International Journal of Lean Six Sigma A comprehensive insight into the Six Sigma DMAIC toolbox Meryem Uluskan

Article information: To cite this document: Meryem Uluskan , (2016),"A comprehensive insight into the Six Sigma DMAIC toolbox", International Journal of Lean Six Sigma, Vol. 7 Iss 4 pp. Permanent link to this document: http://dx.doi.org/10.1108/IJLSS-10-2015-0040 Downloaded on: 19 September 2016, At: 06:12 (PT) References: this document contains references to 0 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 23 times since 2016*

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A COMPREHENSIVE INSIGHT INTO THE SIX SIGMA DMAIC TOOLBOX

ABSTRACT Purpose: As opposed to general literature reviews, by narrowing down the context only around the resources related to Six Sigma tools, this study offers a strong discussion about Six Sigma toolbox

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which has a vital role in success of Six Sigma. Design/methodology/approach: Based on a comprehensive literature research, the most used tools, classification of tools, flow of tools with respect to define, measure, analyze, improve, and control (DMAIC) steps, tools as Critical Success Factors and reasons of ineffective use of tools are reviewed. In order to stay focused and not to diverge from the research aim, 60 articles which are suitable to the context and flow of the discussion are selected during the construction of the study. Findings: The study provides a detailed and integrated review of Six Sigma articles about tools. The most used tools are listed from different perspectives and resources, and the role of these tools has been discussed. After a broad review, a more practical and combined classification of Six Sigma tools is proposed. Next, the issue of using which tools during which steps of DMAIC is systematically addressed. Finally, emergence of tools as a critical success factor and the gaps in the literature related to tools of Six Sigma are pointed out. Practical Implications: Addressing important statistics and the facts related to the tools of Six Sigma helps especially new practitioners to build a strategic filter to select the most proper tools throughout their projects. Originality/value: This study is unique in investigating only Six Sigma toolbox and providing a literature review on this subject. Keywords: Six Sigma Tools, Most Used Tools, Classification, Flow of tools, Critical Success Factors

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1. INTRODUCTION Six Sigma is an advanced self-control process that aims to produce or deliver near-perfect products and services. As Six Sigma received more and more attention by industrial and academic environments, much has been written about Six Sigma. Because Six Sigma literature has become extremely broad, an overall literature review on this subject is not able to explain in detail any sub-topics in Six Sigma. In order to build efficient articles, literature

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reviews on this subject must be confined to a narrow perspective. This study aims to offer a strong discussion about what is written about Six Sigma toolbox to provide Six Sigma practitioners with some practical hints and valuable highlights. To achieve success, implementation of Six Sigma requires a systematic and disciplined application of some specific tools and techniques (Antony et al., 2007). Furthermore, in their study, Raisinghani et al. (2005) even stated that Six Sigma is a toolset, not a management system. Although the cultural and managerial aspect cannot be ignored or underestimated, the key to success in Six Sigma lies behind rigorous utilization of the tools. Therefore, keeping in mind that Six Sigma in essence is a large toolbox, having a sufficient understanding of these large bulk of tools and properly selecting and implementing the most suitable ones among these tools are critical to maintain the progress in the Six Sigma initiative. Up to now, a great deal of publications about the tools of Six Sigma have been accumulated, therefore a systematic literature review on this subject have become necessary. Some literature review studies classify many case-study papers under "tools and techniques" category (see Aboelmaged, 2009) and these literature reviews may appear to be directly about Six Sigma tools. However, referring case study papers directly under "tools and techniques" theme can be misleading since these papers only provide specific examples about use of particular tools and do not provide a general insight into the whole toolbox. Therefore, our study distinguishes from this type of case-study-based studies by systematically focusing

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on the papers and the books that mainly provide an overview of the Six Sigma tools. There exist valuable resources, especially books, that provide detailed explanations about the Six Sigma tools and techniques (among others, Pyzdek and Keller 2003; George et al., 2005; Basu, 2009). However, a comprehensive and systematic research which is cumulatively investigating these books and papers about tools of Six Sigma is missing in the literature. Considering the great significance of the tools and techniques to the success of the Six Sigma,

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and the related gap in the literature mentioned above, our paper presents a strong discussion about Six Sigma toolbox. The remaining of the paper is organized as follows: First in section 3.1 definitions and the distinction between "tool" and "technique" are presented. Starting from section 3.2.1, the most used tools in Six Sigma are discussed by first addressing why we need to know the most frequently used tools. After providing a detailed discussion about the most frequently used tools from different perspectives and studies in section 3.2.2, it is also discussed whether the most used tools are the least powerful ones in section 3.2.3. In section 3.3, a comprehensive review on tool classification in Six Sigma is presented. In section 3.3.1, after synthesizing and analyzing previous classifications, we offer a more practical and combined classification of Six Sigma tools. Next in section 3.4, a review on the flow of the tools of Six Sigma with respect to each define, measure, analyze, improve, and control (DMAIC) steps is presented to overcome the confusion of using which tools under which steps. Then in section 3.5, literature that refers the tools as Critical Success Factors of Six Sigma has been reviewed. Finally, in section 4 the related gaps in the literature are pointed out to provide future research directions.

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2. METHODOLOGY In this study the aim was to systematically review the journal papers that are directly related to Six Sigma tools. We both utilized Google Scholar and the Science Citation Index databases as our primary search databases because they are commonly used in the academia. The search focused exclusively on peer-reviewed academic journal articles. Our aim was to find the papers that directly provide a general overview of Six Sigma tools and techniques. In order to

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attain a reliable synthesis of primary research studies, the search is set out by choosing a set of keywords and possible combinations that relate to Six Sigma toolbox. The first part of Table 1 shows the number of articles that are retrieved by the corresponding keywords within the North Carolina State University (NCSU) library database. This table is a good representation of the challenge to obtain the articles with the desired content under Six Sigma tools category. A considerable number of papers were returned when "Six Sigma + tools" is searched, because the concept of Six Sigma embraces a very wide range of aspects and many case-study papers mention about tools of Six Sigma. On the other hand, when "Most used + tools + Six Sigma" is searched, it is not possible to receive any related article. This situation reinforce the motivation of this study. Because of accumulated bulk of resources about Six Sigma, whenever it is necessary to retrieve the resources related to a specific content, the search results are emerging as too many to be manually eliminated or too less to be persuaded to access all related resources. Consequently, this study is a very critical resource which investigates large databases (such as Google Scholar) with very carefully selected keywords followed by patient manual content analyses to obtain related studies regarding specifically to Six Sigma toolbox,. [Insert Table 1 Here] For the section 3.2, we defined the first three keyword combinations shown in second part of Table 1, which are supposed to provide us with the possible articles mentioning or

