter 5 is an analysis of a combination of theory and practice. Per chapter a short methodology of investigating can be seen.

To execute the analysis of theory the following steps are taken. First, a short introduction on the Six Sigma DMAIC method is given and sub questions 1 to 6 will be answered. This is done with the help of a meta-analysis. Per phase of the DMAIC method a meta-analysis is executed. Here, the academic sources and tools per phase are the rows and columns in a matrix and the number of times a tool is mentioned is counted. In these sources the tools are either explained or executed in a case study. The list of tool in the rows is build up of all articles. For example, we start with one article and see which tools are explained or executed. The next article may use the same tools, but also different ones and they were added to the list. In this way, more and more possible tools became apparent. From this list, the 80% most mentioned tools are identified as being essential to that particular phase and a list is drawn up with these essential tools. The sources used for this are only from academic literature and books. These articles and books are all less than fifteen years old to guarantee up-to-date results. There is no specific distinction made between which journal are included which are not included. All information is welcome as there are only a limited number of articles that discuss the method.

Next to the analysis of theory, an analysis of practice is executed in Chapter 5. This chapter attempts to answer sub research question 7 thru 11. Another meta-analysis is done, but this time the opinion of the employees of Fokker Aerostructures is included to come up with an adjusted list of essential tools. After this, the list of tools are validated which is done by a small project. Also, the expertise of several experienced Six Sigma project leaders is used to draw a validation map to find the tools which are essential to execute a Six Sigma project successfully. The GBs and BBs that are interviewed have all performed at least one improvement project in the last 5 years to make sure that no information is lost and input is as recent as possible. Input for this chapter is based on the findings of Chapter 4, interviews with Fokker Aerostructures employees and own experiences and observations.

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19 Figure 3: Data gathering method

If all sub research questions are answered and the conclusions are validated, the main research objective will be achieved where the aim is to (1) show how to improve the yield of quality for assembly of the G550 empennage program and (2) to provide a standard DMAIC improvement process on how to set up, implement and monitor the NC reduction process for other programs.

3.2 Data gathering method

During the execution of this research different types of data are used. Sub questions 1 thru 6 is answered with the help of literature, books, observations, own experiences, questionnaires and interviews with many experienced and certified Green and Black Belts at Fokker Aerostructures. As soon as conclusions are drawn, these are validated by a small case study and a final validation map. More information on the exact computation of these maps can be seen in Chapter 6.

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Chapter 4 Analysis of theory

4.1 Introduction

This chapter is split up into six parts, which all include a theoretical section. First, the Six Sigma and DMAIC method are explained. After this, there is a section for each phase in the DMAIC process. The questions that are answered here are the following:

 How can a quality improvement process be defined?

 How can a quality improvement process be measured?

 How can a quality improvement process be analysed?

 How can a quality improvement process be improved?

 How can a quality improvement process be controlled?

Answering these questions is done with the help of a meta-analysis. This is a method to view a large amount of data and draw general conclusions about this. This results in a list of tools per phase that can be essential when defining, measuring, analysing, improving and controlling an improvement project. Here, a tool is defined as ‘an implement used for a particular task’ (Oxford English Dictionary, 1999).

4.2 What are the main characteristics of the Six Sigma DMAIC process?

4.2.1 An introduction to Six Sigma

Six Sigma can be defined in many different ways (Eckes, 2003; Furterer & Elshennawy, 2005; Larson, 2003; Pande et al., 2000) However, all sources agree on the fact that Six Sigma is a methodology that provides businesses with the tools to improve the capability of their business processes (Yang & El-Haik, 2003).

Six Sigma oriented in the 1980s at Motorola, where a highly skilled and trained engineer, who knew statistics, began to study the variation in the various processes within the company. He saw that too much variation in any process leads to ineffectiveness (Eckes, 2003). After significant changes were successful within the company, General Electrics (GE), too, adopted the method to improve their company’s performance. By the end of 1995, GE had decided to make Six Sigma a corporate-wide initiative and less than two years after the initial application GE had generated over $320 million in cost savings (Eckes, 2003). These results are one of the reasons that businesses grew interest in the Six Sigma way of improving and why it is becoming more popular.

