Bsc Honours Degree in Quality Management and Technology An Introduction to Six Sigma                    Eoin DuffInstitute...
AbstractSix sigma first gained public attention when Motorola won the Malcolm Baldrigenational quality award in 1988. The ...
Table of Contents:Chapter 1: Introduction                                 Page 11.1: What is six sigma?                   ...
3.9:    Pareto chart                                          Page 273.10: Cause and Effect diagram                       ...
List of IllustrationsTables:Table 1: Six sigma process capabilityTable 2: Sigma/Quality levelTable 3: Some reported benefi...
AcknowledgementsI would like to say thank you to all my friends and family who helped me and put upwith me while I was com...
Chapter 1: IntroductionThe phenomenon known as six sigma is actually quite hard to pin down and there ismuch disagreement ...
Figure 1: Process model of work (Blakeslee, 1999)Six sigma can be thought of as a business improvement mantra based on the...
Table 1: Six sigma process capability (Lucas, 2002)In theory, the higher the sigma value of a process the less likely it i...
Figure 2: Short term (left) and long term variation (right) of a single characteristic,the 1.5 σshift (Harry 1998)Research...
Table 2: Sigma/Quality level (Henderson et al 2000)As a methodology six sigma can be thought of as combining traditional q...
training needs and different responsibilities to improvement specialists. This typicallyinvolves a champion, who is usuall...
•   Harry, M, (2000), “Framework for business leadership: Breakthrough strategy    makes factorial dimensions of quality v...
Chapter 2: Evolution of Six Sigma2.1 Brief history of quality leading to Six sigmaThe history of the quality movement is a...
2.1.1   W. A Shewhart:Seen by many as the father of modern quality, Shewhart based his work on statisticalmethods and is c...
example the equipment used. The underlying theory of six sigma is not significantlydifferent to this concept, improvements...
3. Assign clear responsibility for meeting the goals   4. Base rewards on results achievedAgain the basis of a six sigma a...
employees, all departments should be involved and all should study statisticalmethods. He proposed that quality control co...
to keep quality characteristics on target. This is also know as the signal to noise ratioand can be used to choose the con...
our modern day quality understanding and methodologies. There are various differingtheories regarding the evolution of qua...
Table 4: Major events in the development of modern day quality theory (Martinez-Lorente et al 1998)                       ...
2.2    The Origins of Six SigmaAlthough it has been shown in the previous section that six sigma is firmly rooted inthe th...
of a TQM system at Motorola’s Austin assembly plant and this outlines the earlyimplementation of six sigma. The importance...
•   Hoyer, R, and Hoyer, B (2001), “What is Quality?”, Quality Progress, July,    pp 53-62•   Kruger, V, (2001), “Main sch...
Chapter 3: Six Sigma ToolsSix sigma’s main focus is achieving results that affect the bottom line by reducingvariation, in...
Define:This step should include an examination of the rationale behind a six sigma projectincluding the impact it will hav...
benchmarked against the best in class. A gap analysis can then be performed todetermine what areas require improvement in ...
3.2    Measurement system analysis (MSA):The ability to measure the quality of your product is of major importance in orde...
an upper limit of +3 standard deviations from the process mean and a lower limit of -3standard deviations from the process...
Statistical control charts as used in SPC are used to: quantify variation in the processbeing “controlled”, center the pro...
Figure 5: Flow diagram of a DFSS process (Kwak and Anbari 2006)3.5    Design of experiments (DOE):This method is used for ...
analysis of variance (ANOVA) are used to determine the significance of each factorand produce the mathematical model which...
seen in reduced defect rates and improved trouble shooting due to a deepunderstanding of the process (Raisinghani et al 20...
categories are represented by bars of differing width as it is the area of the bar whichprovides the value in a histogram ...
this tool is creating meaningful and accurate categories. If the correct categoriescannot be identified then the resultant...
documentation for brainstorming sessions such as the cross functional sessionsrequired in a FMEA project (Rooney et al 200...
relationship between the data as damage to processes and loss of business could becaused when implementing changes based o...
Table 6: Examples of commonly used statistical tools and their use (Henderson et al2000)Works cited in this chapter:   •  ...
•   Raisinghani, M, Ette, H, Pierce, R, Cannon, G and Daripaly, P, (2005), “Six    sigma: concepts tools and applications”...
Chapter 4: Implementing Six SigmaThis section will attempt to discuss some of the more important aspects involved inattemp...
Table 7: Different emphasis of six sigma in various companies (Motwani et al 2004)4.1    Six Sigma critical success factor...
measured accurately.     Metrics must be carefully selected and tools should beappropriate to the context of the processes...
from the rest of the workforce and to show the importance of the six sigma program(Coronado and Antony 2002), (Antony and ...
improve the business. It is good practice to publish results of all six sigma projects tohighlight success stories and als...
Figure 9: Six sigma belt system structure (Ho et al 2008)4.1.5   TrainingTraining is obviously of critical importance to t...
improvement projects as they have the greatest knowledge of the process they workon. Table 9 shows a comparison of the var...
4.1.7   Linking six sigma to customerAll six sigma projects should commence with a determination of customerrequirements t...
4.1.10 Understanding the tools and techniques of six sigmaSix sigma training can be divided into three main areas:   1. Te...
4.1.12 Project Prioritisation and selectionAgain, six sigma is mainly a project driven program so the selection of the rig...
•   Ho, Y, Chang, O, and Wang, W, (2008), “An empirical study of key success    factors for six sigma green belt projects ...
ConclusionS ix sigma has come a long way since it first gained recognition and popularity whenMotorola won the Malcolm Bal...
business will suffer as a result. It is critically important that the individuals who areselected to use six sigma methodo...
Bibliography     Antony, J, and Banuelas, R, (2002), “Key ingredients for the successful      implementation of Six sigma...
   Garvin, D, (1998), “Managing Quality: The Strategic and Competitive Edge”,    The Free Press, New York   Goldman, H, ...
   McAdam, R, and Lafferty, B, (2004), “A multilevel case study critique of six    sigma: statistical control or strategi...
Appendix 1: Six sigma Tools (De Koning and De Mast 2006)                                                           50
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An Introduction To Six Sigma

  1. 1. Bsc Honours Degree in Quality Management and Technology An Introduction to Six Sigma Eoin DuffInstitute of Technology Sligo April 2009
  2. 2. AbstractSix sigma first gained public attention when Motorola won the Malcolm Baldrigenational quality award in 1988. The savings ($15 billion over 11 years) (Kwak et al2006) that Motorola attributed to it’s six sigma programme attracted the attention ofnumerous companies such as General Electric, IBM, Allied Signal, Johnson andJohnson and many more. Six sigma’s rise in popularity led to various different formsof implementation, which has led to disagreement in the literature over how to definesix sigma. There is also disagreement over whether six sigma is a new concept orsimply a new form of Total Quality Management. Six sigma can be the basis of aquality management system or a driver of organisational culture change andcontinuous business improvement. In the author’s opinion, six sigma has evolvedfrom TQM and uses many of the same tools and theories but has a fixed structure (thebelt system), measurable goals and an expansive tool set to achieve those goals. Theplan used to implement a six sigma programme is critically important, there has beenprogress made towards identifying the critical success factors involved and this isdiscussed in Chapter 4. Six sigma should not be seen as a quick fix solution or a onesize fits all option for every business, if it is suitable for a business it should betailored to fit their needs and implemented with care. If suitable to the problem athand and applied correctly the benefits of success outweigh the risks of failure.
