Advice Six Sigma NC reduction projects

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Advice

Six Sigma NC reduction projects

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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List of Figures

Figure 1: DMAIC method ... 8

Figure 2: Stakeholder analysis, example ... 12

Figure 3: Alternative stakeholder analysis ... 13

Figure 4: SIPOC, example... 14

Figure 5: Input and output variable example ... 17

Figure 6: Current process flow example... 18

Figure 7: Combination of Inputs and Outputs variables AND current process flow ... 18

Figure 8: NC rate per month ... 19

Figure 9: Actual NC rate per month ... 19

Figure 10: Stratification factors, example ... 20

Figure 11: Pareto, example ... 21

Figure 12: Process map, example ... 25

Figure 13: Fishbone diagram, example ... 25

Figure 14: Pareto, example ... 27

Figure 15: Probability plot, example ... 28

Figure 16: Box plot, example 1 ... 28

Figure 17: Box plot, example 2 ... 29

Figure 18: Run chart, example... 31

Figure 19: I-MR chart, example 1 ... 31

Figure 20: I-MR chart, example 2 ... 32

Figure 21: VSM, example ... 33

Figure 22: Scatterplot, example ... 34

Figure 23: Regression, example ... 35

Figure 24: Fishbone diagram, example ... 44

Figure 25: Control chart, example ... 46

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List of Tables

Table 1: Six Sigma change agents and their characteristics (Pyzdek, 2003) ... 8

Table 2: Short overview of DMAIC method... 9

Table 3: Team members ... 11

Table 4: Scope example ... 12

Table 5: Schedule, example ... 13

Table 6: FMEA, example ... 26

Table 7: Seven wastes (Brook, 2010) ... 30

Table 8: Prioritisation matrix, example ... 41

Table 9: Pick chart, example ... 42

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List of Abbreviation

ANOVA Analysis of variance

BB Black Belt

BNVA Business non-value added CAP Change Acceleration process

CEDAC Cause and effect diagram with added cards CTQ Critical to quality

CpK Process capability index

DMAIC Define, Measure, Analyse, Improve, Control DPMO Defect per million opportunities

EAV Own NC’s (translated from Dutch abbreviation) FMEA Failure mode and effects analysis

Gage R&R Gage repeatability & reproducibility

GB Green Belt

GE General Electrics

HGV Hoogeveen

I-MR Individual moving range KPI Key performance indicator LCL Lower control limit

MSA Measurement system analysis

MR Moving range

NC Non conformance

NVA Non-value added

PPD Papendrecht

PpK Process performance index

RACI Responsible, accountable, consulted, informed

SC Scrap conformance

SIPOC Supplier, Input, Process, Output, Customer

SMART Specific, Measurable, Achievable, Relevant, Time bound TAV Suppliers NC’s (translated from Dutch abbreviation) TPD Technical process description (instructions)

TQM Total quality management UCL Upper control limit

VA Value added

VF Vertical fin

VOC Voice of the customer

VSM Value stream map

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Chapter 1 Introduction

This document is part of a Master thesis where an investigation is done on how to best execute a Six Sigma project to increase the yield of quality for an assembly process. Below, an introduction to Six Sigma is given and a guide on how to use this document.

1.1 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.

Now, what is it exactly? A company’s performance can be measured by the Sigma level of their business processes, where Sigma, , is a letter in the Greek alphabet used to measure variability in any process (Pyzdek, 2003). It refers to six standard deviations and means a process performance of no more than 3.4 defects per million opportunities (DPMO) (English, 2004). The purpose of this is to increase performance and decrease performance variation, which will lead to defect reduction and improvement in profits, to employee morale and quality of product, and eventually to business excellence (Yang & El-Haik, 2003).

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.

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

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

The method by which Six Sigma is executed is the DMAIC method and can be seen below (Figure 1).

Figure 1: 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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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.

1.2 Introduction to this document

Now that more insight is given on Six Sigma and DMAIC, this document can help a GB project leader with the execution of an NC-reduction project at Fokker Aerostructures.

After research, tools have been identified in a particular order so that NC’s will be reduced at the end of a project. Per phase a list is presented of essential tools and optional tools and definitions, a way of using the tools and examples are shown. At the end of each chapter some practical tips are given that are specific for Fokker Aerostructures and these come from books, interviews with experienced GBs and BBs and own experiences.

When writing this advice many sources were used. However, two books were extremely helpful when writing this advice and the first recommendation is to use these books during a project as they give a clear and extended overview on how to execute an improvement project.

The books are:

 Brook, Q. 2010. Lean Six Sigma and Minitab: The Complete Toolbox Guide of all Lean Six

Sigma Practitioners. Hampshire: OPEX Resources Ltd.

 George, M.L., Rowlands, D., Price, M. & Maxey, J. 2005. The Lean Six Sigma Pocket Toolbook. New York: McGraw-Hill.

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Chapter 2 Define

2.1 The Define phase

The ‘Define’ phase starts as soon as a problem is identified in an organisation. This phase is the first in the DMAIC method and helps to clarify the understanding of why it is a problem, before investing time and money in commencing a project (Brook, 2010). Beware, that Six Sigma starts with problems only, and the ‘Define’ phase is one which only focuses on the problem; causes and solutions will 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). Below a list of essential and optional tools can be seen.

Essential tools

Problem/opportunity statement Business case

Team members and responsibilities VOC/customer requirements CTQ/define Y Scope Key stakeholders Schedule

Optional tools

Process map SIPOC Goal statement

2.2 Essential tools

2.2.1 Problem/opportunity statement

The problem/opportunity statement should articulate what the problem is. It should not presume any solutions. If possible, try to express the problem in numbers. When was it seen, what is the problem, what is de magnitude and the consequence of this problem. Making it SMART (Specific, Measurable, Achievable, Relevant, Time bound) can help.

2.2.2 Business case

This is a brief summary of what the business issue is. It should be in non-technical terms (understandable by finance) and should clearly articulate the risk and opportunity that is being addressed. Preferably, the risk or opportunity is also expressed in €. Expressing the potential savings is important to create support from the champion and/or sponsor.