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improvement in profits, to employee morale and quality of product, and eventually to business excellence (Yang & El-Haik, 2003).

As shown, defects and quality are important measures when using Six Sigma, and these aspects are further elaborated on in the following paragraphs.

Quality can be described in many different ways but a fairly simple definition states that quality means that the output of the process corresponds to the set of specifications (Riezebos, 2008). Mathematically, quality can be specified as follows (Yang & El-Haik, 2003):

Where Q = Quality P = Performance E = Expectations

Garvin (1987) expands the concept of quality with eight dimensions, namely performance, features, reliability, conformance, durability, serviceability, aesthetics and perceived quality. For this investigation the conformance dimension is most applicable. Conformance is the degree to which a product’s design and operating characteristics meet established standards (Garvin, 1987).

Defects are materials and products that do not meet a company’s quality specifications (Feigenbaum, 1956) and they can be harmful in a way that the number of defects determines the quality. The more defects, the less the quality, as quality was already defined as the degree to which a product meets established standards (Garvin, 1987) and a defects means this standard is not met.

So, why use Six Sigma methodology to increase quality, while there are so many others ways to do this? The reason is that Six Sigma is relatively simple, unlike other quality improvements programs for example Total Quality Management (TQM), where over 400 tools and techniques can be applied (Pyzdek, 2003). Also, the direct effect of Six Sigma is to simply save money, while TQM aims for relativity more complex effects, for example achieving customer loyalty and improved performance (Andersson, et al. 2006).

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Table 1: Six Sigma change agents and their characteristics (Pyzdek, 2003)

Change agents

Characteristics

Champions High-level individuals who understand Six Sigma and are committed to its success

Sponsors/Process owner

Sponsors are owners of processes and systems who help initiate and coordinate Six Sigma improvement activities in their area of responsibility. The two functions can be done by the same person, but also by separate people.

Black Belt Technically oriented individuals held in high regard by their peers. They should be actively involved in organisational change and development

Green Belt Project leaders capable of forming and facilitating Six Sigma teams and managing projects from concept to completion. Usually they are assisted by a Black Belt (five to seven per Black Belt)

Master Black Belt The highest level of technical and organisational proficiency. They must be able to assist Black Belts and possess excellent communication skills.

The method by which Six Sigma is executed is the DMAIC method. This will further be explained in the next sub section (4.2.2).

4.2.2 DMAIC

Six Sigma follows a basic methodology (DMAIC) which can be seen below (Figure 4).

Figure 4: DMAIC method

DMAIC is used to improve existing business processes (Schaffer, 2007) and de Mast and Bisgaard (2007) state that the five-step method is the most prevalent Six Sigma method used.

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23 Table 2: Short overview of DMAIC method

Short overview

D

efine

Select the process that needs to be improved.

M

easure

Translate the process into quantifiable forms, collect data, and assess the current performances.

A

nalyse

Identify the root cause of defects and set goals for performance.

I

mprove

Implement and evaluate changes (solutions) to the process to remove the root cause of defects.

C

ontrol

Standardize solutions and continuously monitor improvements.

4.2.3 Short conclusion

This section attempts to answer the question what the main characteristics of the Six Sigma DMAIC are. First, Six Sigma is defined as a methodology that provides businesses with the tools to improve the capability of their businesses. Some background information on the method is given. Quality is defined as the degree in which the output of the process corresponds to the set of specifications and defects are materials and products that do not meet a company’s quality specifications. Six Sigma attempts to reduce these defects, which increases quality.

Next, Six Sigma is chosen over other improvement processes, because the execution and its aims are relatively simple compared to these other processes. The following roles can be identified within a DMAIC process; Champion, Sponsor/Process owner, Black Belt, Green Belt and Master Black Belt. In the second sub section (4.2.2) some more information is given on the DMAIC method that will be used in this investigation. The steps of the DMAIC process are reviewed shortly, but more depth is given to the five steps when answering the rest of the sub research questions

4.3 How can a quality improvement process be defined?

In this section, the second sub question is answered. Here, the first step of the DMAIC process (Define) is discussed in depth. To find out how a quality improvement process can be defined, the methodology for executing this step is considered. First, a short introduction is given on the concept. Next, a meta-analysis is done for the ‘Define’ phase where different academic literature is used to find the tools that are most mentioned and are necessary to define a quality improvement process.