  3. 3. Table of Contents:Chapter 1: Introduction Page 11.1: What is six sigma? Page 1Chapter 2: Evolution of Six Sigma Page 72.1: Brief history of quality leading to Six Sigma Page 72.1.1: W.A Shewhart Page 82.1.2: W.E Deming Page 82.1.3: Joseph M. Juran Page 92.1.4: Armind V. Feigenbaum Page 102.1.5: Dr Karou Ishikawa Page 102.1.6: Genichi Taguchi Page 112.1.7: Philip B. Crosby Page 122.1.8: Landmarks on the road to Six Sigma Page 122.2: The Origins of Six Sigma Page 15Chapter 3: Six Sigma Tools Page 183.1: Define Measure Analyse Improve Control (DMAIC) Page 183.2: Measurement system analysis Page 213.3: Process Control Page 213.4: Design for Six Sigma (DFSS) Page 233.5: Design of Experiments (DOE) Page 243.6: Failure Mode and Effects Analysis (FMEA) Page 253.7: Capability analysis Page 263.8: Histogram Page 26
  4. 4. 3.9: Pareto chart Page 273.10: Cause and Effect diagram Page 283.11: Scatter Plots Page 293.12: Statistical Analysis Page 30Chapter 4: Implementing Sigma Page 334.1: Six Sigma Critical Success Factors Page 344.1.1: Management involvement and commitment Page 354.1.2: Cultural change Page 364.1.3: Communication Page 364.1.4: Organisational infrastructure Page 374.1.5: Training Page 384.1.6: Linking Six Sigma to business strategy Page 394.1.7: Linking Six Sigma to customer Page 404.1.8: Linking Six Sigma to Human Resources Page 404.1.9: Linking Six Sigma to suppliers Page 404.1.10: Understanding the tools and techniques of Six Sigma Page 414.1.11: Project management skills Page 414.1.12: Project Prioritisation skills Page 42Conclusion Page 44Bibliography Page 46Appendix 1: Six Sigma Tools Page 47
  5. 5. List of IllustrationsTables:Table 1: Six sigma process capabilityTable 2: Sigma/Quality levelTable 3: Some reported benefits and savings arising from six sigma programsTable 4: Major events in the development of modern day quality theoryTable 5: Process Cpk index values versus sigma valuesTable 6: Examples of commonly used statistical tools and their useTable 7: Different emphasis of six sigma in various companiesTable 8: Critical success factors for six sigma implementationTable 9: Work role versus training profile for six sigma implementationFigures:Figure 1: Process model of workFigure 2: Short term (left) and long term variation (right) of a single characteristic,the 1.5 σshiftFigure3: Overview of DMAIC methodFigure 4: Differentiation between specification limits and actual process variationFigure 5: Flow diagram of a DFSS processFigure 6: Example of a Pareto chartFigure 7: Cause and effect diagramFigure 8: Scatter Plot of Defects versus TemperatureFigure 9: Six sigma belt system structure
  6. 6. AcknowledgementsI would like to say thank you to all my friends and family who helped me and put upwith me while I was completing this thesis, you all know who you are. I would alsolike to thank my supervisor Paul Curran for being both flexible and encouragingthroughout. I would finally like to thank all the staff in IT Sligo who helped me withreferences from the library and Noel Rafferty for his initial guidance
  7. 7. Chapter 1: IntroductionThe phenomenon known as six sigma is actually quite hard to pin down and there ismuch disagreement in the literature. The reason for this may be due in part, to itsevolving nature. In this thesis a fundamental definition of what six sigma is will bediscussed. Its history in terms of its evolution and application will also be discussed,along with an outline of some of the more popular six sigma tools. In order tocritically evaluate the application of six sigma, a selection critical success factors willbe examined.1.1 What is six sigma?So what is six sigma and why does it exist? In order to understand what it is, it is firstuseful to consider why six sigma would be needed in the first place. Put simply,variation is the reason for the existence of six sigma. Variation is everywhere and inevery process, it is present in the manufacture of all products as well as the provisionof services and in this way it affects the “quality” of products and services providedby every business on the planet. The “quality” of the products or services provided bya business has a major effect on customer satisfaction, which affects the bottom lineof any business, profits. Quality itself has many definitions and will be brieflydiscussed later, for now it can be thought of as consistently giving the customers whatthey want or expect. But why is variation important? Work can be thought of as aprocess where inputs are transformed into outputs, these outputs can be thought of asthe product which is delivered to the customer. In order to be consistent in providingthe customer with satisfactory or good products, the variation within the process mustbe minimised. In order to control variation it must first be measured and understood,statistics can be used for this purpose and six sigma uses proven statistical methods tomeasure and reduce process variation and defective results, see Figure 1 below. 1
  8. 8. Figure 1: Process model of work (Blakeslee, 1999)Six sigma can be thought of as a business improvement mantra based on the corefoundation of identifying and eliminating the root causes of defects in processes. Thisis done by focusing on the outputs which are critical to customer satisfaction. Processimprovement is the goal, which leads to improved customer satisfaction as well asaugmented profits through increased savings and revenue (Snee 1999). In simpleterms, six sigma refers to the ability of a process to produce outputs with only 3.4defects per million opportunities (DPMO) or a success rate of 99.9997%, where adefect can be thought of as anything that leads to customer dissatisfaction (Snee1999). In this way six sigma proposes a direct correlation between: the level ofdefects and wasted operating costs to the level of customer satisfaction (Harry 2000).The “sigma value” can be seen as a metric to measure the quality of any process.Higher levels of DPMO are associated with lower “sigma values” where sigma in thiscase is used as a unit of measurement for the amount of defects produced by aprocess, as can be seen in Table 1. In statistical terms σ(sigma) represents standarddeviation, a measure of variation but in terms of six sigma the “sigma value” is usedto indicate how many defects are likely to occur in a process. 2
  9. 9. Table 1: Six sigma process capability (Lucas, 2002)In theory, the higher the sigma value of a process the less likely it is for defects tooccur. Consequently an increase in the sigma value will increase product reliability,improve costs and reduce cycle times as well as increase customer satisfaction (Harry2000). There is a fundamental assumption in six sigma methodology which hasgained a lot of attention within the literature, the assumption that long term processcapability can be estimated from short term performance data or the “1.5 sigma shift”debate. Based on past research at Motorola, six sigma assumes that any process isquite likely to shift from its natural center point or mean on a normal distribution, byapproximately 1.5 standard deviations at any given moment (Harry 1998). This 1.5sigma shift represents the long term variability present in a process which can be putdown to things such as wear and tear, material changes, machine set up etc. (Harry1998). With this information in mind, it can be seen from Figure 2 below that evenprocesses with very good performance in the short term can have largely increasedvariation in the long term, 0.002 rises to 3.4 DPMO when there is a 1.5 sigma shift inthe location of the process mean and Table 2 explores this relationship further. 3
  10. 10. Figure 2: Short term (left) and long term variation (right) of a single characteristic,the 1.5 σshift (Harry 1998)Research by Bothe (2002) provides a statistical rationale for the 1.5 sigma shift,stating that shifts in the mean below this magnitude have less than a 50% chance ofbeing detected by statistical process control. If these shifts remain undetected theyincrease the number of defects and widen the spread of the output. Therefore byassuming the worst and allowing for a 1.5 sigma shift the producers can have moreconfidence that their customers will receive the desired quality levels. Bothe alsostates however, that assuming a 1.5 sigma shift for every process is not optimal and hepresents a guideline based on subgroup size for selecting the level of shift to be usedfor a certain process. The important point is that all quality problems are measured byDPMO as a metric and this metric is transformed into an equivalent Z value for thenormal distribution which is known as the sigma value of process capability as shownin Table 2 below along with the effect of various shifts from the mean. 4
  11. 11. Table 2: Sigma/Quality level (Henderson et al 2000)As a methodology six sigma can be thought of as combining traditional quality toolsand statistical methods to improve profits and customer satisfaction by eliminatingdefects from processes. The “breakthrough strategy” as it is commonly referred to,which six sigma is based on was originally seen as a four step process for problemsolving and process improvement: measure, analyse, improve and control (MAIC). Adefine step is now commonly included to the MAIC process to form DMAIC. Thedefine step is self explanatory in that it defines the problem accurately and in detail.Measuring quantifies the situation, this involves analysing the measurement data andthe processes involved to identify the root cause of the problem. Improvement iscarried out by considering a range of solutions to the problem and implementing themost suitable ones. Controlling the process involves on going measurement andmaintenance of the process to ensure the problems do not resurface (Hammer andGoding 2001). This will be discussed in more detail later, it is interesting for now toconsider how similar this core MAIC process is to the traditional plan-do-check-act(PDCA) cycle originally proposed by Shewhart and popularised by Deming (Lucas2002). Six sigma enthusiasts claim that the structured roles and responsibilities of itsimplementation set six sigma apart from other quality initiatives. Six sigma uses a“belt system” (Zu et al 2008) as part of a structured approach to assign the relevant 5