2.2.3 Team members and responsibilities

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the beginning. Some people may not be part of the core team, but do know about the project and can be asked for helped when needed. An example of a table can be seen below (Table 3).

Table 3: Team members

Name Role Expertise/knowledge Days/hours per week

… … … …

... ... ... ...

2.2.4 VOC/customer requirements

VOC stands for Voice of the Customer. The purpose of finding out the VOC or customer requirements is to find out what the customers really care about. There are different ways of collecting the VOC, including interviews, focus groups and surveys (George et al., 2005). However, these tools mentioned above can be time consuming and unnecessary. When working on an NC reduction project, most of the times, a key stakeholder will have been given a target in numbers to reduce the NC rate. If this is the case, the VOC is quite simple and can be kept quite short. If no NC rate target is given, it is possible to use the mentioned tactics to find the VOC.

When finding the VOC, make clear that both the project leader and the customer know when this target is met. If a target of a particular NC is set, make clear when the improvements are made, and show the average NC rate from that particular point. If it is done correctly, it is clear that the rate before the improvements is higher, and the rate shows less variance and has a lower average after the improvements. So, make sure that the improvements can be seen easily and the new NC rate balances around the customers given NC rate.

2.2.5 CTQ/define Y

The CTQ is an abbreviation of Critical to Quality. This is a way of measuring the VOC and a unit can be given to this. Within Fokker Aerostructures the number of NC’s is expressed in the same unit

throughout the entire organisation. This will, therefore, be an easy step in de ‘Define’ phase, where Y=(#NC + #SC)/1000 production hours/month.

2.2.6 Scope

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Table 4: Scope example

In scope Out of scope

…

Only include those aspects that will never become part of the scope.

2.2.7 Key stakeholders

Identifying the stakeholders of a project can help when considering those people involved or affected by the project. There are many ways to execute a stakeholder analysis, but a relatively simple but effective example is shown below (Figure 2). Here, different stakeholder have been given a circle, where the bigger circle represents bigger involvement or are affected more. In this way, it is possible to see in one glance who should be taken into consideration.

Figure 2: Stakeholder analysis, example

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Figure 3: Alternative stakeholder analysis

2.2.8 Schedule

A schedule can help plan the project and prevent a project from lasting too long. It will give a project leader a reason to prioritize his/her project and setting a deadline may help to stick to it. To plan the project a table can be used, but other ways, maybe showing a ‘time line’ for the project can be used too. An example is given below (Table 5). Here this deadline can represent a tollgate meeting with the champion and/or sponsor.

Table 5: Schedule, example

Phase Deadline Total time (weeks/months)

Define …/…/…. …

Measure …/…/…. …

Analyse …/…/…. …

Improve …/…/…. …

Control …/…/…. …

This tollgate meeting is a mile stone in the project and here, the steering committee will be shown the progress of the project so far. Also, this steering committee can use this opportunity to ask questions, help solve possible problems and give a ‘go’ to move on to the next phase of the project.

2.3 Optional tools

2.3.1 Process map SIPOC

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though this tools is placed in under optional tools, it can be extremely useful to really identify the process and the customer.

Figure 4: SIPOC, example

2.3.2 Goal statement

The goal statement can be used when the VOC is not specific enough yet. In general, a project starts with a vague problem, which becomes more and more specific as the ‘Define’ phase progresses. So, it starts with a general problem statement, the VOC is found out and then the CTQ/Y can be defined. For an NC reduction project, this will be fairly straight forward as a ‘customer’ will have a certain reduction in mind. However, if the goal is not a repetition of the VOC, it may be helpful to still use this tool, otherwise it may be double work.

2.4 Practical tips for the Define phase

The ‘Define’ phase is explained above, but more tips can be given to future project leaders, that are specifically interesting for Fokker Aerostructures. The information below comes from interviews with several Green and Black Belt project leaders at Fokker Aerostructures and from own experiences and observations.

2.4.1 Available capacity and team abilities

When forming a team, a project leader must keep some things in mind. First of all, be sure that there is enough capacity to execute the project. It will be a waste if a project failed due to a lack of capacity. Do not ask too much of the team members and make sure that their manager supports the project too and is willing to give the project priority.

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Third, it might be a possibility to involve the team from the beginning of the project. Normally, a team is formed in the ‘Define’ phase, but is only involved from the ‘Measure’ phase when their expertise is needed. However, it is also possible to include the team sooner and get their help when setting up the business case and when finding the high-over problem. This will help the project leader and it will also increase involvement for the team members, right from the beginning of the project.

Last, when forming a team it is important that all team member know what is expected from them and that the project leader is aware of the level of participation of a team member. A tool that can be used here is the RACI-model. This stands for Responsible, Accountable, Consulted, Informed (Frauman, 2012) and are all roles that can be assigned to a team member to clearly have a distinction between the team members.

2.4.2 Black Belt mentor; Key stakeholder or not?

Normally, every Green Belt is supported by a Black Belt. This Black Belt can help the Green Belt with the execution of each phase and has knowledge of what a Six Sigma project entails. He or she can help keep the structure of the project and can stress the importance of following each step properly. However, during interviews with GB project leaders, opinions on the role of this BB were divided. Some stated that the BB should not be the same person as the champion and/or sponsor. If this happens, the BB will put the results of the project above the structure and execution of the phases. He/she would want to see results as soon as possible and this could jeopardize the method. On the other hand, GB’s disagreed with this and stated that they wanted the BB to be a key stakeholder too. Their argument was that, if an influential person is the mentor, this creates a more supportive and influential basis which can help the project too. Having an influential person or leader as a BB mentor, can ‘open doors’ that would have stayed closed if ‘any’ BB was the mentor.

Both sides have a point and it is up to the project leader to consider the options and make an appropriate decision depending on that particular situation.

2.4.3 Other pitfalls

Last but not least, some other pitfalls have been identified and will be mentioned here shortly. First, beware that the problem you are trying to solve is the actual problem. Solving something else than the problem, will cost a lot of time, resources and will cause motivational problems. So, be sure to identify the VOC and the CTQ’s correctly. Taking a little bit of extra time for this may help you in a later stage of the project.