4.3.1 The ‘Define’ phase

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come later in the process. The purpose of the ‘Define’ phase is to have the team and its sponsor reach agreement on the scope, goals, and financial and performance targets for the project (George, et al., 2005).

Many different tools can be used to execute the first phase in the improvement process, and the following sub section illustrates an analysisof this ‘Define’ phase.

4.3.2 Meta-analysis of the ‘Define’ phase

In this sub section a meta-analysis is done of the ‘Define’ phase. As explained in the methodology, different tools that can be used in the ‘Define’ phase were placed in a column and the sources in rows. With this matrix, the number of times a tools is used by the sources can be counted and a cumulative score is given. When placing these scores in order of highest to lowest a graph is drawn. This can be seen in the figure (Figure 5) below. Appendix I shows the entire matrix. The sources used here are form four books and eight articles and these can also be found in the matrix.

Figure 5: Meta-analysis 'Define' theory

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from the trivial few (Pyzdek, 2003), where 20% of the tools make up for 80% of the total amount of points.

4.3.3. Short conclusion

After the meta-analysis, a general conclusion is drawn in an attempt to answer the question how a quality improvement can be defined. There are 21 tools identified from numerous sources and each are given points to find out which tools are mentioned most. When applying a Pareto, the tools that should be used to complete the ‘Define’ phase are:

Problem/opportunity statement Team members and responsibilities

Process map/supplier, input, process, output, customer (SIPOC)

Schedule

Voice of the customer (VOC)/customer requirements

Critical to quality (CTQ)/define Y Goal statement

Scope

Budget/resources Business impact/benefit

4.4 How can a quality improvement process be measured?

In this section an attempt is made to answer the question on how a quality improvement process can be measured. First, a short explanation is given on what the ‘Measure’ phase is about and what its aim is. Second, a theoretical meta-analysis is done to find the vital tools to execute the ‘Measure’ phase.

4.4.1 The ‘Measure’ phase

The second phase of the DMAIC method is the ‘Measure’ phase. Measurement can be defined as the assignment of numbers to observed phenomena according to certain rules. In theory it is a simple numerical assignment to something, but in reality is problematic, as managers never know the ‘true’ value (Pyzdek, 2003). Even though measuring has its limitations, is it still an important step in the DMAIC process. This step involves trying to collect data to evaluate the current performance level of the process and provide information for the ‘Analyse’ and ‘Improve’ phases (Yang & El-Haik, 2003). The aim is to set a baseline from which a clear measurement plan can be drawn up (Brook, 2010).

4.4.2 Distinction between the ‘Measure’ phase and the ‘Analyse’ phase

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The ‘Measure’ phase start with selecting a so-called ‘Y’. As can be seen later in this research, this Y is determined by the Voice of the Customer (VOC) and the Critical to Quality (CTQ’s) that come with this. For this process, the Y is the NC rate. However, the Y may consist of many different things that make up this Y, or y1, y2, y3, etc. Once the sub-y’s are identified the factors that influences these can be found, or the so-called x’s. These are the variables that are the critical inputs (George et al., 2005). Brook (2010) states that y1 = F(x1, x2, x3, etc.), where the process output (y1) is a function of many process inputs (xi, xii, xiii, etc.). Due to the separation of the Y, the y1, y2, y3 etc, and the x1, x2, x3, etc. This can be used to separate the ‘Measure’ and the ‘Analyse’ phase. This separation can be seen below (Table 3). Also, ‘z’ is shown as a variable in the ‘Measure’ phase. This can be seen as a ‘searching direction’ and these are frequently interchanged with the x’s, which is incorrect. With the ‘searching direction’ one means the direction found in the Pareto. For example, when different areas are identified where variation exists, the area are the z’s and the Pareto can be used to select the vital z or searching area.

Table 3: Variables and their phases

Variables Phase

Y

Measure y1, y2, y3, etc.

z1, z2, z3, etc.

x1, x2, x3, etc. Analyse

4.4.3 Meta-analysis of the ‘Measure’ phase

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27 Figure 6: Meta-analysis 'Measure' theory

The figure above (Figure 6) shows the number of times a tool is mentioned cumulatviely and, again, a Pareto analysis is done to separate the vital tools.