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listing the most used tools of Six Sigma within Google Scholar search engine. When the combined query "most used tools" and "Six Sigma" has been searched in Google Scholar, 66 articles are retrieved. Next step is to filter out irrelevant articles which are not directly mentioning about the most used tools of Six Sigma. In order to demonstrate the difficulty in finding the relevant articles, in Table 2, a couple of articles among these 66 retrieved search results and their context in terms of "most used tools" are listed. Even though they are all

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talking about the most used tools in quality management related areas, they all are eliminated because of content mismatch as seen Table 2. Finally only 4 articles out of 66 was retained to further discussed in section 3.2. The other combined keywords and the resulting total of number of articles that are retrieved within Google Scholar, and the articles having an exact content match are shown in Table 1. [Insert Table 2 Here] The literature search is handled by exhaustively searching almost all possible set of keywords and all possible combinations that fit each part of Section 3 which are all about Six Sigma tools and techniques. While it was possible to catch the related articles with the related keywords, sometimes we had to investigate the related sources from other perspectives and extract related content from these articles. It has been mentioned that when we search "the most used" or "the most commonly used" tools of Six Sigma it is possible to receive a reasonable amount of related papers. On the other hand for section 3.3, as it can seen in Table A when "classification of tools" and "Six Sigma" has been searched by Google Scholar, only a few related studies showed up. A number of classification schemes for Six Sigma tools exists in the literature - the majority of which are based on the steps of DMAIC methodology. However, the aim of section 3.3 is to retrieve other tool classification schemes which are primarily based on functionality. At this point, we referred to a couple of books about Six Sigma Tools, and regarded their index as a classification scheme for Six Sigma tools. Another

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way to obtain relevant resources was to investigate the articles that cited the resources that we had already found to match the desired content. While investigating the related articles for section 3.4, searching keywords which are directly explaining the query such as "when to use which tools for DMAIC" did not yield effective results. Therefore, there was a need to come up with several alternative keywords. "Roadmap of DMAIC", "flow of DMAIC", "timeline DMAIC" were all useful keywords

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which brought a couple of potential relevant documents. Finally, for section 3.5, we carefully tracked the articles about critical success factors of quality management starting from the earlier ones (e.g. Saraph et al. (1989)) up to the most current studies (e.g. Ismyrlis and Moschidis (2013)). After scanning a large bulk of articles and books, in order to stay focused and not to diverge from our research aim, 60 articles which are suitable to the context and flow of our discussion are selected during the construction of the study. Each article was carefully reviewed and our paper was organized to reflect the status of perception of tools and techniques in the literature. This research serves as a comprehensive base for a complete understanding of Six Sigma tools and techniques. 3. TOOLS OF SIX SIGMA In this section first definitions and the distinction between "tool" and "technique" are presented. Then a detailed discussion about the most frequently used tools from different perspectives and studies are provided. 3.1. Definitions, Tools And Techniques First it is important to clarify the distinction between tools and techniques. While a tool has a specific role and is often narrow in focus, a technique has a wider application and requires specific skills, creativity and training (Antony, 2006). A single tool may be described as a device which has a clear role. Some examples are cause-and-effect-diagram, relationship

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diagram, control chart, histogram, Pareto analysis, and flow chart, among others. A technique, on the other hand, can be viewed as a collection of tools which are necessary for wider applications (Basu, 2009). Some examples of techniques are Statistical Process Control, Quality Function Deployment (House of Quality), Failure Mode and Effects Analysis (FMEA), and Design of Experiments (DOE), among others. Sometimes, there exist some inconsistencies in tool/technique classifications, as an example, supplier-input-process-output-

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customer (SIPOC) model is regarded both as a tool (Basu, 2009) and a technique (Ismrylis and Moschidis, 2013). Consequently, considering these inconsistencies and that a technique is the combination of tools, for the sake of simplicity we will use the term "tools of Six Sigma" to refer both the tools and the techniques of Six Sigma in the rest of the paper. 3.2. The Most Used Tools in Six Sigma In this section the most used tools in Six Sigma are discussed by first addressing why we need to know the most frequently used tools. After providing a detailed discussion about the most used tools from different perspectives and studies, it is discussed whether the most used tools are the least powerful ones. 3.2.1. Why need to know the most frequently used tools? Appropriate use of analysis tools can impact the productivity and profitability of a firm at a large extent. On the other hand, exhaustive usage of tools may cause counter effect in problem solving and improvement efforts. In Firka (2010), it is mentioned that teaching a lot of tools of Six Sigma can be a significant problem during introduction phase of Six Sigma to organizations. In his study, he points out that after spending a lot of time to learn how to apply all the tools, some Six Sigma black belts can go beyond the real requirements of their projects by trying to apply all these tools. According to his study, this type of frustrating periods can severely damage the perception of usefulness of Six Sigma. Therefore, the solution that he mentioned in his study is to start the Six Sigma with a training program focusing on the tools

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that are most used. Consequently, keeping these facts in mind, it can be claimed that the necessity to know the most used tools of Six Sigma arises especially for organizations new in Six Sigma. Six Sigma includes a very large bulk of tools. This brings an anxiety for team members or team leaders who are new in Six Sigma. At this point, it can be very useful to learn which tools are more frequently used by other practitioners or organizations. The most

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frequently used tools (at least some parts of them) can be regarded as the most practical tools which can be easily understood by the practitioners or stakeholders. Six Sigma black and green belt training includes a set of Six Sigma tools which consists of the most used tools, therefore green and black belts are supposed to be familiar at least with these ones (Snee, 2005; Voehl et al. 2012). Therefore, not only new practitioners but also academic environments are interested in figuring out which tools of Six Sigma are most used by the means of empirical studies. Moreover, in Linderman et al. 2006, the authors argue that when goal difficulty is high, increasing use of Six Sigma tools results in higher performance. Therefore, for project teams that have already reached a saturation level in Six Sigma implementations and have started to set more challenging and difficult goals, increasing use of Six Sigma tools results in higher performance. So it can be concluded that not only for new practitioners but also for experienced practitioners, there is evidence that systematic and rigorous use of Six Sigma tools result in superior project results and performance. Considering these findings, the necessity to know the most frequently used tools in Six Sigma appears crucial in achieving better results in the Six Sigma projects. Table 3 represents the research studies about the most frequently used tools of Six Sigma with respect to different studies as well as most used tools of TQM to provide a comparison. [Insert Table 3 Here]

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3.2.2. The most used tools from different perspectives and studies In Antony and Banuelas (2002) which is one of the first studies investigating the most frequent tools, the most used Six Sigma tools are listed as cause-and-effect analysis, Pareto analysis, control charts and run charts. They also mention that many companies are not using DOE, Taguchi methods, quality function deployment (QFD), FMEA, 5-S practice, Poka-Yoke and statistical process control (SPC). On the other hand at the same year, in Cury and