  12. 12. training needs and different responsibilities to improvement specialists. This typicallyinvolves a champion, who is usually an executive who will sponsor improvementprograms and provide the resources required to complete projects. Master black beltsare experts in statistical analysis, project management, problem solving techniquesleadership skills, quality improvement techniques etc and they are responsible fortraining black belts and green belts. They are also responsible for overseeing anumber of projects which are run by black belts who in turn work with and mentorgreen belts to complete six sigma projects. Whether or not six sigma is a novel idea isirrelevant in the author’s opinion. Results to the bottom line are what matter in theworld of business and by that measure six sigma can be seen as a formidable resourcewhich has had some impressive results to date as shown in Table 3 below.Table 3: Some reported benefits and savings arising from six sigma programs (Kwaket al 2006)Works cited in this chapter: • Blakeslee, J, (1999), “Implementing the six sigma solution” Quality Progress, July, pp 77-86 • Bothe, D, (2002), “Statistical reason for the 1.5σ shift” Quality Engineering Vol 14, No 3, pp 479-487 6
  13. 13. • Harry, M, (2000), “Framework for business leadership: Breakthrough strategy makes factorial dimensions of quality visible so managers can close capability, capacity gaps”, Quality Progress, April• Harry, M, (1998), “Six sigma: a breakthrough strategy for profitability”, Quality Progress, May, pp 60-65• Hammer, M and Goding, J, (2001) “Putting six sigma in perspective” Quality, Vol 40, No.10, pp 58-62• Henderson, K, and Evans, J, (2000), “Successful implementation of six sigma: benchmarking General Electric Company”, Benchmarking: an International Journal, Vol 7, No 4, pp 260-281• Kwak, Y, and Anbari F, (2006) “Benefits, obstacles and future of six sigma approach” Technovation 26, pp 707-715• Lucas, J, (2002 ), “The essential six sigma: How successful six sigma implementation can improve the bottom line”, Quality Progress, January, pp 27-31• Snee, R, (1999 ), “Why should statisticians pay attention to six sigma?” , Quality Progress, September, pp 100-103• Zu, X, Fredendall, L, and Douglas, T, (2008) “The evolving theory of quality management: The role of Six Sigma” Journal of operations management 26, pp 630-650 7
  14. 14. Chapter 2: Evolution of Six Sigma2.1 Brief history of quality leading to Six sigmaThe history of the quality movement is a complex area of debate, despite the intenseinterest and the volume of research and publications on the subject there is still nouniversally agreed definition of quality. It seems as though every commentatorcontributing to the quality literature has their own definition of what quality is.Because of this it is useful to consider quality by a generalisation of definitions,Reeves and Bednar (1994) evaluate four definitions of quality: 1. Excellence 2. Value 3. Conformance to specifications 4. Meeting and/or exceeding expectationsConsidering the wide scope of the subject area and the difficulties encountered whiletrying to define quality, the history and development of quality is difficult to representconcisely and completely. This section will attempt to cover the main areas whichhad an impact on quality theory and practice leading up to six sigma. Whenconsidering quality theory the so called “Quality Guru’s” theories are generallyagreed to form the foundation of the modern day understanding of quality. Althoughit is understood that there is much disagreement over who is a guru and who is not,there is general a consensus over the gurus discussed in this section (Bendel et al1995), (Bendel 1991), (Martinez-Lorente et al 1998), (Nwabueze 2001), (Goldman2005), (Sanderson 1995), (Flood 1993), (Kruger 2001), (Hoyer and Hoyer 2001),(Dale et al 2001). 8
  15. 15. 2.1.1 W. A Shewhart:Seen by many as the father of modern quality, Shewhart based his work on statisticalmethods and is considered the founder of Statistical Process Control (SPC) as hepioneered the use of control charts to statistically analyse processes. He believed thatquality standards should be defined in terms of quantitatively measurable productcharacteristics; he also had consideration for customer satisfaction and value receivedfor the price paid. His definition of quality considers quality to be both subjective andobjective where the subjective side refers to what the customer wants and theobjective side refers to aspects of the product which are separate to what the customerwants. As six sigma has a customer focus and is heavily based in statistical tools itcould be argued that Shewhart’s work is hugely important to six sigma and mayrepresent the foundations of the methodology. Shewhart also considered value for theprice paid to be critically important and as six sigma focuses on bottom line savingsas well as improving product quality, in this way it could be argued that six sigma is amethodology which attempts to create quality as described by Shewhart.2.1.2 W. E Deming:Deming worked closely with Shewhart and is considered by many to have popularisedmany of Shewhart’s teachings. Deming’s definition of quality is not concisely statedbut can be considered as including the following: Quality must be defined in terms ofcustomer satisfaction. Quality is multidimensional and complex and cannot bedefined by a single characteristic. Deming emphasised variability and the differencebetween special causes and common causes. Special causes of variation can be seenas those which prevent constant performance in a statistical sense, which can beattributed to operation of the process. Common causes can be thought of as thosewhich are inherent in the process and can only be changed by management, for 9
  16. 16. example the equipment used. The underlying theory of six sigma is not significantlydifferent to this concept, improvements can be made by identifying and eliminatingspecial cause variation and subsequent improvements must involve changes in designof the process to minimise the amount of common cause variation. Six sigma uses atool known as Design For Six Sigma (DFSS) when attempting to optimise the designof a process, this will be discussed later. Deming encouraged the Japanese toimplement a systematic approach to problem solving by using the PDCA (Plan DoCheck Act) cycle. As discussed previously, the DMAIC method of structuredproblem solving used in six sigma could be considered a close relative of the PDCAcycle. Deming encouraged a top down approach to quality which required seniormanagement to become actively involved in their companies quality improvementprogrammes. This is considered a critical success factor when implementing a sixsigma program and will be discussed in more detail later.2.1.3 Joseph M. Juran:Juran proposed that a practical definition of quality was probably not possible andtherefore he defined quality as “fitness for use”. In this way it seems like he tries toencompass customer requirements (use) as well as conformance to measurableproduct characteristics or specifications (fitness). Juran focused on planning,organisational issues, management’s responsibility for quality and the need to settargets for improvement. Juran believed that quality does not happen by accident, itmust be planned for and he proposed the “quality trilogy” of quality planning, qualitycontrol and quality improvement as critical aspects. Juran also introduced a four pointformula to attain results: 1. Establish specific goals to be reached 2. Establish plans for reaching them 10
  17. 17. 3. Assign clear responsibility for meeting the goals 4. Base rewards on results achievedAgain the basis of a six sigma approach can be seen as similar to Juran’s beliefs inthat goal focused planning and responsibilities are a major part of its employment.Bonuses in many six sigma companies are tied to the financial results achieved bytheir projects which can be seen as the fourth point in Juran’s plan for reaching goals.2.1.4 Armind V. Feigenbaum:Feigenbaum is seen as the creator of total quality control. His theory outlined asystematic approach to quality which involved all staff equally trying to build qualityin to the product rather than trying to inspect out bad quality. He believed that qualitymust be defined by customer satisfaction and therefore it is a dynamic entity whichmust change along with changing customer expectations or desires. Feigenbaumstheories can be seen as forming part of the organisational side of six sigma. His beliefthat every worker must strive to build quality into the product and process by taking aproactive approach rather than trying to inspect out bad quality is also a keycomponent of six sigma theory.2.1.5 Karou Ishikawa:Known as a pioneer of the Quality Circle movement in Japan in the early 1960’s,Ishikawa attempted to make statistical techniques such as control charts, scatterdiagrams, binomial probability and sampling inspection more accessible to thoseworking in industry. He emphasised good data collection and presentation, the use ofPareto charts to prioritise quality improvement projects and the use of cause andeffect diagrams (fishbone or Ishikawa diagrams) for finding, solving and documentingthe causes of variations in quality. He described quality control as including companywide participation from top management all the way down to lower ranking 11