Second, make sure that the project is not too big. Especially when you are an inexperienced GB project leader, it is more desirable to have a project that is too small than too big. It is also possible, and maybe better, to extend the project when too small instead of drowning when the scope of the project is too big.

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be planned, so that the project will not be overlooked due to a possible lack of capacity or other priorities.

2.5 Practical tips for all the steps in the DMAIC method

Next to the practical tips that are important in the ‘Define’ phase only, there are some other tips that are helpful for the entire DMAIC method. They are written here, because now already some things are known about a DMAIC process and they will be better understood than when written in the introduction.

2.5.1 The ‘Soft side’ of Six Sigma

Six Sigma has a so-called ‘soft side’. As clearly stated in this research, DMAIC is very data-oriented and the ‘human aspect or factor’ is seen as not as important. However, the human aspect cannot be left out from the project as people can have a great influence on the project, both in a positive and a negative way. To deal with this ’soft side’ of Six Sigma a certain model is used at Fokker Aerostructures, the so called Change Acceleration Process model (CAP). Here, five steps are mentioned to go from the current state to the desired state and the model can be seen in Appendix I. Even though this research does not include a detailed description of the model, it is good to keep this model in mind when executing a DMAIC project. (This model is also explained in detail in the Green Belt course that the Stork Academy offers).

2.5.2 Use of an assistant project leader

During a DMAIC improvement process it is possible to make use of an assistant project leader. The GB that made use of this function is quite satisfied with this. It helps to stimulate the project leader to continue with the project, when motivation is less or when the project has become of lower priority for that person. It can also help when the project leader has questions, or needs help when, for example, leading meetings. Even though it can be a good motivation, it is not seen as a necessary function in the team and it could be seen as a good addition to the team. It is even possible to combine it with another function, where one team member is both an expert in their area of knowledge and a project leader assistant.

2.5.3 Execute each step

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Chapter 3 Measure

3.1 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). The tools that can be used to execute this phase can be seen below and will be described in section 3.2 and 3.3.

Essential tools

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

Current process flow

Process capabilities, current quality level, CpK, PpK Measurement system analysis (MSA)

Stratification factors, brainstorming Data collection plan

Pareto

Optional tools

Needed sample size (sampling) Sigma level (DPMO), baseline Gage R&R

Data gathering

3.2 Essential tools

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

The inputs of the process are the variables that influence the output. Below an example can be seen (Figure 5) on how to connect the input to the output. The aspects in the blue boxes are the variables and these are things that are CTQ’s. With the CTQ’s certain Key performance indicators (KPIs) can be identified that are used to measure the output. To fill in this example, brainstorming can help to find factors that can predict the output and can help find things to measure in the data collection plan. More information on brainstorming can be found in sub section 3.2.6.

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3.2.2 Operational definition

An operational definition is developed to clearly understand a description for a KPI. When looking at the KPI’s found in the figure above (Figure 5) operational definitions can clarify these. Also, when measuring, it can help to set operational definitions, so that each person is measuring the same kind of thing. For example, when looking at the process of drilling, it is possible that a drill is not sharp. However, it needs to be decided on what is sharp and what is not. Another example, when looking at the education of people, it may be hard to decide who is educated and who is considered uneducated. Here, it would be possible to decide on the number of certificates to decide when the team considers someone a well-educated operator. Setting these standards, help to get a clear definition for all people involved.

3.2.3 Current process flow

Making a process flow of the current state can help a team see how the process works and enables it to quickly see problems and improvement areas. The level of details in the process flow map can be adjusted to the specific needs of the team. It is also possible to make multiple process maps throughout the phases. For example, you can start with a high-over process map and decide to make a more detailed one when a problem area is selected and you are zooming in on one particular process. A short example of a process flow can be seen below (Figure 6)

Figure 6: Current process flow example

It is possible to include the process flow into Figure 6 above, to make one complete overview of the current state of the process. However, if the process flow is quite elaborate, it might be better to split it up to prevent the figure from becoming unclear. The example below (Figure 7) shows a way of displaying it in the combined way.

Figure 7: Combination of Inputs and Outputs variables AND current process flow

3.2.4 Process capabilities, current quality level, CpK, PpK

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considered, a separation can be been in reason codes, and one can divide the TAV and EAV, where the EAV are the only ones that are relevant. On the other hand, if the scope does not specifically makes a division between ‘own’ and ‘other’ NC’s, this step can be executed in a different way where the current quality level is shown. See below for an example (Figure 8).

Figure 8: NC rate per month

3.2.5 Measurement System Analysis

The Measurement System Analysis (MSA) has two steps. First, check whether the collected data is accurate. This can be done when looking at the NC rate and the reasons codes given to them by the quality department. Below a figure can be seen (Figure 9) where the MSA is executed.

Figure 9: Actual NC rate per month

The second aspect of the MSA is to set up the data collection plan. However, this will be done in sub section 3.2.7, and more information needs to be gathered to do so.

00 01 02 03 04 05 06 07

Month 1 Month 2 Month 3 Month 4 Month 5

Y = NC Rate

Including TAV Excluding TAV

00 01 02 03 04 05 06 07

Month 1 Month 2 Month 3 Month 4 Month 5

Y = NC Rate

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3.2.6 Stratification factors, brainstorming

Using stratification factors can help when collecting descriptive data that will help identify patterns in data, by filling in the example given below (Figure 10). It start with (1) output. Decide what the output is. In an NC reduction project, this will be an NC. Next decide what you want to find out about the NC (2). When you have identify what you want to know, questions can be formulated in part (3). Last (4), a way of measuring needs to be decided on.

Figure 10: Stratification factors, example

To find the stratification factors, brainstorming is a method that is often used. It is the search by a group for the solution to a problem and can be extremely useful in a variety of business situations (Ferguson, 2001). It can be used to stimulate the creative thinking process and makes sure that all group members’ ideas are considered (George et al., 2005). When brainstorming some ground rules can be set:

1. Find a group with different types of expertise, but avoid different ranks. A subordinate will always feel restrained in the presence of a superior (Ferguson, 2001).