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Kadasah (2002), the most used qualitative tools of TQM are cited as check lists, flow charts and brainstorming, and the most used quantitative tools of TQM are cited as sampling inspection and control charts. In Bayazit (2003), by the means of a table which provides the numbers of companies using each tool, the most used tools of TQM are listed as Pareto charts, SPC, cause-and-effect diagrams, and process chart. In Antony (2004), for UK service industries, the most commonly used tools of Six Sigma in the service organizations are listed as bullet points: brainstorming, process mapping, affinity diagrams, root cause analysis, control charts, benchmarking, Pareto analysis and change management tools. The least commonly used tools and techniques are again listed as bullet points: QFD, Hoshin-Kanri (policy deployment), Kano Model, design of experiments, statistical process control and Poka-Yoke (mistake proofing). In Tari (2005), this concept was investigated in more detail under TQM circumstance. In this study, several tools are given within a matrix table representing the percentages of the companies which are familiar with these tools, which implemented them and which are regarding them as basic tools. In Antony et al. (2005), for SMEs (small and medium sized enterprises) in the UK, it is mentioned that the most popular tools and techniques include process mapping, histogram, cause-and-effect analysis, run chart, control chart, FMEA, process capability analysis (PCA), and Poka-Yoke. On the other hand, they mention that non-parametric tests (e.g. MannWhitney test), affinity diagram, project charter, SIPOC, quality costing analysis, run charts,

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measurement system analysis (MSA) and QFD are not popular in many SMEs. They also provide a matrix table which shows the rates of usefulness of many tools as well as the familiarity and usage rate of companies with respect to these tools. In Antony and Desai (2009), they preferred to list the most used tools in Six Sigma under two categories. They mention that the most commonly used statistical tools and techniques are listed as histogram, run charts, SPC charts and PCA. Similarly, the most

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commonly used problem solving tools are brainstorming, cause-and-effect analysis, Pareto analysis, process mapping and project charter. The least commonly used problem solving tools are listed as affinity diagrams, force field analysis and matrix analysis. And, the least commonly used statistical tools and techniques are non-parametric tests (Mann-Whitney Test), Taguchi methods and DOE. It was also found that FMEA is also quite popular in the participating companies whereas QFD was not very popular among the companies participated in their survey. While most used tools of Six Sigma were continued to be investigated, in her study with a different perspective, Erginel (2010) looked at frequently used tools of TQM both in SMEs and in large companies. The author stated that basic problem solving tools such as brain storming, pareto analysis and control charts are the most preferred tools by both large companies and SMEs. FMEA is the most preferred tool (large companies 43%, SMEs 25%) for advanced evaluation of data. She also mentions in her research that statistical tools are approximately used twice as much as in large companies than SMEs. For both large companies and SMEs, scatter diagram, box plot, QFD, and regression analysis are among the least used tools. Also, in Nguenang, L. B. (2010) and Antony and Kumar (2012), the authors investigated the most used tools of Six Sigma among South African and Scottish organizations respectively.

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In Miguel et al. (2012), the ten most tools used by the companies are given as: data collection, histogram, Pareto diagram, brainstorming, controls charts, capability measures, flow chart, process mapping, measurement system evaluation, and SPC. Their results also indicate that eight of the ten most-used tools and techniques are concentrated in the “measure” stage of DMAIC. The ten least used tools according to their study: out-of-control action plan (OCAP), process decision program chart (PDPC), evolutionary operation, operational testing,

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program evaluation and review technique (PERT), Critical Path Method (CPM), market testing, stakeholder analysis, fault tree analysis (FTA) and the accelerated life test. Finally, from a different perspective, Souza et al. (2014) compares the rate of usage of quality tools for different quality initiatives such as ISO 9001, Lean Manufacturing and Six Sigma, however, the number of total respondents implementing Six Sigma was fairly limited. As it can be seen from second column of Table 3, because these studies are conducted within different countries and even within different sectors such as service, manufacturing and software etc., the most used tools can be anticipated to different. However, still it is possible to find common tools among these studies. By referring a couple of previous studies and creating a table to demonstrate the most used tools of Six Sigma, Pulakanam and Voges (2010) decided that even though well-known seven tools of quality are the most used ones, Six sigma implementation differ from TQM programs by more frequently engaging sophisticated tools, such as ANOVA and probability plots. This sentence best describes the overall view of frequency of use of Six Sigma tools. 3.2.3. Are the most used tools the least powerful ones? In Antony et al. (2005), the authors define the most used tools as the tools which offer visual representation and are easier to use, therefore they attract more users compared to the more sophisticated and complex statistical tools. In conjunction with this definition, in Antony and Banuelas (2002), it is mentioned that the tools which are less frequently used are more

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powerful compared to most used tools. In other words, the authors imply that more powerful techniques are unfortunately less frequently used in the organizations. Therefore from this discussion, we can claim that companies do not effectively benefit from the Six Sigma methodology, just like human-being uses his or her brain at only very low capacity. Hahn et al. (2000) mention that most Six Sigma tools are not new, but became popular under the structured flow of DMAIC. The skills obtained by employees after

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industrial training programs on specialized topics such as DOE, SPC, regression and ANOVA are so temporary that they are quickly forgotten when employees return to work. However, disciplined steps of Six Sigma are believed to make these skills more permanent, so more popular in quality management. Furthermore, it is mentioned that these complex tools will become increasingly more important as the organizations move beyond the simplest problems to more complex ones. To sum up, today the tools which offer visual representation and are easier to use appear as the most used tools of Six Sigma. However, as the companies experiences increase, the most used tools will shift towards the more powerful and complex tools which will bring more benefits to organizations. 3.3. Tool Classification in Six Sigma Six Sigma training period includes introduction of a large number of Six Sigma tools to prospective practitioners. During this training, it is very valuable to present tools of Six Sigma in such an organized way that prospective practitioners fairly figure out the relationships between all the tools of Six Sigma. To accomplish this task, systematic classification schemes of Six Sigma tools are necessary at all levels to guide the practitioners to select which tools to use within the large bulk of Six Sigma toolset. During Six Sigma projects when the practitioners are not satisfied with implementing some set of tools, they should easily access the list of other options with which they can substitute their current tools. A number of classification schemes for Six Sigma tools exists in the literature - the majority of which are

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based on the steps of DMAIC methodology. However, other tool classification schemes which are based on functionality or basic characteristics are necessary to better help practitioners during their Six Sigma projects. One of the early detailed classifications of Six Sigma tools is made in Tague (1995). The author created a "tool matrix" in which she labeled each tool as one of the following categories: project planning and implementing tools, idea creation tools, process analysis

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tools, data collection and analysis tools, cause analysis tools, evaluation and decision making tools. This table is such a valuable one that it classifies a very large set of tools based on functionality of tools in a very detailed way. However, assignment of certain tools to some categories looks perplexing at the first glance. As an example, mistake proofing which is mostly regarded as an improvement tool is assigned to the category of "Process Analysis tools", which may be confusing for new practitioners or team leaders. Furthermore, separating "Data Gathering and Analysis" as "Data Gathering" and "Data Analysis" could be better because these actions are quite different in essence. Based on this source and ASQ (American Society for Quality) website, an abbreviated version of this classification scheme is provided in Chakraborty and Tan (2012). In Pande et al. (2002), an another classification scheme for Six Sigma tools is provided. The categories of this classification scheme are: Tools for generating ideas and organizing information, Tools for data gathering, Tools for process and data analysis, Tools for statistical analysis, and Tools for implementation and process management. This classification scheme also is very reasonable and efficient, however it lacks "decision-making tools (or solution selection)" tools, and it would be better if "tools for process and data analysis" and "Tools for implementation and process management" are both divided into two sub-categories.