  18. 18. employees, all departments should be involved and all should study statisticalmethods. He proposed that quality control concepts and methods should be used forproblem solving and analysis in all areas of the business; and that internal andexternal audits should be carried out to ensure that this is actually taking place. Whenconsidering the impact of Ishikawa’s work to modern day six sigma, it is easily seenthat all of his teachings above are still the basic building blocks of a six sigmaprogram. The idea that statistical thinking should be used to solve problems in allareas of the business, and that statistical and problem solving techniques should bemade accessible to workers involved in improvement initiatives is a core principle ofsix sigma and the same tools Ishikawa recommended are still used in six sigmaprograms today.2.1.6 Genichi Taguchi:In the early 1970’s Taguchi developed the concept of the Quality Loss Functionwhich is defined as the loss imparted by the product to society from the time theproduct is shipped. The loss function shows that a reduction in variability from atarget value leads to a decrease in loss and therefore an increase in quality. This ideaof reducing variation to increase quality has been described earlier as the reason whysix sigma exists and is key to any six sigma program. Taguchi’s methodologyincluded routine optimisation of product and process prior to manufacture as opposedto the achievement of quality through inspection. Design For Six Sigma (DFSS) isused for the same purpose and could be seen as stemming from Taguchi’s work.Taguchi methodology is basically a method for identifying optimal conditions forconsistently producing a robust product which satisfies the customer requirements.Taguchi methods can be used to identify variables which are critical to quality andtherefore identify areas to improve quality. Statistical process control can then be used 12
  19. 19. to keep quality characteristics on target. This is also know as the signal to noise ratioand can be used to choose the control setting that minimises the sensitivity to noise.In this way the Taguchi method is often seen as the forerunner to the Design OfExperiments (DOE) methodology applied in six sigma which will be discussed later.2.1.7 Philip B. Crosby:Crosby is probably best known for the concepts of “Do it right first time” and “ZeroDefects”. He defines quality as conformance to the requirements that the companyhas established for its products based directly on its customers needs. Crosbybelieved that all staff should be given training for the tools of quality improvement soprevention of bad quality can take place in every area. He believed that all workshould be viewed as a process or series of actions to produce the desired output. Inthis way process models could be used to ensure clear requirements have been definedand are understood by the supplier and the customer both internally and externally.By examining Crosby’s theories on quality it can again be seen that the fundamentalsof six sigma have a lot in common with the views of the quality Gurus. In his case,3.14 DPMO is seen by many as practically zero defects. His process view of qualityis again in line with the view of quality taught by six sigma practitioners, with thebelief that prevention of bad quality by improving the processes that create theoutputs is the key to good quality. Six sigma projects are measured by financialmetrics which is again in line with Crosby’s belief that the measurement of qualitymust be price.2.1.8 Landmarks on the road to Six SigmaThe contributions of the guru’s discussed above have definitely had an influence onshaping how we view quality today and therefore how Six sigma came into existence.But they are only a minute portion of the major theorists and key events which led to 13
  20. 20. our modern day quality understanding and methodologies. There are various differingtheories regarding the evolution of quality present in the literature but there is somebasic agreement amongst certain commentators (Garvin 1988), (Dahlgaard et al1998), (Dahlgaard 1999), (Bregman et al 1994) that the main landmarks can be seenas: 1. Inspection 2. Statistical Quality Control 3. Quality Assurance 4. Total Quality Management or Strategic QualityIt can be argued that Six sigma is not vastly different to TQM in theory but it laysdown a plan to be followed or a “road map” which shows companies what structuremust be set up, the training it requires and which tools should be used in certainsituations which will all ultimately lead to the desired result of improving quality,reducing waste and increasing profits. These four landmarks represent a majorsummarisation of the events and theories which have led to our current understandingof quality, this is directly linked to six sigma’s core beliefs and many of the tools ituses. Martinez-Lorente et al 1998, outline some of the major events which haveshaped modern day quality thinking and this is included as Table 4 below. 14
  21. 21. Table 4: Major events in the development of modern day quality theory (Martinez-Lorente et al 1998) 15
  22. 22. 2.2 The Origins of Six SigmaAlthough it has been shown in the previous section that six sigma is firmly rooted inthe theories and practices used in other quality initiatives such as TQM, it can still bethought of as a separate entity and its own roots can be firmly traced back toMotorola, “six sigma” is a registered trademark of Motorola. As outlined by Harryand Schroeder (2000), six sigma gained recognition and popularity when Motorolawon the Malcolm Baldrige national quality award in 1988. The credit for coining thephrase “six sigma” is given to Bill Smith who was an engineer at Motorola’scommunications sector. Smith wrote a paper in 1985 which concluded that productswhich were found defective but were repaired during the production process werefrequently the subject of early customer complaints. Conversely, products that wereproduced right first time were rarely the subject of such early customer complaints.This sparked a debate within Motorola and eventually led to the adoption of aproactive approach to quality by focusing on process optimisation. Six sigma wasapplied to various processes and within the first four years it saved Motorola 2.2billion dollars (Harry and Schroeder, 2000). Motorola’s CEO at the time, Bob Galvinwas determined to improve quality. When Galvin read a paper written by MikelHarry, a senior staff engineer at Motorola’s government electronics group entitled“The strategic vision for accelerating six sigma within Motorola”, he realised itspotential and decided to make achieving six sigma a blue chip for the company. In1990 Galvin asked Harry to start up the six sigma research institute in Illinois inconjunction with various other companies including IBM and Kodak. These eventsrepresent the birth of six sigma as a realistic business strategy. The work done byHarry and his colleagues in Illinois laid the ground rules which are still followed bysix sigma practitioners today. Kumar and Gupta (1993) describe the implementation 16
  23. 23. of a TQM system at Motorola’s Austin assembly plant and this outlines the earlyimplementation of six sigma. The importance of SPC and DOE are outlined in thispaper as well as a focus on working in teams with assigned roles and responsibilities(early version of the belt system, although not stated), providing appropriate statisticaland problem solving training, setting targets, assigning responsibilities, justifyingcosts and documenting results. The cultural resistance to the change is also discussedand this paper represents an ideal vantage point for considering the earlyimplementation of six sigma.Works cited in this chapter: • Bendell, T, (1991), “The Quality gurus: What can they do for your business?”, London: The Department of Trade and Industry, HMSO • Bendell, T, Penson, R and Carr, S, (1995), “The quality gurus-their approaches described and considered”, Managing service quality, Vol 5, No 6, pp 44-48 • Bregman, B and Klefsjo, B, (1994), “Quality, from customer needs to customer satisfaction” London, McGraw-Hill • Dahlgaard, J, Kristensen, K and Kanji, G (1998), “Fundamentals of Total Quality Management”, London: Chapman & Hall • Dahlgaardd, S, (1999), “The evolution patterns of quality management: some reflections on the quality movement”, Total Quality Management, Vol 10, No 4, pp. 473-480 • Dale, B, Wu, P, Zairi, M, Williams, A, Van Der Wiele, T, (2001), “Total quality management and theory: An exploratory study of contribution”, Total Quality Management, Vol 12, No 4, pp 439-449 • Garvin, D, (1998), “Managing Quality: The Strategic and Competitive Edge”, The Free Press, New York • Goldman, H, (2005), “The origins and development of quality initiatives in American business”, The TQM magazine Vol 17, No 3, pp 217-225 • Harry, M and Schroeder, R, (2000), “Six sigma: The breakthrough management strategy revolutionizing the world’s top corporations”, New York: Doubleday 17
  24. 24. • Hoyer, R, and Hoyer, B (2001), “What is Quality?”, Quality Progress, July, pp 53-62• Kruger, V, (2001), “Main schools of TQM “the big 5””, The TQM magazine, Vol 13, No 3, pp 146-155• Kumar S and Gupta Y, (1993) “Statistical process control at Motorola’s Austin assembly plant”, The Institute of Management Sciences, Interfaces Vol 23, No 2, pp 84-92• Martinez-Lorente, A, Dewhurst, F and Dale, B, (1998) “Total Quality management: Origins and evolution of the term”, The TQM magazine, Vol 10, No 5, pp 378-386• Nwabueze, U, (2001), “How the mighty have fallen: the naked truth about TQM”, Managerial Auditing Journal, Vol 16, No 9, pp 504-513• Reeves, C and Bednar, D, (1994) “Defining Quality: Alternatives and implications”, Academy of management review, Vol 19, No 3, pp 419-445• Sanderson, M, (1995), “Future developments in total quality management- what can we learn from the past?”, The TQM magazine, Vol 7, No 3, pp 28-31 18
  25. 25. Chapter 3: Six Sigma ToolsSix sigma’s main focus is achieving results that affect the bottom line by reducingvariation, increasing efficiency, optimising processes and augmenting profits. Buthow is it possible to achieve such results on a practical level? As was discussed in thebrief history of quality, there have been many theories and practical solutionsdiscovered over the years for achieving these goals. Six sigma brings tools togetherfrom a variety of fields such as quality engineering, problem solving, process analysisand industrial statistics under its banner to achieve its goals. Due to the non prejudicenature of six sigma’s tool selection almost any useful scientific tool can be used toachieve its goals and only a selection of the more popular tools will be discussed inthis section. It should also be noted that applying six sigma is not a quick fix solution,nor is it suitable to every situation. It is necessary to have an understanding of eachtool, how it works, its strengths and its limitations before deciding if it is a suitableapproach to take for the problem at hand. Inappropriate application of tools can domore harm than good and is a danger that cannot be understated. De Koning and DeMast (2006) compiled a list of commonly used tools including what phase of DMAICthey are generally used in and this is included as Appendix 1.3.1 Define Measure Analyse Improve Control (DMAIC):Known as the breakthrough methodology, DMAIC is arguably the most commonlyused six sigma method and is at the heart of the six sigma mentality, an overview canbe seen in Figure. There are many variations of the basic idea present in the literatureDe Koning et al (2005) conducted a study of some of the more popular renditions andtheir research claims that the main points of each stage are as follows: 19