2. Point out one facilitator.

3. Find the problem and set the goal for the brainstorm session (George et al., 2005). 4. Do not judge ideas (yet!) (Taylor, et al. 1958).

5. Go for quantity, not quality (Taylor, et al. 1958). 6. Build on existing ideas (George et al., 2005).

In practice, the project leader can facilitate the session. The problem is put onto a big piece of paper and during the brainstorm session the facilitator puts sticky notes on there. Make sure that everybody is heard and as many ideas as possible are on the paper by the end of the session. Tools can be used to help the session, for example, the 6-M model. The six M’s stand for Machine, Method, Men, Measurement, Money (or resources) and Milieu (or environment). This gives a direction of where to search and can help not to overlook possible causes.

3.2.7 Data collection plan

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of NC is measured, it is possible to find the process step and production phase where most gains can be established.

Next, it may be important to find out general information on the process. It is just as important to take measurements when something goes wrong, as when it goes right. Knowing, for example, which tools was used to drill a correct hole, may be just as valuable as knowing which drill was used to drill a wrong hole. To be even more precise, it is best to try and collect data that is continuous. In that way, one can see the process variation best. Even though a hole may be drilled correctly, it may be very interesting to see how where within this margin the size is. The more data is available, the better the process can be monitored, and information can be gained even when things are going right.

3.2.8 Pareto

The last step in the process of the essential tools is the Pareto. This Pareto can be created when data has been gathered. This is the process of ranking opportunities to determine which of many potential opportunities should be pursued first. It separates the vital few from the trivial few (Pyzdek, 2003).It can help the team zoom in on the right production phase or process steps. A small example is shown below (Figure 11).

Figure 11: Pareto, example

Here, it is clear that drilling and assembling are the processes that needs to be focused on as these are the two processes that are part of the 80% where most NC’s are found. These searching areas are the z’s of this project. This is not the same as the x’s of the process. To make the distinction more clear. The x’s are the aspects that determine the output of Y and the z’s are the direction in which to search for the x’s. For example, the Y can be an oval hole, the z is drilling as this is the process step where oval holes can be created, the x will be the sharpness of the drill, which is the actual cause for the hole size and shape.

Drilling Assembling Countersinking Rivetting

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3.3 Optional tools

3.3.1 Needed sample size (sampling)

The needed sample size may be decided on when starting to collect data. Decide how many NC’s you want to measure or which period is long enough to make correct assumption on the production phase and process step of the NC. The decision of how many data will be collected can be done pragmatic, but can also be done with the help of statistical analysis. The needed sample size can also be decided on during the process of measuring. This will depend on the data. If it is clear in which direction to search, less measurements are needed, in comparison to when it is not so evident. For this step, a time span can be decided on, but actual sampling is not necessary as all NC’s need to be measured, due to the fact that they occur relatively seldom. For a high volume process this would be different, but for Fokker Aerostructures this step is less important.

3.3.2 Sigma level (DPMO), baseline

Defining the current sigma level that can be set as a baseline helps defining the current state of the process. It is usually used in production environments with high volumes. However, calculating the sigma level may not say too much and this tools cannot solely show the current state of the process. Do not forget that the calculation can be helpful in a different way. Finding out all the opportunities can give new insights in the way the product is produced. For example, when looking at drilling it may be interesting to find the amount of holes that are drilled manually. When this number is very high, other options, like drilling with a robot, can come to mind.

However, when a calculation of the sigma level is relevant the following formula can be used:

Here the number of opportunities per unit can be, for example, the amount of holes drilled in a product. Every hole is a possible opportunity to drill a hole correctly.

3.3.3 Gage R&R (repeatability & reproducibility)

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3.3.4 Data gathering

This step in the process is the actual data gathering. It is important to base any conclusion on actual data as this is one of the main strengths of the Six Sigma way of improving any process. However, this is not an actual tool on its own.

3.4 Practical tips for the Measure phase

Here, some practical tips are given to complete the process in the most effective way. They are found with the help of interviews with GB and BB project leaders at Fokker Aerostructures and on own experiences.

3.4.1 Current state of the process

Some things need to be taken into consideration when mapping the current state of the process. First of all, a project leader should ask the employees what they believe the process looks like. There are instructions (TPD’s) written per phase of the process of assembling. However, looking at these TPD’s might not give the full picture of the state of the process. Realise that the instruction are the way it is supposed to go, not how it actually goes!

Next, when trying to find out the way it actually goes, some help needs to be given to assembly workers when describing the process. Fokker Aerostructures is a highly technical organisation with a lot of history, where many activities are done on the base of experience. So, when describing the process, make sure no steps are skipped and the assembly workers rethink exactly what they do step by step to get a complete overview of the process steps. It is even possible observe the process or film it to get a complete overview of the steps that are taken.

3.4.2 Measuring

One of the most important aspects of the ‘Measure’ phase is, obviously, the measuring. When starting this phase, do not be hesitant to start measuring those aspects that can already be measured as soon as possible. The sooner one starts with the measurements, the more data can be gathered and this will increase the speed of finding out more information of the process.

Second, the challenge of the ‘Measure’ phase is to actually measure what is needed. This might mean that extra care should be given to those aspects that seem hard or impossible to measure. Try to make all important aspects quantifiable. Thinking ‘outside the box’ is necessary here to get all the needed information.

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Chapter 4 Analyse

4.1 The Analyse phase

As seen before, the ‘Analyse’ phase comes third in the DMAIC cycle for 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 projects 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’s a lot of waste. The tools that can help you with this can be seen below.

Essential tools

Process mapping/flowcharting Fishbone/cause and effect/CEDAC Brainstorming

Pareto/prioritizing causes Hypothesis testing Baseline per X Gage R&R per X Seven wastes Improvement plan Box plot

Optional tools

Run chart

Value stream mapping/value analysis Scatterplots

Regression/correlation ANOVA

Five laws of lean

4.2 Essential tools

4.2.1 Process mapping/flowcharting

A process map, or flow chart, is an illustration where the process that was chosen can be seen in details. It helps to show how the process really works (Brook, 2010). This map is best constructed with the help of assembly workers that know the process very well and can describe each step in detail. An example can be seen below (Figure 12). What is interesting to see is that the process of drilling is many more steps than one might think beforehand. So, make sure the process is mapped out step by step no matter how small these step might seem.