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In George et al. (2005), another efficient classification is provided as in the following way: Tools for working with ideas, Process Flow Tools, Voice of Customer (VOC), Data Collection Tools, Descriptive Statistic Tools, Variation Analysis Tools, Identifying and Verifying Causes Tools, Selecting and Testing Solution Tools. The first significant modification of this classification to former ones is the introduction of the category "Process flow tools". This category used by George et al. (2005) to refer to flow charts, value stream

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maps, spaghetti diagrams etc. is also later used by Bentley and Davis (2009). In George et al. (2005), the other categories which are not obviously apparent in former two classifications are the "Variation Analysis Tools" and "Descriptive Statistics Tools". These categories are respectively corresponding to "Process Capability Analysis" and "Knowledge Discovery Tools" in Pyzdek and Keller (2003), therefore can be named accordingly also with these names. As Kwak and Anbari (2006) points out Six Sigma method has two major perspectives: statistical and strategic. The origin of Six Sigma comes from statistics and statisticians (Kwak and Anbari, 2006) and therefore Six Sigma's foundation is in statistical analysis (Zugelder, 2012). Hahn et al. (1999), Hoerl and Snee (2002), and Montgomery (2001) make emphasis on a statistical, probabilistic, and quantitative point of view of Six Sigma method (Kwak and Anbari, 2006). On the other hand, in the business world, Six Sigma is defined as a business strategy used to improve business profitability, to improve the effectiveness and efficiency of all operations to meet or exceed customer’s needs and expectations by Antony and Banuelas (2001) (Kwak and Anbari, 2006). Therefore considering both statistical and qualitative dimensions of Six Sigma, a high level classification of Six Sigma tools as qualitative vs. quantitative will be appropriate. In Scheuermann et al. (1997), a classification scheme 'qualitative and quantitative tools of TQM' are cited by providing the lists of tools for each category as bullet points. Chappell and Peck

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(2006) defines DMAIC methodology as 'a mixture of quantitative and qualitative tools' by which root causes of problems are identified. In Ricondo and Viles (2005), Kano Analysis, QFD and FMEA are named as qualitative tools. In the literature, quantitative and qualitative tools are also sometimes more precisely referred to as statistical vs. non-statistical tools (Antony and Banuelas, 2002; Nonthaleerak and Hendry, 2008). Non-statistical tools class can be also referred as mind tools or sometimes only as

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"problem solving tools" (Pyzdek and Keller, 2003). If a comprehensive classification is desired, non-statistical tools can be categorized as team management tools, decision making tools (decision matrix analysis, paired comparison analysis, the analytic hierarchy process, Pareto, decision tree analysis, Delphi method etc.), strategy tools (critical success factors, SWOT analysis, Porter's five forces analysis, benchmarking, critical-to-quality (CTQ) trees etc.), problem solving tools (FMEA, Plan Do Control Act (PDCA), root-cause analysis, 5 whys, cause-and-effect analysis, interrelationship diagrams, affinity diagrams, tree diagrams etc.), project management tools (PDCA, project charter, Gantt charts, PERT, SIPOC), creativity tools (brainstorming, Kano model), time management tools, communication tools and leadership tools etc. However, these types of detailed classifications for both nonstatistical and statistical tools go beyond scope of Six Sigma methodology and training. Classification of Six Sigma tools in literature is given in Table 4. [Insert Table 4 Here] 3.3.1. A better classification Finally, in order to build a necessary yet sufficient classification, considering both functionality and "qualitative and quantitative" distinction, a comprehensive classification can be built and proposed as represented in Table 5. The organization of the classification scheme is in conjunction with the previous studies in Table 4. However, in the proposed classification voice of customer (VOC) is located under idea generation tools, while VOC data collection is 15

located under data collection. VOC itself is to understand the customer needs which is the essence of Six Sigma, therefore we are regarding it as a creativity tool. Kano analysis helps organization of information of customer needs, therefore it is located under information organization tools category. Because critical to quality (CTQ) is to convert VOC into measurable metrics, CTQ is located at this category and at the border of qualitative and quantitative tools.

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[Insert Table 5 Here] 3.4. Which Tools When Another source of confusion during training of Six Sigma is the uncertainty of using which tools under which steps. In order to overcome these difficulties, starting from the earlier sources about Six Sigma, matrices which are matching the tools of Six Sigma with the DMAIC steps are presented in various type of publications. In Rath and Strong's Six Sigma Pocket Guide by Williams et al. (2003) which has been a popular source for years, this type of matrix table is provided where around 50 tools are paired with one or more steps of DMAIC. In Pyzdek and Keller (2003), the flow of the book and table of contents are a good reference to locate tools of Six Sigma within DMAIC process. In Hagemeyer et al. (2006), by the means of a case study, they tried to compare the steps associated with each tool as dictated in Six Sigma training with the steps where each tool is actually used in real case. Finally, it is emphasized that a tool may be used in more than one step or may even be used throughout the entire process. Considering the above discussion, it can be argued that the time of use of each tool must be so flexible that their use or implementation must be scheduled according to needs of each project, and the schedule of use of these tools must be dynamically adapted during the project in accordance with the progress of the project. Because of this reason, after providing a general overview and a road map of Six Sigma, some Six Sigma books or sources in the

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literature provide the tools in alphabetical order (Tague, 1995; Brassard et al., 2002). By building this type of structures for the books, the authors are implying that Six Sigma is a large set of tools such that you are always free to select and use the tools that you desire and need. However, as mentioned at the beginning of this section, this type of presentation makes it difficult to figure out the timeline of tools during Six Sigma projects at least for the people new in Six Sigma. At the beginning, only the steps which are characteristically associated

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with each tool must be mentioned in Six Sigma training to build a consistent picture of Six Sigma in the minds of prospective practitioners. Therefore, recent publications are very precisely providing the information about the time of usage for each tool. In Meran et al., (2013) each tool is routinely described with the titles "When", "Goal" and "Procedure". And, for every step of DMAIC, a very explicit road map is given to remove any confusion in Six Sigma Methodology. In the table provided in Williams et al. (2003), VOC is only matched with Define phase, while Control Chart is matched with Measure, Analysis, Improve and Control. From this table, it can be argued that VOC is confined with only Define step, but control charts almost appear at every level of project. Let us assume a case that the team members desire to ask their customers (i.e. the people receive their output as input) to prioritize the potential solutions that they propose against a root cause. In this example, the team members appear to collect a type of VOC data in "improve stage" which appears to violate the DMAIC flow. A brief review of flow of tools with respect to DMAIC steps is given in Table 6. In Tang et al. (2007) to introduce some extension tools in contrast to classical ones, an advanced table has been created where the phase of each tool is explained by matching each tool with the deliverables expected from each step of DMAIC. The contradiction mentioned above can be very simply overcome by generating such a table shown in Table 7 which is