  26. 26. Define:This step should include an examination of the rationale behind a six sigma projectincluding the impact it will have on processes and customer satisfaction as well as anyother benefits. In order to achieve this, the customer requirements must be defined.The problem that must be solved should also be rigorously defined in this stage asfailure to accurately define the problem will jeopardise the project before it begins.Measure:The basic purpose of this stage is to convert the problem definition into somemeasurable form. In this stage the critical to quality (CTQ) characteristics should beidentified for the output of the process being examined. These are characteristicswhich represent the voice of the customer. The capability of the measurement systemto consistently measure the CTQ’s with the desired accuracy must be verified (seemeasurement system analysis below). The current output of the process should beexamined to determine the baseline defect rate and determine realistic targets forimprovement. The process should be accurately mapped and the short term and longterm process capability should be determined. An unreliable or unprovenmeasurement method can again put the project in jeopardy and carrying on a projectthat is generating false data can lead to implementation of erroneous and dangerouschanges to live processes.Analyse:This phase involves analysing the data collected in the measure phase in order todiscover the root causes of defects; and what factors impact the CTQ’s as well as todetermine what relationship these factors have with the output of the process. In thisway the root causes of defects should be highlighted and key process variables whichcause defects should be revealed. The key product performance data should be 20
  27. 27. benchmarked against the best in class. A gap analysis can then be performed todetermine what areas require improvement in order to be considered best in class. Itis important that the right analysis is made by fully trained and experiencedprofessionals as a faulty interpretation of the data could again lead to implementingthe wrong changes which could cause more harm than good.Improve:This stage involves the design and implementation of changes to the process whichwill have a positive effect on the CTQ’s and will therefore reduce variability anddefect rates. The consequences of a change to live systems should be thoroughlyanalysed and validated before making the change to avoid unwanted complications.Control:The main concern of this phase is the control of the process once the desired processcapability and output quality have been achieved. It is imperative that a reliablesystem is put in place to maintain any improvements which have been made.Figure3: Overview of DMAIC method (Cheng 2008) 21
  28. 28. 3.2 Measurement system analysis (MSA):The ability to measure the quality of your product is of major importance in order toprovide customer satisfaction. Even if you can determine what your customer wantsyou will not be able to consistently provide it unless you have confidence in yourmeasurement system. The first step in a six sigma implementation is quite often ananalysis of the ability to accurately measure the product characteristics that requireoptimisation. The methodology used to determine the fitness of measurement systemsis known as measurement system analysis (MSA). MSA is carried out as a gage studyby separating the variation due to measuring equipment (repeatability) from thevariation due to operator bias (reproducibility). Multiple measurement systems can beused to measure the same output to discover the optimum system relative to thedesired range of control. Once a suitable measurement system has been discoveredexperimentation on the process can be carried out which will provide results that canbe analysed with confidence to discover where and how improvements can be made.In order to obtain valid results the study must be carefully planned and randomisedand representative samples must be obtained to guarantee that accurate conclusionsare drawn about the measurement systems capabilities (Raisinghani et al 2005).3.3 Process control:Process control is crucial to consistently producing outputs that meet thespecifications laid down to represent customer satisfaction. A control systemhighlights when a process is producing outputs which are deviating from the processoptimum. In this way it acts as a warning system, highlighting shifts in the processbefore product quality is compromised. Statistical process control (SPC) can be usedas a method to achieve this goal. As mentioned earlier Dr Walter Shewhart pioneeredthe use of control charts, where the output of a process is measured and charted with 22
  29. 29. an upper limit of +3 standard deviations from the process mean and a lower limit of -3standard deviations from the process mean based on a normal distribution. Productcontrol requires product specifications for critical to quality characteristics of theproduct which are based on customer requirements. Products with characteristicsoutside the specification are deemed unacceptable to customers and therefore arescrapped or reworked. Process control is unrelated to the product specifications; it isbased on the capability of the production process itself. This involves measuring theoutput of a process under normal conditions over many runs. After sufficient data hasbeen collected (at least 30 runs) the mean and standard deviation are calculated.Limits of + 3 and – 3 standard deviations from the mean are put on the process, allruns are measured against these limits as opposed to the specification limits. If outputmeasurements are outside the control chart limits then something in the process haschanged and must be corrected before product quality is affected, in other wordsbefore the process output drifts beyond the product specification as seen in Figure 4.Periodic checks on the process must be carried out to ensure the limits remain suitableto the desired output, especially if customer expectations change as the process couldstill be under control but the output may be unacceptable to the customer (Raisinghaniet al 2005).Figure 4: Differentiation between specification limits and actual process variation(McAdam et al 2004) 23
  30. 30. Statistical control charts as used in SPC are used to: quantify variation in the processbeing “controlled”, center the process around the desired mean value for a givenproduct characteristic being measured, monitor processes in real time and to helpdecide when it is necessary to adjust the process to prevent defects. There are manydifferent types of control charts each suited to different types of processes but allcharts can be categorised as either variable (continuous data) or attribute (discretedata). Some examples include: the and R chart, the and S chart, XmR chart, thep chart, the np chart, the c chart and the u chart, see Rooney et al 2009 for moredetail.3.4 Design for Six Sigma (DFSS):DFSS is used to design processes which can produce products that will meet customerexpectations by being capable of working at six sigma quality levels. It is applied inthe early stages of product development and has a customer and process focus, itsgoal is to maximise quality and reduce the chance of defects occurring during routinemanufacture (Kwak and Anbari 2006). The process itself involves applyingqualitative and quantitative tools to identify and measure key performance indicatorswhich when controlled will allow the process to be optimised in terms of quality, costand time. Although powerful, DFSS can be difficult to implement and the creation ofaccurate mathematical models to predict future performance can often be verychallenging. Like all tools it should first be considered if DFSS is suitable and anappropriate use of resources for any given process before its implementation. Figure5 below shows a flow diagram of the process including some useful tools that can beused in the DFSS process. 24
  31. 31. Figure 5: Flow diagram of a DFSS process (Kwak and Anbari 2006)3.5 Design of experiments (DOE):This method is used for the optimisation of complex processes which have numerousindependent inputs which may interact with each other. DOE can be used to analysethe output and determine how it is affected by changes to the various inputs. Whenanalysing a complex system the traditional method of one factor at a time (OFAT)will rarely succeed as it ignores the interactions between the various factors. DOEattempts to discover all possibilities and the end product of a successful DOE is amathematical model that can accurately predict the output characteristics given anycombination of input variables. Typical of six sigma, this involves rigorous analysisof the process characteristics and all input characteristics. Process mapping and 25