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Figure 12: Process map, example

4.2.2 Fishbone/cause and effect/CEDAC

A Cause and Effect diagram is a tool that helps a team organize the ideas they have about potential causes of problems. It is sometimes called a fishbone diagram because it resembles the skeleton of a fish (George et al., 2004). CEDAC stands for Cause and Effect diagram with Added Cards and this is a special kind of Cause and Effect diagram, where solution are also given. As we are still in the ‘Analyse’ phase, no solutions are given yet, so a relatively simple fishbone is shown below (Figure 13). To construct the fishbone, a brainstorm session can help where the process map above (Figure 12) can be used to find all possible things that can go wrong. When possible mistakes are identified, the team can zoom in to get to a deeper level. The ‘why’ method can be used. This is a method to get to the real root cause (Brook, 2010). Using the example below: Determining what should be drilled goes wrong. Why: because the operator read the instructions wrong. Why: because there is a lack of discipline etc.

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4.2.3 Brainstorming

To execute the two tools mentioned above, brainstorming is a good tool to use. Sub section 3.2.6. explains brainstorming in more detail and also practical tips and trick are included there on how to facilitate a brainstorming session and make the session as efficient as possible.

4.2.4 Pareto/prioritizing causes

Now that the potential causes have been identified, a priority can be given to them. With the help of three aspects each potential cause has been given a score. The severity, the occurrence and the level of detection is given a grade between 1 thru 10, where 1 is lowest and 10 is highest. These scores can be filled in with the entire team as each team member will be able to judge the score in their particular expertise area. This tool is also called an Failure and Effect Mode analysis (FMEA).This is a risk analysis tool that can be useful in environments where you have to prevent an event from ever happening (Brook, 2010).

An example of an FMEA is given below (Table 6). Here, the score per aspect are multiplied and a total score is given. This helps rank the causes.

Table 6: FMEA, example

When looking at the potential causes of Table 6. There are three main areas that can cause problems in the process. These are discipline, the use of grease during drilling and the drill itself. When looking at just these problems, the scores per category can be added and a number of points is given per category.

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Figure 14: Pareto, example

With this figure, one can see which cause occurs most frequent and where possible gains might be biggest.

4.2.5 Hypothesis testing

Hypothesis testing refers to a set of tools that can tell us how certain we can be in making a specific decision or statement (Brook, 2010). There is always a null hypothesis (H0) and an alternative hypothesis (H1) that are tested. For example, H0 = the two sets of data are the same, H1 = the two sets of data are not the same. With testing these two statements a, so called Alpha (α) level is set. This is a measure of how confident you want to be in your decision (Brook, 2010). Usually this is set at 0,95, which is a confidence interval of 95%. The test is run and a p-value appears. A general rule is: “If P is low, H0 has to go”. The p-value is the probability of getting the same results that you got if the H0 was true (Brook, 2010). So if p is low, the probability of getting the same results is also low. There a many different types of test and per project the type of test that are appropriate will be different. To find the appropriate tests a roadmap can be used and this can be seen in Appendix II. In this map, one can see that first the type of data is important (discrete or continuous). From there different types of tests should be executed with the help of the software program Minitab.

For more information on which tests to use and which hypothesis can be tested, please refer to the Lean Six Sigma & Minitab book (Brook, 2010). This is the complete toolbox guide for all lean Six Sigma practitioners and is a very helpful book in all stages of the GB project.

One special tool that can be used in Minitab deserves some extra attention. This is the probability plot. This plot can help decide how well specific data fits within a sample. An example of a probability plot can be seen below (Figure 15).

976 635 336 0 200 400 600 800 1000 1200

Discipline Drill Grease

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28 3,295 3,290 3,285 3,280 3,275 3,270 3,265 3,260 99 95 90 80 70 60 50 40 30 20 10 5 1 Data P e rc e n t With (3.2mm) Without (3.2mm) Variable

Probability Plot of With (3.2mm); Without (3.2mm)

Normal

Figure 15: Probability plot, example

This particular plot shows the data gathered on the x-axis. On the y-axis percentages can be seen. This graph shows, for example, that within the red dots 75% of data is below 3,280 and 25% is above it. The more vertical the dots of the data are, the less variance there is in the data. With the help of this graph it is relatively easy to see how well a process is performing and it can be easily compared to other data of processes. In the example above, it is clear that the process represented by the black dots is performing better than the one represented by the red dots, due to the wider spread of the data.

4.2.6 Box plot

The box plot is one of the easiest ways of comparing sets of data. Two examples of box plots have been given below (Figure 16 and Figure 17).

Without (3.2mm) With (3.2mm) 3,295 3,290 3,285 3,280 3,275 3,270 3,265 3,260 D a ta

Boxplot of With (3.2mm); Without (3.2mm)

Figure 16: Box plot, example 1

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as 1,5 times the length of the box. Data that does not fit in the length of the whisker is called an outlier and is represented with a star (*).

Due to the use of one y-axis for both data sets, the samples can easily be compared. For example, when looking at Figure 16, it is clear that the data sample are quite similar, except for the range of the data which is bigger in the data sample at the right. However, the medians are comparable and 50% of the data lies on almost the same data outcomes.

On the other hand, when looking at Figure 17, this is not the case. The data samples are very different as they are placed in the graph in different areas and it is clear that the median of the left sample is much higher than the median of the right sample.

Without (4.8mm) With (4.8mm) 4,84 4,82 4,80 4,78 4,76 4,74 D a ta

Boxplot of With (4.8mm); Without (4.8mm)

Figure 17: Box plot, example 2

These box plots give a simple and quick way of comparing samples and are very helpful when looking at differences and similarities in a process .

4.2.7 Baseline per X

Per X, or potential cause that is found in previous steps, a baseline should be set as a starting point of the analysis. With this starting point, the team can set realistic goals and determine which goals are met and which are not. Collecting data on how a process should be executed can be used later in the ‘Improve’ phase to cross link it is potential NC’s.