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characteristically similar to the one presented in Tang et al. (2007). By looking this proposed sample table, a logically valid inference can be made as follow: VOC which mostly meets the deliverables of DEFINE phase can be characteristically regarded as 'a tool of Define phase', however, from the table, it is observed that it can also be used to "Prioritize Potential Solutions" which is a deliverable of Improve phase. In the table presented in Tang et al. (2007), the suitability of tools for different

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environments are also depicted by the means of different symbols within the boxes. Similarly, the frequency of a tool in meeting a specific deliverable can be also presented in this matrix table again by the means of different size or shape of symbols. When tools are ordered from left to right according to their time of usage in projects, the points in the boxes will be mostly located around the diagonal of the matrix (Table 7). Therefore we would like to name this important table as "Deliverables vs. Tools Diagonal Matrix". As the researchers share their experiences (such as what they are able to achieve by the means of which tools) in the form of this table, the readers can more quickly access the information and experiences related to tools of Six Sigma. [Insert Table 6 Here] [Insert Table 7 Here] 3.5. Emergence of Tools as A Critical Success Factor of Six Sigma In Garvin (1991), after declaring that Total Quality Management (TQM) does not provide a single recipe, it is mentioned that nevertheless Balridge Award winning companies that are successfully implementing TQM share some common properties which is listed as: senior management leadership, commitment to employee training, and systematically fostering continuous improvement. Therefore, this type of high level items which are leading to success in quality management are regarded as 'key success factors' or 'critical success factors' of quality management. Saraph et al. (1989) is one of the early studies that systematically 18

organizes and gives a list of the critical factors of quality management. In this article, eight critical factors are determined - one of which is 'training'. Under training category, two elements are described as: training in basic (e.g. histograms and control charts) and advanced (e.g. design of experiment and regression) statistical techniques. Of course, employee training leads to more effective use of some statistical or quality tools by employees, however, a high level item corresponding to 'effective use of quality management and statistical tools' are not

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directly established in these early studies. Ahire et al. (1996) is one of the early studies which raise "tools" to high level factors. In this study, 'SPC Usage' (considering all the statistical tools of SPC) is directly cited as a high level success factor of quality management. In Yusof and Aspinwall (1999), a table is provided in which previously established critical success factors of quality management are compared in terms of the high level items. In this table, among 10 generic critical factors, 'Tools and Techniques' has taken its place as a key success factor. With Antony and Banuelas (2002), the critical success factors of Six Sigma is established as a list which includes directly "Understanding tools and techniques within Six Sigma". By this publication, tools of Six Sigma explicitly emerged as critical success factors of Six Sigma. By the means of a literature review, Brun (2010) created a graph displaying a statistical overview of publications about critical success factors (CSF) of Six Sigma. In this graph, it can be seen that five publications out of eighteen are regarded "understanding tools of Six Sigma" as CSF of Six Sigma. In Laureani and Antony (2012), it is shown that seven articles out of 31 has regarded 'tools and technique' as CSF of Six Sigma. In Albliwi et al. (2014), from a different point of view, wrong selection of Six Sigma tools is regarded as Critical Failure Factors in Six Sigma. In Ismyrlis and Moschidis (2013), while summarizing 32 CSFs of Six Sigma as only 6 bullets, they preferred to keep "Utilization of quality-statistical tools and data analysis" as a major bullet. Their article is directly named as 'Six Sigma’s critical success factors and

19

toolbox'. Consequently, it can be concluded that there has been a change in the high level success factors from a previous emphasis on top management commitment or resource allocation to a new emphasis on training, understanding and utilization of quality-statistical tools and data analysis. This change will be also accelerated by the rise of new computer based technology which results in easier access or use of statistical analysis programs, more widespread use of advanced methods such as optimization and simulation which are all

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embedded in Six Sigma toolbox. A brief review of tools as CSF of Six Sigma is given in Table 8. [Insert Table 8 Here] 4. DISCUSSION: GAPS IN THE LITERATURE 4.1. Requirement for More Statistics about the use of Tools of Six Sigma As in discussed in section 3.2, there is both anecdotal and empirical studies which discuss the most used tools of Six Sigma. However, as it can be seen, all these conclusions are originated from a specific industry or from a limited region. In order to improve the reliability of statistics about the tools of Six Sigma, the sample population size can be increased by reaching as many as organizations worldwide which are members of international quality societies. Moreover, in addition to the most used tools, more importantly the most beneficial tools of Six Sigma must be investigated as in Antony et al. 2008. In other words, the tools of Six Sigma must be investigated two-dimensionally: the most used tools vs. the most beneficial tools. Therefore, the mismatch between the most used tools and the most beneficial tools must be statistically demonstrated to encourage the practitioners to gradually move towards the most beneficial ones. Another useful statistics about the tools can be comparison of the frequency of use of tools within different quality initiatives such as ISO 9001, TQM, Lean manufacturing and Six Sigma as in Souza et al. 2014. By the means of this type of data, it can be better illustrated

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that which tools are more associated with which quality initiatives. As discussed in section 3.2, Six sigma is a statistical fact oriented methodology, therefore Six Sigma projects are supposed to engage in statistical analysis more than other initiatives. However, anecdotal evidences are not sufficient to illustrate the realities about this situation. Only after the use of statistical analysis is proven to be more frequent in Six Sigma compared to other quality initiatives by the means of a comprehensive survey data, then it can be confidently mentioned

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that practical situations are in line with theoretical expectations. While classifying tools of Six Sigma based on their functionality as in section 3.3, it may be a better idea to classify these tool based on the type of projects. Because each different types of projects have very different aims and needs, the tools which are supposed to meet these different needs must be also different. Or at least, the manner of usage of tools must be modified for different projects. For example, the tools required for projects related to reduction in cycle time or lead time, the tools for market related projects and the tools for reduction of rework in engineering process must be all separately determined to provide an excellent guide for Six Sigma practitioners. In order to achieve this task, a theoretical framework which is based on a comprehensive practical observations must be built to create a basis for project type based selection of tools. 4.2. Effective Use Of Tools In the section 3.5, the importance of tools and techniques in Six Sigma are emphasized by showing that 'effective utilization of tools' is regarded as a CSF of Six Sigma. At this point it would be valuable to know what can be an obstacle in utilizing tools effectively, or what major factors are influencing effective use of Six Sigma tools. Basu (2009) explains the major factors leading to ineffective use of tools and techniques as: •