In this part of the research an attempt is made to answer the question on how a quality improvement process can be measured. A theoretical meta-analysis is done, from which a matrix and a figure are derived. When the Pareto analysis is done, the following twelve tools should be used to complete the ‘Measure’ phase.

Data collection plan

Process cap./Current Q level/CpK, PpK Inputs, outputs, variables, CTQ’s, KPI’s Gage R&R

Sigma level (DPMO)/baseline Needed sample size/sampling

Measurement system analysis (MSA) Current process flow

Stratification factors/brainstorming Type of data (continuous, discrete) Data gathering

Operational definition

4.5 How can a quality improvement process be analysed?

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4.5.1 The ‘Analyse’ phase

As seen before, the ‘Analyse’ phase comes third in the DMAIC cycle in an improvement process. This phase involves determining the root causes of defective products (Dreachslin, 2007) and the goal is to analyse the problems and process inefficiencies (Furterer & Elsehennawy, 2005). Eckes (2003) states that the ‘Analyse’ step is seen as the most important by many in the DMAIC methodology. This is the case because many project team have preconceived notions of what to improve and after measurement they will want to jump right to the ‘Improve’ phase (Eckes, 2003). To avoid any solving of the ‘wrong’ problems it is essential that a team verifies why the problem exists. George et al. (2004) also mention the challenge of sticking to the data to reach conclusions about the root causes of problems. It is important to look for patterns in the data and target places where there is a lot of waste.

4.5.2 Meta-analysis of the ‘Analyse’ phase

Similar to the previous two phases, a meta-analysis is done for the ‘Analyse’ phase. The tools and sources are matched and cumulative scores are given to the number of times a tools is either mentioned, explained or executed. For this analysis six books and eighteen articles were used. The matrix that was filled in can be seen in Appendix III and the figure below (Figure 7) shows the Pareto analysis.

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Here, an effort is done to answer the question on how a quality improvement process can be analysed. A short description is given of what the ‘Analyse’ phase entails and in sub section 4.5.2 a meta-analysis is done. Together with the Pareto analysis the following thirteen tools should be used when analysing the improvement project.

Potential causes/X’s Pareto/prioritizing causes

Fishbone/Cause and Effect/CEDAC Process mapping/flowcharting Hypothesis testing

Value stream mapping/value analysis Brainstorming

Failure Mode and Effect Analysis (FMEA) Run chart

Design of Experiments (DEO) Scatter plot

Regression/correlation Five why’s

4.6 How can a quality improvement process be improved?

Improving an assembly process with regards to the quality, can be done in several ways. In this section an attempt is made to show how quality can be improved. To do this, academic literature and books are used to do a meta-analysis on the tools that can be used to improve the quality of the assembly process. Before this is done, a short introduction is given on what the ‘Improve’ phase entails.

4.6.1 The ‘Improve’ phase

The ‘Improve’ phase comes after the ‘Analyse’ phase and is fourth in the DMAIC process. The aim of the improvement phase is to examine the causes which appear during the analysis phase and to generate a set of solutions to improve the performance of the process (Orbak, 2012). Rasis et al. (2002:2) state that the ‘Improve’ phase involves designing experiments to understand the relationship between the Y’s and the vital few X’s … and conducting pilot tests of the action plans. Basically, it aims to make changes in a process that will eliminate defect, waste, costs, etc., that are linked to the customers’ needs identified in the ‘Define’ phase (George et al., 2004).

4.6.2 Meta-analysis of the ‘Improve’ phase

To execute an analysis of the ‘Improve’ phase, several steps are taken. First of all, tools are found in literature that can be used for this phase. Each of these tools fit into one for the four categories that are also found in literature. These categories are: ‘Generate possible solutions’, ‘Select the best solution’, ‘Assess the risks’ and ‘Pilot and implement’. This order is important when executing the phase, because it would not be logical to, for example, implement a solution without having selected the best one or having assessed its risks first.