4.2.8 Gage R&R per X

As explained in sub section 3.3.3 the Gage R&R measures the reproducibility and the repeatability of a measurement. Its aim is to find out whether more measurements done by the same person, get the same results. Also, it looks at whether the same results are obtained when the same measurement is done by different people. When measuring with continuous data, this is a good system to take all variation out of the measurement system. Continuous data is any variable measured on a continuum or scale that can be indefinitely divided (George et al., 2005).In executing an Gage R&R it can confirm that the data measured is reliable. When setting the baseline per X (sub section 4.2.7), it can be important to perform this Gage R&R to make sure the team is working with the right data.

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4.2.9 Seven wastes

The seven wastes of a process have been identified by Taiichi Ohno, who was Toyota’s Chief Engineer and these are often used when thinking of ‘lean manufacturing’. When looking at a process it is important to find out what the wastes are, so that it is possible to recognize ways in which to improve. The seven wastes are mentioned below (Table 7) and a short description is given.

Table 7: Seven wastes (Brook, 2010)

Waste Description

1 Overproduction Making more products than the customer requires 2 Waiting Waiting increases lead time and does not add value 3 Transporting Moving things cost money and time without adding value 4 Over processing Adding more value than the customer is willing to pay for 5 Inventory Holding inventory increases lead time and costs money

6 Motion Needless movements at ergonomic level have impact on overall efficiency and can cause health and safety issues

7 Defects Defects cause repairing or replacing which is costly

When trying to improve the “quick wins” try use these wastes to see where they occur and can be eliminated. For example, when there is a lot of waiting on a product, see how this time can be shortened. This can make the process more effective overall and can help identify possible problem areas.

4.2.10 Improvement pan

Once the problem areas are defined, an improvement plan can be written. This starts in the ‘Analyse’ phase for “quick wins” and will continue in the ‘Improve’ phase when more detailed plans should be executed in order to improve the identified problem areas. This plan can be as elaborate as needed, but some things should be made clear for the plan to be effective. The team should specify the problem, including the baseline found earlier in the ‘Analyse’ phase. Possible causes are identified and brainstorming can be used to find solutions to these problems. In this phase, the “quick wins” will be dealt with and the solutions are fairly simple. Once a solution is agreed upon, specify who will be responsible for the improvement and within what time span this solution needs to be implemented. Last, an objective should be set, so that it is clear to the entire team what you are expecting of the responsible team member and success can be measured with the set objective.

4.3 Optional tools

4.3.1 Run chart

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31 35 30 25 20 15 10 5 1 3,0 2,5 2,0 1,5 1,0 0,5 0,0 Observation N C s pe r w ee k

Number of runs about median: 17

Expected number of runs: 16,8

Longest run about median: 7

Approx P-Value for Clustering: 0,535

Approx P-Value for Mixtures: 0,465

Number of runs up or down: 20

Expected number of runs: 23,0

Longest run up or down: 4

Approx P-Value for Trends: 0,108

Approx P-Value for Oscillation: 0,892

Run Chart of NCs per week

Figure 18: Run chart, example

To get a more complete picture of the current process an I-MR chart can be computed. This chart plots two graphs. The one above shows the individual data (I), the one below shows the moving range (MR), which is the difference between each two adjacent points of the individual graph. The I-MR chart is used when few units are produced and data is scarce (George et al., 2005). An example can be seen below (Figure 19).

34 31 28 25 22 19 16 13 10 7 4 1 4 2 0 -2 O bserv ation In d iv id u a l V a lu e _ X=0,971 U C L=4,179 LC L=-2,236 34 31 28 25 22 19 16 13 10 7 4 1 4 3 2 1 0 O bserv ation M o v in g R a n g e __ MR=1,206 U C L=3,940 LC L=0 I-MR Chart of NCs per week

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In short, the graph shows the average, but also analyses the upper control limit (UCL) and the lower control limit (LCL), which represent the expected variation. The goal of any process is to reduce this variation as much as possible.

To find out whether you are searching in the right direction, it is possible to see what the process is capable of. This can be done by looking at past data and taking out the identified problem area. A new I-MR chart is made and the graph is shown below (Figure 20). On the left of the line, the current data is shown and the right of the line is the data that can be gained when the potential cause is not taken into account. Again, the first one shows the individual points and the one below shows the moving range. 64 57 50 43 36 29 22 15 8 1 4 2 0 -2 O bserv ation In d iv id u a l V a lu e _ X=0,171 U C L=0,875 LC L=-0,533 Before A fter 64 57 50 43 36 29 22 15 8 1 4 3 2 1 0 O bserv ation M o v in g R a n g e __ MR=0,265 U C L=0,865 LC L=0 Before A fter 1 1 1 1 1 1 1 1 1 1 1 1 1

I-MR Chart of C3 by Before/after

Figure 20: I-MR chart, example 2

As one can see, that the average and the variances can change drastically. These two graphs show that the goal of the project is definitely attainable and the project has a lot of potential.

4.3.2 Value stream mapping (VSM)

A value stream map (VSM) is an overview of the value stream in an organisation, from supplier to customer. It is used to identify waste in a process (Bakker et al., 2011). A value analysis is used to distinguish process steps that customers are willing to pay for from those that are not (George et al., 2005). Both can be used to clearly identify all steps of the process, but a VSM is more complicated to construct than a value analysis. Due to the relatively detailed process map an VSM is not necessary, but a value analysis can be helpful. Per step, there are three classification (George et al., 2005):

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2. Business Non-Value Added (BNVA); these are activities required by the business to executed the VA activities, but are not real value for the customer.

3. Non-Value-Added (NVA); which are activities that add no real value from the customers perspective and are not required for legal, financial or other business reasons.

In the figure below (Figure 21) the process map of sub section 4.2.1 is used and each step in the process has been given a colour to identify VA (green), BNVA (yellow) and NVA activities (red). The aim is to eliminate the NVA activities and to minimize the BNVA activities.