Inadequate Training

•

(Insufficient) Management Commitment or Resources

21

•

Employee Mindset

•

Poor application tools and techniques

And, the author lists the critical success factors influencing successful implementation

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of tools and techniques as: •

Top management commitment

•

Availability of resources

•

Well designed education and training program

•

Rigorous project management approach

It can be observed all these items are at the same time high level CSFs of Six Sigma. Except inadequate training as a negative factor (or oppositely well designed educationtraining program as a positive factor), all these factors cannot very directly affect the effective use tools. What is needed is to provide a set of CSFs or issues which can directly be related to use of tools and techniques under a scenario that both top management and employees are committed to practice Six Sigma in their company. As an example, a specific reason of failure of effective use of tools cited by Spring et al. (1998) is that employees perceive some basic tools as too simplistic and not appropriate for the process. Finally, a couple of proposals for CSFs of effective use of Six Sigma tools can be a listed as follows: •

Total hours of Six Sigma training

•

Existence of an expert in statistics within the company

•

Accumulating experience by frequent use of tools via continuous or successive implementation of Six Sigma projects

•

Opportunity to continuously consult to Six Sigma consulting firms

•

Having a well-established Six Sigma role structure etc.

As a future research direction, because effective use of Six Sigma tools is highly critical for the success of Six Sigma implementations, all these proposals or parameters 22

should be investigated by empirical studies to define low-level factors of effective use of Six Sigma. 5. CONCLUSION Tools support a rational analysis in problem solving. From a managerial perspective, when Six sigma teams settle down to solve their problems via DMAIC methodology, they often struggle with identifying the most appropriate tools to use and when to use them (Meran et al.,

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2013). Six Sigma methodology is a flow of application of tools, therefore a strategic filter to select the most proper tools will encourage practitioners to follow the best flow throughout their projects. Of course, as the team members earn their own experiences about Six Sigma tools, they will build their own filtering strategy to select the tools of Six Sigma which they need. However, this type of experience cannot be easily obtained for a reasonable period of time. Therefore, practice-oriented guides are necessary that share the ideas and experiences about tried-and-tested tools originally from previous practitioners. Another question in minds about the tools is the effectiveness rating of each tool. Only a few studies mention systematically about the effectiveness of each tool from the eyes of industrial members (Hagemeyer et al., 2006). However, it is quite obvious that this type of information and experiences are so valuable for practitioners who are new in Six Sigma. Therefore, what actually needed is strong statistics regarding to the use of tools and techniques in Six Sigma. Our study has addressed some of these statistics based on the literature, and build some valuable insights into the realities about use of tools of Six Sigma. It is certain that by the means of structured education and training, Six Sigma tools can be learned effectively by prospective practitioners. However, when it is time to apply these tools in the real world, receiving a couple hints would be valuable instead of struggling within the time consuming cycle of try-and-fail. What we have tried to do in this study is to collect these hints together as much as possible. From this perspective, our study provides a

23

comprehensive insight into Six Sigma Toolbox by reviewing the most used tools, classification of tools, flow of tools with respect to DMAIC steps, tools as Critical Success Factors and reasons of ineffective use of tools. By doing so we examined more closely the research that was published specifically under the category of Six Sigma toolbox. Also pointing out the gaps in the literature, the future research directions are provided to build better understanding of the Six Sigma toolbox.

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In the literature, one of the issue about TQM is mentioned that it provides practitioners with a vast set of tools with no clear framework for using them effectively (Motwani et al. 2004). On the other hand, what makes Six sigma differ from other quality management practices is to provide a clearly defined framework for using specially defined subset of tools (instead of vast set of tools) within DMAIC methodology (Motwani et al. 2004). Therefore, a well-defined framework for the use of tools is one of the significant expectation of practitioners from Six Sigma methodology. Consequently, Six Sigma methodology can be improved by academic environments by paying more attention to Six Sigma toolbox and by investigating the realities about the use of tools of Six Sigma by the means of empirical studies. 6. LIMITATIONS: In He and Goh (2015), it has been stated that Six Sigma toolkit is quite open in nature. Because Six Sigma can be integrated with many management theory and methods such as lean production, quality management systems, performance excellence model, supply chain management, theory of constraints, it is difficult to limit the scope of Six Sigma tools (He and Goh 2015). While it is possible to define a set of tools which can be attributed to belong to Six Sigma, sometimes it is not possible to discriminate the tools as belonging to a specific discipline (see Kumar et al. 2006 which includes a diagram which can only partially separate the interrelated tools of Lean and Six Sigma). Therefore, in order not to diverge from the main

24

point, the scope of this research is limited by the tools associated with DMAIC methodology. To give an example, the tools of design for Six Sigma (DFSS) is excluded from the main discussion. Consequently, recognizing the importance of investigating the facts about the Six Sigma toolbox, future researches can focus on more thorough point of view to provide Six

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Sigma practitioners with pragmatic evidences about Six Sigma methodology.

ACKNOWLEDGEMENTS This project is funded by TUBITAK (Scientific and Technological Research Council of Turkey). Project Number: 115C079.

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Antony, J. (2006). Six sigma for service processes. Business Process Management Journal, 12(2), 234-248. Antony, J., Jiju Antony, F., Kumar, M., & Rae Cho, B. (2007). Six sigma in service organisations: Benefits, challenges and difficulties, common myths, empirical observations and success factors. International Journal of Quality & Reliability Management, 24(3), 294311.

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Cullen, J., O'Connor, M., & Mangan, J. (2004). Matching management tools and techniques with management challenges. Strategy & Leadership, 32(3), 27-30. Curry, A., & Kadasah, N. (2002). Focusing on key elements of TQM-evaluation for sustainability. The TQM magazine, 14(4), 207-216. Erginel, N. (2010). Are TQM principles implemented by large companies and SMEs similar in Turkiye?. Anadolu University Journal Of Science And Technology, 11(2), 125-140. Farris, G. F., Hartz, C. A., Krishnamurthy, K., & McIlvaine, B. (2003). Web-enabled innovation in new product development. Research Technology Management, 46(6), 24.