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articles and five books. The sources used are in this matrix in Appendix IV too. The results of the analysis can be seen in the figure below (Figure 8).

Figure 8: Meta-analysis 'Improve' theory

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31 Table 4: Tools of the 'Improve’ phase - random

Brainstorming for solutions Implementation/Documentation Pilot studies/testing

Design of Experiments

Prioritisation matrix/ Solution selection matrix/Pareto Main effect plots/impact measurement

Recalculation of sigma/Process capability Assessment criteria

Paired comparison/Pair wise ranking Benchmarking

Response surface methodology FMEA/Risk analysis

Analysis of Variance (ANOVA)

To make the list more meaningful, the tools are ranked according to the steps that were identified in paragraph 4.6.2. With those steps the following table (Table 5) is generated showing the essential tools that have to be used to ‘Improve’ the yield of quality of a production process.

Table 5: Tools of the 'Improve' phase - in order

Generate possible solutions

Brainstorming for solutions Design of Experiments

Benchmarking

Response surface methodology

Select the best solutions

Prioritisation matrix/ Solution selection matrix/Pareto Assessment criteria

Paired comparison/Pair wise ranking

Assess the risks

FMEA/Risk analysis

Pilot & Implement

Implementation/Documentation

Pilot studies/testing

Main effect plots/impact measurement

Recalculation of sigma/Process capability

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4.7 How can a quality improvement process be controlled?

The sixth research question concerns the ‘Control’ phase of the Six Sigma DMAIC method, and will attempt to show how a quality improvement process can be controlled. This section is build up in the same way as the other questions, so first the ‘Control’ phase is further explained and second a meta-analysis is done to find out how to control an improvement process with inputs from academic papers and books. These source combined, show a list of tools and activities to be done to control a process and eventually a conclusion is drawn on which tools are most important in this step of the process.

4.7.1 The ‘Control’ phase

The ‘Control’ phase aims to ensure that the solutions that have been implemented become embedded into the process, so that the improvement will be sustained after the project has been closed (Brook, 2010). This phase comes with many difficulties, including a lack of resources, lack of coordination between functions and impatience to get results (Gijo & Rao, 2005) while it is so important to finish this phase well, to make the changes and improvements last. To achieve the aim of closing the project in a good manner, several things can help, which may include documenting the new procedures and training everyone (George et al., 2004).

4.7.2 Meta-analysis of the ‘Control’ phase

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33 Figure 9: Meta-analysis 'Control' theory

4.7.3. Short conclusion

The ‘Control’ phase is the last phase in the DMAIC process and is important to make the improvements last. Many tools can be used to do so and this sub section tries to separate the essential tools from the list of all tools. With the help of 23 sources, a meta-analysis and a Pareto analysis, the nine vital tools are found and can be seen in random order in the table below (Table 6). Table 6: Tools of the 'Control' phase - random

Process control plans/chart Documentation

Monitor implementation Standardised processes Training employees/Discipline Audit results/Financial benefits

Communicate/transfer to process owners SPC

Mistake proofing

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34 Table 7: Tools of the 'Control' phase - in order

Implement ongoing measurements

Process control plans/chart

SPC

Standardise the solution

Documentation

Monitor implementation

Standardised processes

Training employees/Discipline

Mistake proofing

Quantify the improvement

Audit results/Financial benefits

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Chapter 5 Analysis of practice

5.1 Introduction

In this section, the findings of Chapter 4 are combined with practice to find questions to sub research question 7 thru 11. Per phase tools are identified that are seen as essential in academic literature. However, as this research is conducted for Fokker Aerostructures, their expertise is also used to come to a final method on how to define, measure, analyse, improve and control the G550 quality improvement process.

To do so, each section answers a sub research question through another meta-analysis. However, this time not only academic literature and books are taken into account. Also, projects and opinions of Green Belts and Black Belts are taken into account to fill in a similar matrix. The data that is gathered within Fokker Aerostructures is approximately 90% of all available data and one can say that this percentage is high enough to gain reliable results.

Once the matrix is filled in, the tools can be put into order where the one mentioned most cumulatively is on top of the list. A Pareto analysis is done and this yields a new and adjusted list of tools which are considered essential. With this combined list of theory and practice, a validation is done in Chapter 6, so that the list can be adjusted yet again. All to come to a standardised way of applying Six Sigma to increase the yield of quality of the G550 production process.