Figure 21: VSM, example

4.3.3 Scatterplots

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34 3,280 3,275 3,270 3,265 3,260 20 15 10 5 0 3,29 3,28 3,27 3,26 W it h ( 3 .2 m m ) Hole W it h o u t (3 .2 m m )

Matrix Plot of With (3.2mm); Without (3.2mm) vs Hole

Figure 22: Scatterplot, example

4.3.4 Regression/correlation

Regression and correlation measures are related to the scatterplot. Only, where the scatterplot shows an overview of the data, regression and correlation also find coefficients related to the data. Correlation indicates whether there is a relationship between the values of different measures (George et al., 2005). The coefficient of the correlation can be measured by the Pearson Coefficient. This is used to measure the degree of linear association between the sets of data (Brook, 2010). Minitab can be used to calculate the Pearson correlation and an example of an outcome can be seen below.

Pearson correlation of Hole and Without (3.2mm) = 0,871 P-Value = 0,000

These results give the following information:

 The Pearson coefficient range from +1 (Strong positive correlation), to zero (no correlation), to -1 (strong negative correlation).

 There is a positive correlation which can be seen by the Pearson correlation of 0.871(blue).

 If the p-value is less than 0.05, a correlation exists. Here it is 0,000(green) meaning that a correlation in the data exists.

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35 20 15 10 5 0 3,295 3,290 3,285 3,280 3,275 3,270 3,265 3,260 Hole W it h o u t (3 .2 m m ) S 0,0043312 R-Sq 75,8% R-Sq(adj) 74,4%

Fitted Line Plot

Without (3.2mm) = 3,260 + 0,001324 Hole

Figure 23: Regression, example

The percentages stated at R-Sq shows the regression, where a higher percentage means more correlation. Everything above 75% is a strong correlation.

4.3.5 ANOVA

ANOVA stands for ANalysis Of VAriance and it compares three or more samples with each other to see if any of the sample means is statistically different from one another (George et al., 2005). ANOVA can only be applied when the data is normally distributed. To give an illustration of how Minitab’s output for this tools can be interpreted two tests have been executed. Even though this is only done with the two sets of data, it can give a clear overview of what results are important. When performing an ANOVA test, there are two hypotheses, which is similar to many other tests. Here, H0 will be: there is no difference between the two sets of data and H1 will be: there is difference between the sets of data.

Here, two ANOVA’s are done, one with 3.2mm and one with 4.8mm (green). This first sets of data show that there is no significant different between the sets of data. The p-value is more than 0,05 (blue), which means that H0 is accepted. Also when looking at the horizontal lines drawn (yellow), one can seen that there is definite overlap between the samples.

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36 One-way ANOVA: 3.2mm (with vs. without) Source DF SS MS F P C9 1 0,0000533 0,0000533 1,00 0,324 Error 36 0,0019148 0,0000532

Total 37 0,0019681

S = 0,007293 R-Sq = 2,71% R-Sq(adj) = 0,01%

Individual 95% CIs For Mean Based on Pooled StDev

Level N Mean StDev -+---+---+---+--- With 19 3,27061 0,00576 (---*---)

Without 19 3,27298 0,00856 (---*---) -+---+---+---+--- 3,2675 3,2700 3,2725 3,2750 Pooled StDev = 0,00729

One-way ANOVA: 4.8mm (with vs. without) Source DF SS MS F P C9 1 0,013642 0,013642 60,95 0,000 Error 36 0,008057 0,000224

Total 37 0,021699

S = 0,01496 R-Sq = 62,87% R-Sq(adj) = 61,84%

Individual 95% CIs For Mean Based on Pooled StDev

Level N Mean StDev ---+---+---+---+--- With 19 4,8097 0,0122 (---*----) Without 19 4,7718 0,0173 (---*----)

---+---+---+---+--- 4,770 4,785 4,800 4,815 Pooled StDev = 0,0150

4.3.6 Five laws of lean

Adding lean to Six Sigma gives the best of both world and the five laws of lean should be taken into account when improving the “quick wins” in the process. Lean Six Sigma finds its foundation in four important principles (George et al,. 2004):

 Delight customers

 Improve the process

 Use teamwork

 Base decisions on data

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Customers are most important and they need to define quality which will be highest priority to achieved sustained revenue growth.

2. The Law of Flexibility

This law states that the speeds and flexibility of a process are linked. An inflexible process will hinder flow and vice versa (Brook, 2010).

3. The Law of Focus

This law states that 80% of the problems in a process will be caused by 20% of the activities. It should be best to focus on this 20%.

4. The Law of Velocity (Little’s Law)

The speed of a process is inversely related to the amount of Work-in-progress (WIP). If WIP is high, speed is low and vice versa.

5. The Law of Complexity and Cost

In general, the more complex a product is, the more it will cost.

4.4 Practical tips for the Analyse phase

4.4.1 Lean Six Sigma & Minitab book

Lean Six Sigma & Minitab is an extremely helpful book that was used extensively during the process of writing this advice. The book is divided into clear chapters and overviews per phase of the DMAIC process and most tools are explained in detail on when, where and why to use them. Sometimes, in this advice, the statistical tools are not explained in details, due to the characteristics differences in each data set. However, this book can further help with the statistical analysis and using the book throughout the project, in combination with this advice, is recommended (Brook, 2010).

4.4.2 Minitab software

As explained in previous sub sections in this chapter, Minitab is software that is used at Fokker Aerostructures to do all sorts of statistical testing. The book, described above, is helpful, but ‘playing’ with Minitab is the best way to learn the functions of capabilities of the software. During the Green Belt course of the Stork Academy, Minitab will be introduced and the project leader should experiment with it to gain some experience. From there, the GB will find that it is helpful to use this software to find potential causes. An example, is that performing an ANOVA, which can only be done with normally distributed data, on other data than normally distributed is not that exact way to use it, but can give some interesting insights. The fact that the software is easy in use, makes that tests, like the one in the example, can easily be performed and some more information can be gained with this.

4.4.3 Back to the Y’s

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Chapter 5 Improve

5.1 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). The tools that can be helpful are listed below.