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Firka, D. (2010). Six sigma: an evolutionary analysis through case studies. The TQM Journal, 22(4), 423-434. Garvin, D. A. (1991). How the Baldrige Award Really Works. Harvard Business Review. George, M., Rowlands, D., Price, M., & Maxey, J. (2005). The lean six sigma pocket toolbook. The McGraw-Hill. Giles, T., & Cormican, K. (2014). Best practice project management: an analysis of the front end of the innovation process in the medical technology industry. International Journal of Information Systems and Project Management, 2(3), 5-20. Goicoechea, I., & Fenollera, M. (2012). Quality management in the automotive industry. In B. Katalinic (Ed.), DAAAM International Scientific Book, 619-632. Hagemeyer, C., Gershenson, J. K., & Johnson, D. M. (2006). Classification and application of problem solving quality tools: a manufacturing case study. The TQM Magazine, 18(5), 455483. Hahn, G.H., Hill, W., Hoerl, R.W., Zinkgraf, S.A., (1999). The impact of six sigma improvement: a glimpse into the future of statistics. The American Statistician, 53, 1-8. Hahn, G. J., Doganaksoy, N., & Hoerl, R. (2000). The evolution of six sigma. Quality Engineering, 12(3), 317-326. He, Z., & Goh, T. N. (2015). Enhancing the Future Impact of Six Sigma Management. Quality Technology And Quantitative Management, 12(1), 83-92. Hoerl, R.W., Snee, R.D., (2002). Statistical Thinking: Improving Business Performance. San Jose: Duxbury Press/Thompson Learning. Ismyrlis, V., & Moschidis, O. (2013). Six sigma's critical success factors and toolbox. International Journal of Lean Six Sigma, 4(2), 108-117. Kwak, Y. H., & Anbari, F. T. (2006). Benefits, obstacles, and future of six sigma approach. Technovation, 26(5), 708-715.

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Laureani, A., & Antony, J. (2012). Critical success factors for the effective implementation of lean sigma: Results from an empirical study and agenda for future research. International Journal of Lean Six Sigma, 3(4), 274-283. Linderman, K., Schroeder, R. G., & Choo, A. S. (2006). Six sigma: the role of goals in improvement teams. Journal of Operations Management, 24(6), 779-790. Machado, V. C., & Leitner, U. (2010). Lean tools and lean transformation process in health care. International Journal of Management Science and Engineering Management, 5(5), 383392.

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Mahanti, R., & Antony, J. (2009). Six Sigma in the Indian software industry: some observations and results from a pilot survey. The TQM Journal, 21(6), 549-564. Meran, R., John, A., Roenpage, O., & Staudter, C. (2013). Six Sigma+ Lean Toolset: Mindset for Successful Implementation of Improvement Projects. Berlin: Springer Science & Business Media. Miguel, P. A., & Marcos Andrietta, J. (2010). Outcomes from a descriptive survey of Six Sigma management practices in Brazil. International Journal of Lean Six Sigma, 1(4), 358377. Miguel, P. A., Satolo, E., Marcos Andrietta, J., & Araujo Calarge, F. (2012). Benchmarking the use of tools and techniques in the six sigma programme based on a survey conducted in a developing country. Benchmarking: an International Journal, 19(6), 690-708. Montgomery, D.C., (2001). Introduction to Statistical Quality Control. New York, NY: Wiley. 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, 16(4), 273-283. Nguenang, L. B. (2010). An approach to six sigma implementation in South African enterprises, Doctoral dissertation, Cape Peninsula University of Technology. Nonthaleerak, P., & Hendry, L. (2008). Exploring the six sigma phenomenon using multiple case study evidence. International Journal of Operations & Production Management, 28(3), 279-303. Pande, P. S., Holpp, L., & Pande, P. (2002). What is six sigma?. New York, NY: McGrawHill. Pulakanam, V., & Voges, K. E. (2010). Adoption of Six Sigma: review of empirical research. International Review of Business Research Papers, 6(5), 149-163. Raisinghani, M. S., Ette, H., Pierce, R., Cannon, G., & Daripaly, P. (2005). Six Sigma: concepts, tools, and applications. Industrial management & Data systems, 105(4), 491-505.

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Ricondo, I., & Viles, E. (2005). Six Sigma and its link to TQM, BPR, lean and the learning organisation. International Journal of Six Sigma and Competitive Advantage, 1(3), 323-354. Pyzdek, T., & Keller, P. A. (2003). The Six Sigma Handbook. New York, NY: McGraw-Hill. Saraph, J. V., Benson, P. G., & Schroeder, R. G. (1989). An instrument for measuring the critical factors of quality. Decision sciences, 20(4), 810-829. Scheuermann, L., Zhu, Z., & Scheuermann, S. B. (1997). TQM success efforts: use more quantitative or qualitative tools?. Industrial Management & Data Systems, 97(7), 264-270.

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Selma, M. R. B., Abdelghani, E., & Rajhi, M. T. (2013). Risk management tools practiced in Tunisian Commercial Banks. Studies in Business and Economics, 8(1), 55-78. Snee, R. D. (2005). Leading business improvement: A new role for statisticians and quality professionals. Quality and Reliability Engineering International, 21(3), 235-242. Sousa, S. D., Aspinwall, E., Sampaio, P. A., & Rodrigues, A. G. (2005). Performance measures and quality tools in Portuguese small and medium enterprises: survey results. Total Quality Management and Business Excellence, 16(2), 277-307. Souza, J. P. E., Alves, J. M., & Silva, M. B. (2014). Quality in the aerospace supply chain: investigation about the main characteristics, International Review of Mechanical Engineering, 8(5), 893-900. Spring, M., McQuater, R., Swift, K., Dale, B., & Booker, J. (1998). The use of quality tools and techniques in product introduction: an assessment methodology. The TQM Magazine, 10(1), 45-50. Tague, N. R. (1995). The Quality Toolbox. Milwaukee, WI: ASQ Quality Press. Tang, L. C., Goh, T. N., Lam, S. W., & Zhang, C. W. (2007). Fortification of six sigma: expanding the DMAIC toolset. Quality and Reliability Engineering International, 23(1), 3-18. Tari, J.J. (2005). Components of successful total quality management. The TQM magazine, 17(2), 182-194. Voehl, F., Harrington, H. J., Mignosa, C., & Charron, R. (2013). The lean six sigma black belt handbook: tools and methods for process acceleration. Boca Raton, FL: CRC Press. Williams, M.A., Bertels, T. & Dershin, H. (2003). Rath and Strong’s Six Sigma Pocket Guide. Lexington, MA: Rath and Strong Management Consultants. Yusof, S. R. M., & Aspinwall, E. (1999). Critical success factors for total quality management implementation in small and medium enterprises. Total Quality Management, 10(4-5), 803809. Zugelder, T. J. (2012). Lean Six Sigma Literature: A Review and Agenda for Future Research, Doctoral dissertation, The Ohio State University.

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Table 1. Keyword Search Results Search Results within NCSU library database Total

-

Journal Papers (including non-peer reviewed) 13

32

61

65

158

Six Sigma + techniques

21

36

34

91

Six Sigma + toolbox

3

-

4

7

Classification + tools + Six Sigma

-

-

-

-

Most used + tools + Six Sigma

-

-

-

-

Frequently used + tools + Six Sigma

-

-

-

-

Tool classification + Six Sigma

-

-

-

-

DMAIC + tools

1

-

4

5

Flow + tools + Six Sigma

-

-

-

-

Tools + Critical Success Factors + Six

-

-

-

-

-

-

-

-

Keywords (Combination of words in the title)

Journal Papers (peerreviewed) 10

Books

Six Sigma + tools

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Literature review + Six Sigma

23

Sigma Ineffective use + tools + Six Sigma

Search Results within Google Scholar Keywords "most used tools" + "Six Sigma"

Total number of Retrieved Articles 66

Relevant Articles having an exact content match 4

"most commonly used tools" + "Six Sigma"

136

12

"most frequently used tools" + "Six Sigma"

49

3

"classification of tools" + "Six Sigma"

20

3

"categorization of tools" + "Six Sigma"

4

-

Table 2. Some Eliminated Resources Due to Context Mismatch Reference

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Banuelas et al. (2006)

The context of the resource with regard to "most used tools" The most used tools in Prioritization of Six sigma projects.