  32. 32. analysis of variance (ANOVA) are used to determine the significance of each factorand produce the mathematical model which will be used to optimise the process andalso to trouble shoot any deviations which may occur during normal operation. Itmust be stated that this approach may not be successful in all situations. The correctstatistical approach for the conditions of the experiment can be difficult to find, if itexists at all. It is suggested that in order to have confidence in the DOE it should betested with known truths when designing the model to confirm its accuracy (Deaconuand Coleman 2000) (Raisinghani et al 2005).3.6 Failure Mode and Effects Analysis (FMEA)The purpose of FMEA is to predict problems before they occur and proactivelyimprove processes in order to prevent detrimental effects to the product/processoutput from such problems occurring. To carry out FMEA for any process; a groupof all the stakeholders must be determined and a representative from each groupshould be brought together to discuss potential problems at every stage of the process.The group will start with a process map and/or a design schematic for any relevanttools/devices. The process is carefully examined to identify any possibilities whichmay harm the product at every stage of the process. A relative priority number (RPN)is assigned to each activity depending on the severity of the failure, the possibility ofthe failure occurring and the ability to detect it. If the RPN is high, usually 120, 60for a six sigma organisation then corrective actions must be taken to reduce themagnitude of the RPN and therefore reduce the risk of detrimental effects on theproduct at that stage of the process. The corrective action may be a designedexperiment to optimise an area of the process or it may require purchasing of newequipment. A detailed FMEA may require a weekly meeting of stakeholderrepresentatives for 6 months but the benefits of such a thorough approach are usually 26
  33. 33. seen in reduced defect rates and improved trouble shooting due to a deepunderstanding of the process (Raisinghani et al 2005). It is essential that all teammembers have a deep understanding of FMEA development and that the correctinputs are identified or an inadequate and inaccurate FMEA could be the result. It isalso imperative that RPN’s represent the reality of the situation or the FMEA couldagain be ineffective.3.7 Capability analysis:The process capability (Cpk/Cp) indices are often used to measure a process’ abilityto produce outputs which conform to specifications in order to determine if a processis capable of producing products with six sigma quality. Process capability is ameasure of how much variation there is in the process in relation to its specifications.It can be used when discussing quality levels internally and also with key suppliersand customers. As can be seen from Table 5 below, if the Cpk is below a certain levelthen the process will not be capable to produce quality at a sigma level higher than thecorresponding level in the table. In order for a process to be able to operate at a sixsigma level of quality it must have a Cpk of 2 (Raisinghani et al 2005).Table 5: Process Cpk index values versus sigma values (Raisinghani et al 2005)3.8 Histogram:A histogram is a graphical display of frequencies present in a tabulated data set. Itcan be used to clearly show the number of occurrences for each different category in agiven data set. It is similar to a bar chart in appearance but it differs when the 27
  34. 34. categories are represented by bars of differing width as it is the area of the bar whichprovides the value in a histogram rather than just the height as in a bar chart. As afairly simple method to use it can be applied to provide a relatively quick insight intoany major messages present in the data. The histogram can be used to gain an earlyinsight into the data set before moving on to further analysis and is commonly used insix sigma programs to analyse data sets, but only superficial information can bedetermined, such as the distribution of the data etc. (Rooney et al 2009).3.9 Pareto chart:In the 1950’s Juran was involved in popularising the theories of an Italian economistnamed Vilfredo Pareto and Juran coined the phrase “The vital few”. The main focuswas on the Pareto principle, also known as the 80-20 rule, which states that in anysituation or set of variables; a small number of factors will have the greatest effect.For example, 80% of a company’s revenue will most likely come from only 20% ofits products. A Pareto chart is used to graphically separate the vital few areas whichshould be focused on to achieve the greatest rewards; from the trivial many which willnot provide as impressive gains should they be improved upon. A Pareto chart is agood place to start when trying to decide what areas should be the focus of animprovement project and Pareto charts are commonly used by six sigma practitioners.The chart itself is similar to a bar chart, but differs by sorting the bars so that the chartdisplays the values from the highest to the lowest from left to right, the chart usuallyincludes a cumulative percentage line as shown in Figure 6 below. If the categoriesrepresented in the first Pareto chart are complex categories then further Paretoanalysis can be performed on the major categories using stratification of individualcategories to highlight exactly where the focus should be placed to achieve thegreatest results for the effort required. The most difficult part of successfully using 28
  35. 35. this tool is creating meaningful and accurate categories. If the correct categoriescannot be identified then the resultant chart will be inaccurate and may cause teams tofocus efforts in the wrong places (Rooney et al 2009).Figure 6: Example of a Pareto chart (Rooney et al 2009)3.10 Cause and Effect diagramAlso known as the fishbone diagram or Ishikawa diagram after the man credited withits development, Karou Ishikawa who allegedly first used the tool in 1943 (Rooney etal 2009). Cause and effect diagrams can be used to analyse process deviations to findthe root cause by investigating the main causes and their sub causes which in turnleads to the effect of interest, a certain deviation for example. The effect of interest,usually a quality characteristic of the product is the focus of improvement and isdefined as Y in Figure 7 below, while the factors which could potentially impact thequality characteristic, the process variables are defined as X. The key processparameters: People, Material, Method, Equipment and Environment represent themajor areas where causes for variation may be present. These can be tailored to suitthe user’s specific process but the categories represented in Figure 7 are generally agood place to start. Using the diagram facilitates a better understanding ofinterrelationships that may exist within the process that might otherwise be difficult toidentify and the diagram can also be used to provide a good structure and method of 29
  36. 36. documentation for brainstorming sessions such as the cross functional sessionsrequired in a FMEA project (Rooney et al 2009). The major limitation of this toolcan be the people who are using it as it greatly depends on inherent skills of teammembers to identify and understand causes, sub-causes and interrelationships present.Figure 7: Cause and effect diagram (Rooney et al 2009)3.11 Scatter Plots:Scatter plots can be used to determine if there is a potential relationship between twosets of data using a graph to visually represent the data sets. It widely used by sixsigma practitioners due to its simplicity of use yet powerful nature. Whenconstructing the graph the independent variable (Temperature in Figure 8 below) isplotted on the x-axis and the dependent variable (Defects in Figure 8 below) is plottedon the y-axis. If there appears to be a relationship such as a sloped or curved line onthe graph then there more than likely is a relationship between the data. If the pointsare randomly distributed or “scattered” then more than likely there is no relationshipbetween the data. From examining Figure 8 below it could be proposed that thenumber of defects increases as the temperature increases. Proving that there is arelationship between two sets of data is a good place to start, but usually furtherinvestigation is necessary to determine the causes of the relationship and the effects ofinterrelationships between factors and with other factors if present (Rooney et al2009). Caution should be taken not to make inaccurate assumptions about the true 30
  37. 37. relationship between the data as damage to processes and loss of business could becaused when implementing changes based on inaccurate assumptions.Figure 8: Scatter Plot of Defects versus Temperature (Rooney et al 2009)3.12 Statistical analysis:One of the most widely known aspects of six sigma is its use of statistics to driveprocess improvements in a data based way. There are numerous statistical methodswhich can be applied to various situations and in the modern industrial environment itis easier to make use of them due to powerful and relatively easy to use statisticalsoftware packages such as minitab for example. The most important thing is tounderstand what method is applicable to a given situation or set of data and theaccurate interpretation of the results obtained. It should be noted that like all sixsigma tools, there will be many situations which may not suitable for this approachand if used inappropriately inaccurate theories and ineffective or damaging changes toprocesses may be the result. Some of the more common methods and their uses areincluded below as Table 6. 31
  38. 38. Table 6: Examples of commonly used statistical tools and their use (Henderson et al2000)Works cited in this chapter: • De Koning, H, and De Mast, J, (2006), “A rational reconstruction of six- sigma’s breakthrough cookbook”, International Journal of Quality and Reliability Management, Vol 23, No 7, pp 766-787 • Deaconu, S, and Coleman, H, (2000), “Limitations of statistical Design of experiments approaches in engineering testing”, J. Fluids Eng. Vol. 122, No. 2, pp 254-260 • Henderson, K, and Evans, J, (2000), “Successful implementation of six sigma: benchmarking General Electric Company”, Benchmarking: an International Journal, Vol 7, No 4, pp 260-281 • Kwak, Y, and Anbari F, (2006) “Benefits, obstacles and future of six sigma approach” Technovation 26, pp 707-715 • McAdam, R, and Lafferty, B, (2004), “A multilevel case study critique of six sigma: statistical control or strategic change?”, International Journal of operations and production management, Vol 24, No 5, pp 530-549 32