5.2 How can the G550 quality improvement process be defined?

5.2.1 Combined meta-analysis of ‘Define’ phase

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36 Figure 10: Combined meta-analysis 'Define'

After the analysis of the tools that can be used in the ‘Define’ phase, some interesting conclusions are drawn.

There are 26 tools identified from numerous sources and each are given points to find out which tools are mentioned in these sources. A general overview of all sources is given, together with a graph showing the tools most used in theory and at Fokker Aerostructures. Form this, it is clear that what Fokker Aerostructures is doing in both Green or Black Belt’s projects is highly comparable to theory. Especially the vital 80% shows that most bars are almost equally blue as they are green. This means that both sources find the tools equally important. There are a few exceptions, though. Drawing up a schedule, or detailed planning of the Green Belt project, is one of the things that are only mentioned in theory and or not done in practice. On the other hand, the use of a business case is done more in practice than is mentioned in literature.

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When applying a Pareto, the following ten tools should be included in the ‘Define’ phase after combing theory and practice.

Team members and responsibilities Problem/opportunity statement Process map SIPOC

CTQ/define Y Scope VOC/customer requirements Business case Goal statement Key stakeholders Schedule

With this list, one can state that the use of these tools is how the G550 quality improvement process can be defined. In Chapter 6, the above list of tools is validated.

5.3 How can the G550 quality improvement process be measured?

5.3.1 Combined meta-analysis of ‘Measure’ phase

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38 Figure 11: Combined meta-analysis ‘Measure’

In this sub section the results are shown of the analysis that was done to find out which tools can be useful in the ‘Measure’ phase. Through literature and personal interviews with employees of Fokker Aerostructures, the graph above is constructed (Figure 11).

24 tools where found in 24 sources to find out which source mentioned which tool. Per tool the number of times it was mentioned is counted and a separation is made between theory and practice. This is interesting as Fokker Aerostructures finds other tools important than are mentioned in literature and the other way around. For example, literature finds ‘inputs, outputs, CTQ’s, ‘Key performance indicators (KPI’s)’, ‘Process capabilities/current Q level/ Process capability index (CpK)/Process performance index (PpK)’ and ‘Gage R&R’ important, while Fokker Aerostructures mentions this very little or not at all. On the other hand ‘Measurement instruments’ and ‘identifying the source or location of data’ is mentioned by employees of Fokker Aerostructures relatively many times.

For now, when looking at the Pareto, the following twelve tools should be used to measure the G550 quality improvement process and to answer the sub research question:

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Here the list of the tools included can be seen and these should be used to complete the ‘Measure’ phase.

Data collection plan

Inputs, outputs, variables, CTQ’s, KPI’s

Process capabilities, current quality level, CpK, PpK MSA

Data gathering Gage R&R

Stratification factors, brainstorming Sigma level (DPMO), baseline Current process flow

Needed sample size (sampling) Pareto

Operational definition

To make sure this list included all essential tools to ‘Measure’ the G550 quality improvement process, Chapter 6 attempts to validate these tools for such an improvement project.

5.4 How can the G550 quality improvement process be analysed?

5.4.1 Combined meta-analysis of ‘Analyse’ phase

A meta-analysis is done for the ‘Analyse’ phase which combines theory and practice. A matrix is filled in with all sources and possible tools to execute this phase in the DMAIC project. The matrix can be seen in Appendix VIII and the graph is shown below (Figure 12). To come to this graph, six books, eighteen articles, three GB and nine BB projects were used.