Essential tools

Brainstorming for solutions Benchmarking

Assessment criteria

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

Pilot studies/testing

Implementation/documentation

Recalculation of sigma/process capability 5S

Visual management

Optional tools

Fishbone/cause and effect/CEDAC

5.2 General steps to be taken

To complete this phase there are four main steps that should be taken. Per step a short explanation is given of what the step entails and which tools below to which step.

5.2.1 Generate possible solutions

The first step in the ‘Improve’ phase is to generate the possible solutions. In the ‘Analyse’ phase potential causes, or x’s are found and verified, so the problems for the process are known. Only when the problems are known, it is possible to find solutions. The tools that belong in this step are ‘brainstorming for solutions’ and ‘benchmarking’ (see sub section 5.3.1 and 5.3.2)

5.2.2 Select the best solution

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5.2.3 Assess the risks

The best solutions have been identified, but there is one more step that needs to be taken before the solutions can be implemented. This step involves assessing the risk of the solution proposed and the ‘fishbone/cause and effect/CEDAC’ can be used here. As can be seen later in this chapter, this tool belongs to the ‘optional tools’ (in section 5.3) and is not identified as essential. This is due to the fact that when the best solution is chosen, the risks are already taken into account.

5.2.4 Pilot & Implement

The fourth and last step of the ‘Improve’ phase is to pilot and implement the solutions. This can be done, because all possible solutions were generated, prioritised and their risks were assessed. It is now safe to take the best solution and first pilot and then implement it. The following tools can be helpful here: ‘pilot studies/testing’, ‘Implementation/documentation’, ‘recalculation of sigma/ process capability’, ‘5S’ and ‘visual management’ (see sub section 5.3.6, 5.3.7, 5.3.8, 5.3.9 and 5.3.10).

5.3 Essential tools

5.3.1 Brainstorming for solutions

To find solutions to the problems that are identified, brainstorming is a good tool. Moe information on brainstorming can be found in sub section 3.2.6.

5.3.2 Benchmarking

Benchmarking can be used in the ‘Improve’ phase which involves identifying and understanding best practices from other processes and organisations (Brook, 2010). It can involve research into the best practices at the industry, firm, or process level (Pyzdek, 2003). And tells you what’s possible so you can set goals for your own operations (George et al., 2005). Benchmarking is now relatively easy (and free) to do through internet. But there are more sources of input for benchmarking, including surveys or interviews with industry experts, professional organisations, published articles and prior experience of current staff (George et al., 2005). It might be helpful to look further than the direct environment of other programs or other competitors in the industry (Brook, 2010). The best ideas may come from an entirely different industry.

5.3.3 Assessment criteria

Assessment criteria provide a constant basis of comparison within the solution selection techniques that can be used (Brook, 2010). Identifying and documenting criteria takes the guesswork out of selecting solutions and make sure to use all sources of information to determine the criteria (George

et al., 2005). You can get the information from all possible stakeholders, the process owner and

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5.3.4 Prioritisation matrix/solution selection matrix/Pareto

A prioritisation matrix or solution selection matrix are quite similar. Each attempt to give a project leader a structured technique for selecting a solution from several alternatives (Brook, 2010). An example of such a matrix can be seen below (Table 8).

Table 8: Prioritisation matrix, example

In the above matrix five solutions are given scores on their assessment criteria that where identified in sub section 5.3.2. However, not every criteria is equally important. The project leader of team should determine how the criteria are related to each other. In this case of the example, all criteria together were 100% and each criteria got a part of this 100%. Here, ‘Won’t impact the customer’ scored highest with 40%. The remaining 60% was divided over the three other criteria. From this prioritization matrix it is clear that, with the criteria and its weights, solution D is the best solutions

5.3.5 Impact & Effort matrix/Pick chart

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Table 9: Pick chart, example

BIG payoff

SMALL payoff

EASY to implement

_{B D}

Implement Possible

HARD to implement

Challenge

C E

Kill

A

The Pick chart can be used in combination with the prioritisation matrix, but can also be used separately to find the best solution, or the best combination of solutions to improve a process.

5.3.6 Pilot studies/testing

A pilot study is a localised, controlled trial of a solution in order to test its effectiveness before full implementation (Brook, 2010). It helps identify practical problems and failures in a chosen solution (George et al., 2005).

5.3.7 Implementation/documentation

Once the pilot studies have been executed feedback can be gained from these tests. It might be possible to make some adjustments to the solution or decide to make this solution part of the daily process. When implementing the solution, make sure that everything is documented. There a different ways of doing this (e.g. posters, PowerPoint presentation, written report of the project), but be sure to include why this solution is chosen. The prioritisation matrix and Pick chart can help here.

5.3.8 Recalculation of sigma/process capability

To recalculate the process capability a new I-MR chart can be made. This chart is already explained in detail in sub section 4.3.1. Also, it is possible to recalculate the DPMO, and this tool is explained in sub section 3.3.2.

5.3.9 5S

Advice Six Sigma NC reduction projects

Advice

Six Sigma NC reduction projects

Thesis MSc. Technology Management

Faculty of Economics and Business

University of Groningen

April 2013

Table of Contents

List of Figures

List of Tables

List of Abbreviation

Chapter 1

Introduction

1.1 Introduction to Six Sigma

Change agents

Characteristics

Short overview

D

efine

M

easure

A

nalyse

I

mprove

C

ontrol

1.2 Introduction to this document

Chapter 2

Define

2.1 The Define phase

Essential tools

Optional tools

2.2 Essential tools

2.3 Optional tools

2.4 Practical tips for the Define phase

2.5 Practical tips for all the steps in the DMAIC method

Chapter 3

Measure

3.1 The Measure phase

Essential tools

Optional tools

3.2 Essential tools

Y = NC Rate

Y = NC Rate

3.3 Optional tools

3.4 Practical tips for the Measure phase

Chapter 4

Analyse

4.1 The Analyse phase

Essential tools

Optional tools

4.2 Essential tools

4.3 Optional tools

4.4 Practical tips for the Analyse phase

Chapter 5

Improve

5.1 The Improve phase

Essential tools

Optional tools

5.2 General steps to be taken

5.3 Essential tools

BIG payoff

SMALL payoff

EASY to implement

B D

HARD to implement

C E

A

_{B D}