  39. 39. • Raisinghani, M, Ette, H, Pierce, R, Cannon, G and Daripaly, P, (2005), “Six sigma: concepts tools and applications”, Industrial management and data systems, Vol 105, No 4, pp 491-505• Rooney, J, Kubiak, T, Westcott, R, Reid, R, Wagoner, K, Pylipow, P and Plesk, P, (2009), “Building from the basics: Master these quality tools and do your job better”, Quality Progress, January 2009, online content only 33
  40. 40. Chapter 4: Implementing Six SigmaThis section will attempt to discuss some of the more important aspects involved inattempting to apply six sigma in an industrial setting and some critical success factorswill be discussed. The decision to embrace a six sigma program should not be takenlightly and may not suit every business. Before beginning a six sigma program athorough examination of expectations and a realistic assessment of the currentsituation of the business as well as its goals and mission statement should beundertaken. If an existing quality framework exists within the business then decisionsmust be made about how it will interact with the new program, or if the new six sigmaprogram will replace the old program then there must be a consideration of exactlyhow the transition will be made. Each business must make its quality program fit itsunique needs so a “one size fits all” solution is probably not possible and althoughmany businesses use six sigma, a closer inspection reveals some differences betweeneach company’s “version” of six sigma, see Table 7 below. However six sigmaprovides a good foundation for a quality system to be built upon and can be made tofit individual business goals by placing emphasis on the desired areas of importancefor that business and then selecting the appropriate tools and methodologies from thesix sigma tool kit to deliver the goals decided upon. 34
  41. 41. Table 7: Different emphasis of six sigma in various companies (Motwani et al 2004)4.1 Six Sigma critical success factorsDue to the highly customised nature of quality systems as discussed above, it isdifficult to determine an exhaustive list of success factors. Given the widespread useof six sigma across various business sectors from pure manufacturing to pure service,finance, healthcare etc. the difficulties of defining an all encompassing list of criticalsuccess factors becomes even more difficult and there is widespread disagreement inthe literature regarding the success of six sigma when applied to services. In theauthors opinion the difficulties encountered while applying six sigma to services aremost likely a result of the intangible nature of services and the relatively new attemptsto control quality levels when compared to manufacturing based industries, wheremany solutions to inherent quality problems had already been defined and addressedbefore six sigma was conceived. When applying six sigma in a non-manufacturingsetting it is critically important that the process is well understood and can be 35
  42. 42. measured accurately. Metrics must be carefully selected and tools should beappropriate to the context of the processes involved. The progress of six sigmaapplication in this area will require further advances in understanding service qualityas well as its measurement and control. However, there has been some progress madein the literature towards defining some critical success factors of implementing sixsigma. Nonthaleerak and Hendry 2008, investigated the progress made in this areaand suggested that the factors in Table 8 can be considered as a complete list.Table 8: Critical success factors for six sigma implementation (Nonthaleerak andHendry 2008)4.1.1 Management involvement and commitmentThis is arguably the most important factor in successful six sigma implementationsand in the major success stories such as Allied Signal, General Electric and Motorolathe involvement of the CEO in each case is seen as one of the main reasons for itssuccess. Six sigma should be part of ever employee’s daily work including top andmiddle level managers and all managers should be taught the underlying principles.Management should be involved in the creation of the process management systemand they should be involved in six sigma projects themselves to encourage buy in 36
  43. 43. from the rest of the workforce and to show the importance of the six sigma program(Coronado and Antony 2002), (Antony and Banuelas 2002).4.1.2 Cultural changeThe implementation of a new management and working structure in any organisationis a major undertaking and can be met with resistance from the workforce. Theimplementation of a six sigma program can involve a substantial change inorganisational infrastructure and this change can be met with fear of the unknown andresistance from the work force. Eckes (2000) suggests four main causes of suchresistance: 1. Technical 2. Political 3. Organisational 4. IndividualIt is crucial that the workforce understand the need for change and accept the newmethod as the way forward. In six sigma programs workers must take onresponsibility for the quality of their own work, defects must be highlighted asopportunities for improvement and workers must be made feel comfortable tohighlight defects without fear. It has been seen by examining some companies whosuccessfully managed large scale organisational changes that it is vital to increasecommunication, training and motivation of the workforce throughout the transition inorder to overcome cultural resistance to change (Coronado and Antony 2002),(Antony and Banuelas 2002).4.1.3 CommunicationA communication plan must be made with the goal of educating the workforce so theyunderstand why the change is necessary as well as how the new philosophy will help 37
  44. 44. improve the business. It is good practice to publish results of all six sigma projects tohighlight success stories and also problems which have been met in order to avoid thesame problems being met by other projects and also to earn the trust of the workforcethrough open and honest communication (Coronado and Antony 2002), (Antony andBanuelas 2002).4.1.4 Organisational infrastructureIt is essential to have the correct infrastructure in place to support the six sigmaprogram. There must be sufficient training for the individuals who have been selectedto lead the six sigma program, as well as top management support, efficientcommunication methods, teamwork and financial backing. The individuals selectedto lead the six sigma implementation are the members of the six sigma belt system(Coronado and Antony 2002), (Antony and Banuelas 2002), (Ho et al 2008): • The champion is a high level director of the six sigma program • Master black belts mentor six sigma teams and report to the champion • Black belts run six sigma projects, mentor green belts and report to the master black belt • Green belts carry out small scale six sigma projects and work with black belts on larger projectsOnce the organisation has set up the belt system as shown in Figure 9 and its membersare fully trained, the teams can be set up to start six sigma projects. It is advisable tostart with the projects that can be easily completed but will provide relatively largereturn on investment in order to gain buy in from the workforce by showing thebenefits of the six sigma approach. 38
  45. 45. Figure 9: Six sigma belt system structure (Ho et al 2008)4.1.5 TrainingTraining is obviously of critical importance to the success of any six sigmaimplementation. An effective training system allows workers to feel morecomfortable with their new roles and also helps them buy in to the program throughlearning and using new skills to tackle improvement opportunities and produce resultsto the bottom line. The belt system as described above and shown in Figure 9 must berolled out throughout the organisation starting at the very top with CEO’s and toplevel management before being cascaded down throughout the rest of theorganisational levels. The details of the training system differ from organisation toorganisation as well as from the various consultancy firms, but the members of thebelt system should be seen as the change agents within the organisation and theirtraining is critically important as they will spread this training to the rest of theorganisation over time until the entire workforce is educated in six the sigmaphilosophy, especially the operators of processes which are the subject of 39
  46. 46. improvement projects as they have the greatest knowledge of the process they workon. Table 9 shows a comparison of the various roles in the belt system with regard totheir job profile, role, training necessary and the recommended numbers within theorganisation (Coronado and Antony 2002), (Antony and Banuelas 2002).Table 9: Work role versus training profile for six sigma implementation (Coronadoand Antony 2002)4.1.6 Linking six sigma to business strategyFor every six sigma project the link to business strategy must be stated and proven,each project should have a target of process or product improvement that will directlyimpact the operational or financial goals of the organisation. Goals should be statedin financial terms whenever possible and return on investment should be analysed foreach project to determine if the potential benefits outweigh the cost of the projectbefore the project is approved. Six sigma should not be treated as a stand alone set oftools for quality improvement, it must be at the heart of the business culture to reducevariability and improve quality and therefore customer satisfaction (Coronado andAntony 2002), (Antony and Banuelas 2002). 40