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In the above paragraphs the results are shown of the analysis that is made to find out how to perform the ‘Analyse’ phase in the Six Sigma DMAIC improvement process. Again, it is not only interesting to see the overall picture of the tools that can be used in the third phase of a DMAIC project, but it is also helpful to find out what is important in literature (books and articles) and to the project leaders of Green and Black Belts projects in practice at Fokker Aerostructures. It is particularly interesting to see that the top four tools mentioned have almost the same proportion of the number of times mentioned in theory and at Fokker Aerostructures. This means that these are extremely important in the ‘Analyse’ phase. Other tools, especially the ones mentioned least, are only mentioned in literature once or twice and not used in practice at all. The middle part of the tools (between 4 and 17 times mentioned) has a lot of fluctuations in the ratio of theory and practice. Overall, the following tools should be used to analyse the G550 quality improvement process, when looking at the Pareto analysis and this answers the sub question

‘How can the G550 quality improvement process be analysed?’ Pareto/prioritizing causes

Potential causes/X’s

Fishbone/Cause and Effect/CEDAC Process mapping/Flowcharting Brainstorming

Hypothesis testing Scatter plots

Regression/correlation

Value stream mapping/value analysis Run chart

ANOVA

Gage R&R per X Baseline per X Seven wastes Improvement plan Five laws of lean

This extended list of the 80% vital tools and the order in which they should be executed will be tested in Chapter 6.

5.5 How can the G550 quality improvement process be improved?

5.5.1 Combined meta-analysis of ‘Improve’ phase

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41 Figure 13: Combined meta-analysis 'Improve'

After the analysis is done in paragraph 5.5.1. a short conclusion is drawn. An attempt is made to show which tools are important when executing the ‘Improve’ phase of the DMAIC improvement project. To do so, four steps within the ‘Improve’ phase are found and within each step, tools are found. In the table below (Table 8) the four colours represent the four steps. The steps, or colours, are in a random order, due to the fact that only the number of times a tools is mentioned, is taken into account.

Table 8: Combined tools of the ‘Improve’ - random Brainstorming for solutions

Pilot studies/testing

Implementation/Documentation Main effect plots/impact measurement

Prioritisation matrix/ Solution selection matrix/Pareto Recalculation of sigma/Process capability

Design of Experiments

Impact & Effort matrix/Pick chart 5S

Assessment criteria Visual management

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To make the list of tools more logical and practical, these tools are put into order of the steps, which results in the following order (Table 9). The steps are included here too.

Table 9: Combined tools of the ‘Improve’ - in order

Generate possible solutions

Brainstorming for solutions Design of Experiments

Benchmarking

Select the best solution

Prioritisation matrix/ Solution selection matrix/Pareto Impact & Effort matrix/Pick chart

Assessment criteria

Assess the risks

Fishbone/Cause and Effect/CEDAC

Pilot & Implement

Pilot studies/Testing

Implementation/Documentation

Main effect plots/Impact measurement

Recalculation of sigma/Process capability

5S

Visual management

When looking at the list above, together with the tools that are part of the top thirteen, they have different proportions of importance in literature and by the employees of Fokker Aerostructures. For example, the Design for Experiments are mentioned relatively many times in academic papers, while this tools is only mentioned twice by employees. On the other hand, tools listed in place 8 thru 13, are mentioned relatively more in practice than in literature. An example, is the Impact & Effort matrix, which is only mentioned twice in literature, while the Fokker Aerostructures employees mention it in nine projects.

Still, these are the tools that are mentioned most and should be used when improving a DMAIC process. This answers the sub research question:

‘How can the G550 quality improvement process be improved?’

5.6 How can the G550 quality improvement process be controlled?

5.6.1 Combined meta-analysis of ‘Control’ phase

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43 Figure 14: Combined meta-analysis 'Control'

In this sub section, a conclusion is drawn based on the analysis done. First, a total of 21 tools are found within four steps identified earlier. Literature and practice are used to find which tools are used more frequently and this generates a figure (Figure 14). Here, a distinction is made between the Fokker Aerostructures and theory and this shows some interesting things. In general, more tools are used in practice, than that are mentioned in theory. Some tools are mentioned in theory relatively often, while in practice Fokker Aerostructures uses them very little, for example ‘monitoring the implementation’. The other way around is also true, where in practice the tool is used a lot compared to literature. Some examples are the ‘5S’,’ visual management’ and the ‘KPI tree’.

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Table 10:Combined tools of the 'Control' - random

Process control plans/chart Documentation

Communicate/transfer to process owners Monitor implementation

Celebrate the success Lessons learned 5S

Visual management

Training employees/Discipline KPI trees

New project (continuous improvement)

Again, when putting them in a logical order to make it more practical, these tools should be used when controlling the G550 improvement process (Table 11) and they answer the sub research question of section 5.6.