  47. 47. 4.1.7 Linking six sigma to customerAll six sigma projects should commence with a determination of customerrequirements to ensure that they are customer focused. It is vitally important that thecritical to quality aspects (CTQ) defined are actually what the customer wants. Insome cases this is difficult to determine, especially in service industries. Tools suchas quality function deployment can be used to aid the determination of CTQ’s whichwill then be quantitatively defined and used as a baseline for improvement throughthe six sigma project (Coronado and Antony 2002), (Antony and Banuelas 2002).4.1.8 Linking six sigma to Human ResourcesHuman resource policies should be put in place which will encourage the workforceto internalise and actively participate in the six sigma initiative. Coronado andAntony (2002) state that “Some studies show that 61% of the top performingcompanies link their rewards to their business strategies, while lower-performingcompanies create minimal linkage”. There are many ways in which this can becarried out for example by tying bonuses to successful completion of six sigmaprojects or by requiring that full six sigma training and completion of at least oneproject for any promotion as was the case under Jack Welch CEO of General Electric(Antony and Banuelas 2002).4.1.9 Linking six sigma to suppliersIt has been stated in the literature that many organisations have found it beneficial toinclude their suppliers in their six sigma program. By selecting a fewer number ofsuppliers and working with them to reach six sigma levels of quality, the variability ofthe total process can be reduced by improving the quality of the inputs. The key is togain buy in from top management of the supplier (Coronado and Antony 2002),(Antony and Banuelas 2002). 41
  48. 48. 4.1.10 Understanding the tools and techniques of six sigmaSix sigma training can be divided into three main areas: 1. Team tools 2. Process tools 3. Leadership toolsAs stated earlier, because each business will have its own individual needs and eachprocess will have its own specific requirements, a “one size fits all” set of tools andtechniques is probably not possible. Such a tool set would be vastly over complicatedfor most situations. The sheer volume of tools available can cause much confusionand if not properly understood the wrong tool can be applied and can do more harmthan good so caution is necessary before any action is taken. The critical aspect is tounderstand what tools and techniques are suitable to your own business and whichtools should be used in certain situations. This knowledge will only come withtraining and a deep understanding of six sigma theory and application and eachbusiness should have its own customised tool set suited to its internal processes(Coronado and Antony 2002), (Antony and Banuelas 2002).4.1.11 Project Management skillsSince six sigma is mainly a project based approach it is critical that team leaders havea good level of project management skills. If projects are managed poorly, they areunlikely to succeed. All team members should consider and define the major areas ofeach project, cost, time and quality. In this way the team should determine anddocument the scope of the project and they can then attempt to deliver the goalsdecided upon in the shortest time possible for the lowest cost possible (Coronado andAntony 2002), (Antony and Banuelas 2002). 42
  49. 49. 4.1.12 Project Prioritisation and selectionAgain, six sigma is mainly a project driven program so the selection of the rightprojects that will provide the most benefit in a suitable time for an acceptable cost toresources, be it monetary or man hours is of paramount importance. If projects arepoorly selected then it is unlikely that the business will gain the most benefit fromthem if any at all. To avoid poor selection of projects there must be some criteria forselecting projects and a tracking system put in place to monitor each suggestion andits progress. Selection criteria will be specific to each business but a generalguideline criteria could be: 1. Benefits to the business: Customer requirements, financial etc. 2. Project feasibility: resources required/available, project complexity etc. 3. Organisational impact, for example cross functional and learning benefitsEach project should be reviewed by black belts and master black belts on a regularbasis reinforcing six sigma methodology is being applied at all stages. Championsshould keep regular communications with master black belts to find out whatobstacles are being faced to complete the projects and what changes can be made tofacilitate their timely completion (Coronado and Antony 2002), (Antony andBanuelas 2002).References cited in this chapter: • Antony, J, and Banuelas, R, (2002), “Key ingredients for the successful implementation of Six sigma program”, Measuring Business excellence, Vol. 6, No. 4, pp 20-27 • Coronado, R, B, and Antony, J, (2002), “Critical success factors for the successful implementation of six sigma projects in organisations”, The TQM Magazine, Vol. 14, No 2. pp 92-99 • Eckes, G, (2000), “The six sigma revolution”, John Wiley and Sons, New York, NY 43
  50. 50. • Ho, Y, Chang, O, and Wang, W, (2008), “An empirical study of key success factors for six sigma green belt projects at an Asian MRO company”, Journal of Air Transport Management, 14, pp 263-269• Motwani, J, Kumar, A, Antony, J, (2004), “A business process change framework for examining the implementation of six sigma: a case study of Dow chemicals”, The TQM Magazine, Vol. 16, No 4. pp 273-283• Nonthaleerak, P, and Hendry, L, (2008), “Exploring the six sigma phenomenon using multiple case study evidence”, International Journal of Operations and Production Management, Vol. 28, No. 3, pp 279-303 44
  51. 51. ConclusionS ix sigma has come a long way since it first gained recognition and popularity whenMotorola won the Malcolm Baldrige national quality award in 1988. Today six sigmacan be many things depending on how it is applied. It can be the basis of a qualitymanagement system or a driver of organisational culture change and continuousbusiness improvement. It has a large tool set, both quantitative and qualitative, drawnfrom many different sources including quality engineering, problem solving,marketing, industrial statistics etc. and although it makes use of statistical methods itis more than “just a set of statistical tools”, which is a common misconception. Asdiscussed in chapter 2 the roots of six sigma can be firmly linked with the history ofquality and total quality management. Many of the tools used by six sigma have theirorigins in TQM and the various quality movements of the past. It has been arguedthat six sigma overcomes some of the problems inherent in TQM by definingquantifiable goals and providing a framework for achieving them in the belt systeminfrastructure and the associated roles and responsibilities of its members. In theauthor’s opinion, it is irrelevant whether six sigma is vastly different to TQM, it is theresults that matter and six sigma has experienced both success and failures. A sixsigma program is generally introduced with the goal of reducing variation in allprocesses to produce outputs with only 3.4 defects per million opportunities,continually improving quality, reducing waste and increasing customer satisfactionwhich ultimately leads to an increase in profits. However, it should not be seen as acure to every problem that a business may face and six sigma may not suit everybusiness. Six sigma implementation is a huge undertaking and if any of the criticalsuccess factors discussed in chapter 4 are not carried out with the necessarycommitment and expertise then there is a danger that the program will fail and the 45
  52. 52. business will suffer as a result. It is critically important that the individuals who areselected to use six sigma methodology are given sufficient training and are madeaware of the strengths and weaknesses of each tool, as well as what situations it issuitable for and more importantly which situations it is not suitable for. In untrainedhands, application of six sigma tools can greatly damage a business by implementingerroneous changes based on incorrect assumptions or unreliable data. In order to besuccessful the critical success factors outlined in chapter 4 must be given dueattention and all employees must internalise the six sigma philosophy in order to reapthe potential rewards of reduced cycle times, reduced variation and defects, increasedquality levels, customer satisfaction and profits. In the authors opinion the decision toembark on a six sigma implementation should not be taken lightly, but if it seemssuitable to the organisational goals and the necessary commitment, financial backingand attention to the critical success factors is provided then the potential benefits ofsuccess outweigh the risks of failure. 46
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  55. 55.  McAdam, R, and Lafferty, B, (2004), “A multilevel case study critique of six sigma: statistical control or strategic change?”, International Journal of operations and production management, Vol 24, No 5, pp 530-549 Motwani, J, Kumar, A, Antony, J, (2004), “A business process change framework for examining the implementation of six sigma: a case study of Dow chemicals”, The TQM Magazine, Vol. 16, No 4. pp 273-283 Nonthaleerak, P, and Hendry, L, (2008), “Exploring the six sigma phenomenon using multiple case study evidence”, International Journal of Operations and Production Management, Vol. 28, No. 3, pp 279-303 Nwabueze, U, (2001), “How the mighty have fallen: the naked truth about TQM”, Managerial Auditing Journal, Vol 16, No 9, pp 504-513 Raisinghani, M, Ette, H, Pierce, R, Cannon, G and Daripaly, P, (2005), “Six sigma: concepts tools and applications”, Industrial management and data systems, Vol 105, No 4, pp 491-505 Reeves, C and Bednar, D, (1994) “Defining Quality: Alternatives and implications”, Academy of management review, Vol 19, No 3, pp 419-445 Rooney, J, Kubiak, T, Westcott, R, Reid, R, Wagoner, K, Pylipow, P and Plesk, P, (2009), “Building from the basics: Master these quality tools and do your job better”, Quality Progress, January 2009 online content Sanderson, M, (1995), “Future developments in total quality management- what can we learn from the past?”, The TQM magazine, Vol 7, No 3, pp 28-31 Snee, R, (1999 ), “Why should statisticians pay attention to six sigma?” , Quality Progress, September, pp 100-103 Zu, X, Fredendall, L, and Douglas, T, (2008) “The evolving theory of quality management: The role of Six Sigma” Journal of operations management 26, pp 630-650 49
  56. 56. Appendix 1: Six sigma Tools (De Koning and De Mast 2006) 50
  57. 57. 51

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