‘How can the G550 quality improvement process be controlled?’

Table 11: Combined tools of the 'Control' - in order

Implement on-going measurement

Process control plans/chart KPI trees

Standardise the solution

Documentation

Monitor implementation

5S

Visual management

Training employees/Discipline

Quantify the improvement

Close the project

Communicate/transfer to process owners

Celebrate the success

Lessons learned

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Chapter 6 Validation

6.1 Introduction

This section attempts to validate the conclusions drawn so far in this research. This will not only strengthen and elaborate the theoretical base of this project, but also extent the value of this research and to make it practically applicable. To this so, only the 80% vital tools and activities found in the conclusion of the phases of Chapter 5 will be used. The phase will be validated in a number of ways. The steps are explained below.

1. Validation project

To validate the tools that are found in the previous parts of this research, a small quality improvement project is done at Fokker Aerostructures. All steps are executed in the order in which they are given. With the execution of this project, meetings are planned with three different people at the end of each phase. These are a GB that is working on a quality improvement project that is related to the validation project, a BB that had done several projects in this area already and the Director of Operations, who is also a BB. The reason that these three people are chosen is because it is assumed that they give the validation three different points of view. The GB is relatively inexperienced and now working on the first project. The BB is a fulltime function within Fokker Aerostructures and he goes from project to project within the entire organisation. The third person, is now in a new function within the company, but he used to be a BB and has completed at least two large and successful projects. The diversity of these people, one beginner, one full time BB and one experienced BB that no longer works on projects, provides diverse feedback on the validation project. The entire project can be seen in a separate document (“Validation project”) but the feedback from the three ‘reviewers’ can be seen in this document.

2. Initial validation map

Another way of validation the tools that were found per phase, is to make use of visualization. Per phase, three or four main goals are identified. The tools are placed below this and links are drawn that show that a tool should be used to complete a certain goal. The tools that have no link with other tools or to the goals are considered non-essential tools to complete a phase. To drawn the links between the goals and the tools, the expertise is used of an experienced BB that had already completed three large projects. The, so-called, initial validation maps can also be seen in the Appendices of this document.

3. Failure Mode and Effect Analysis (FMEA)

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by a group consisting of three experienced BBs. In that way an overall score per tool is calculated by multiplying the numbers and, the higher the score the more essential the tool is to the phase. To complete the entire table, a session is planned with three experienced BBs at Fokker Aerostructures. The reason that these BBs were chosen is because they are full time BBs at Fokker Aerostructures and they work with the DMAIC method on a daily basis. They have all completed at least two large BB projects. A number of three people is asked to make sure that a majority would arise to decide on a score and to get more opinions into one score, which makes the score more reliable. The FMEAs can be seen in the Appendices of this document.

4. Final Validation map

With all the above information, of all three steps and of Chapter 5 and 6, final validation maps can be drawn. These maps look similar to the initial validation maps, but more colours are included to show which tools are essential, optional or are undecided. This can happen when, for example, the initial validation map links a tool to a goals, while during the FMEA the tool gets a very low score. The final validation maps can be seen in the next sections.

6.2 Validation of the ‘Define’ phase

6.2.1 Feedback sessions

First, the validation project is executed with all the tools in the given order. Now, the steps are assessed by one GB project leader, one BB project leader and the Director of Operations at Fokker Aerostructures, who is also an experienced BB. During one-on-one interviews, the method is shown and feedback is given, mainly on the structure of the tools in the ‘Define’ phase.

Feedback from Green Belt project leader

The GB project leader generally finds the order in which the tools are executed well. However, she recommends moving the business case up so it is executed earlier in the phase. At the moment it comes seventh in the list, while she states that financial benefits are important to Fokker Aerostructures, so it might be better to execute the business case earlier on in the process of defining a project. This will also help to convince possible sponsors and/or champions of the project. Apart from this input, the GB project leader would give a ‘pass’ to go on with the next phase in the DMAIC method.

Feedback from Black Belt project leader

A Standardised Way of Applying Six Sigma to Increase the Yield of Quality of a Production Process