Farris et al. (2003)

The most used tools as well as the most useful tools in Knowledge Management.

Cullen et al. (2004)

The most used Management Tools and Techniques

Machado & Leitner (2013)

The most used Lean tools

Selma et al. (2013)

The most used tools of Operational Risk Management

Antunes et al. (2009), Sousa et al. (2005) Goicoechea & Fenollera (2012) Giles & Cormican (2014)

The most used Quality tools

Crema & Verbano (2015)

The most used tools in Clinical risk management

The most used Quality tools in Automative industry The most used tools in Front End of the innovation

Erginel, 2010

Tari, 2005

Curry and Kadasah, 2002 Bayazit, 2003

Antony and Kumar, 2012 Miguel et al., 2012 (also in Miguel and Andrietta 2010)

Nguenang, 2010

Antony and Desai, 2009

The Reference Antony and Banuelas, 2002 Antony, 2004 (also in Antony et. al. 2007) Antony and Fergusson, 2004 Antony et al., 2005 (also in Antony et al., 2008) Mahanti and Antony (2009)

A questionnaire with 83 firms in Saudi Arabia A questionnaire with 100 companies in Turkey A questionnaire with 106 companies in Spain A questionnaire with 109 SMEs and large companies in Turkey

A questionnaire with 30 firms in South Africa A questionnaire with 78 companies in Scotland A questionnaire with 78 companies in Brazil

A questionnaire with 20 software companies in India. A questionnaire with 43 companies in India

Research Methodology A questionnaire with 45 companies in the UK A questionnaire with 23 service companies in the UK A questionnaire with 15 software companies A questionnaire with 60 SMEs in UK

For both Large Companies and SMEs: brain storming, Pareto analysis and control charts, FMEA

SPC; control charts; fishbone diagram; gap analysis; inspection; capability maturity model; regression; process mapping; QFD; FMEA; PCA. histogram, run charts, SPC charts, PCA, brainstorming, cause and effect analysis, Pareto analysis, process mapping and project charter, FMEA brainstorming, cause and effect diagram, Pareto diagram, check sheet Benchmarking, Brainstorming, Patient Feedback, Process Mapping, Root Cause Analysis data collection, histogram, Pareto, brainstorming, controls charts, capability measures, flow chart, process mapping, measurement system evaluation, and SPC TQM check lists, flow charts and brainstorming, sampling inspection and control charts Pareto charts, SPC, cause-and-effect diagrams, and process charts graphics, SPC, flow chart, histograms

Six Sigma Most Used Tools cause and effect analysis, Pareto analysis, control charts, run charts brainstorming; process mapping; affinity diagrams; root cause analysis; control charts; benchmarking; Pareto analysis; change management tools data flow diagram; gap analysis; process mapping; voice of the customer analysis. process mapping, histogram, cause and effect analysis, FMEA and process capability studies

For both Large Companies and SMEs: scatter diagram, box plot, QFD, regression analysis

QFD, Mistake Proofing, SMED, FMEA, non-parametric tests. OCAP, PDPC, evolutionary operation, operational testing, PERT/CPM, market testing, stakeholder analysis, FTA and the accelerated life test

non-parametric tests (e.g. Mann-Whitney test), affinity diagram, project charter, SIPOC, quality costing analysis, run charts, MSA and QFD service blueprinting; team software process; personal software process; simulation; agile technologies; objectivesprinciples-attributes. non-parametric tests (Mann-Whitney Test), Taguchi Methods, DOE, affinity diagrams, force field analysis and matrix analysis, QFD

Least Used Tools DOE, Taguchi methods, QFD, FMEA, criticality analysis, 5S, Poka-Yoke, SPC QFD; Hoshin-Kanri (policy deployment); Kano Model; design of experiments; SPC, Poka-Yoke (mistake proofing)

Table 3. The Research Studies Mentioning the Most Frequently Used Tools of Six Sigma as well as TQM

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Table 4. Classification of Six Sigma Tools in the Literature Source

Classification Scheme

Tools

Project planning and implementing tools

Scorecard, Checklist, Flowchart, Force-field Analysis, Gantt Chart, Operational definitions, PDCA, Project charter, Stakeholder analysis, Storyboard, Tree diagram. Affinity Diagram, Brainstorming Cause-effect matrix, COPQ analysis, CTQ analysis and CTQ tree, House of quality, Mistake proofing, Relations diagram, SIPOC, Value-added analysis, Work flow diagram Box plot, Control charts, Correlation, Cycle time chart, DOE, Histogram, Normal probability plot, Process capability, Radar chart, Regression, Rub chart, Sampling, Scatter, Stratification, Survey, VOC table FMEA, Fishbone diagram, Why-why diagram Criteria Filtering, Multivoting, Prioritization matrix Brainstorming, Affinity diagramming, Multivoting, Structure tree (tree diagram), High level process map (SIPOC), Flowchart, Cause-and-effect (Fishbone) diagrams) Sampling, operational definitions, VOC methods, checksheets and spreadsheets, MSA Process-flow analysis, Value and non-value added analysis, charts and Graphs (Pareto chart, histogram (frequency plot), Run(trend) chart, Scatter plot (correlation diagram) Tests of statistical significance (chi-square, t-tests, ANOVA), Correlation and Regression, DOE Project management (Gantt chart), FMEA, Stakeholder analysis, Force field diagram, Process documentation, Balanced score cards and Process dashboards Brainstorming, Affinity Diagram, Multivoting SIPOC, Flowchart, Spaghetti (work-flow) diagram, Swimlane flowcharts, Value stream maps, Takt time charts Collecting VOC, Interviews, Surveys, Kano Analysis, Critical to Quality Data Collection planning, Operational definitions, Checksheets, Sampling, MSA Mean, Range, Variance, Boxplots, Histogram, Normal Distributions Run charts, Control Charts Pareto Charts, 5 whys, Cause-effect Diagrams, Scatter plots, Hypothesis testing, Confidence Interval, t-tests, Correlation, Regression, ANOVA, Chi-Square, DOE Solution Selection Matrix, Pairwise ranking, Cost Evaluation, Pugh Matrix, FMEA, Pilot Testing Fishbone diagram, Pareto chart, Scatter diagram

Idea creation tools Process analysis tools Tague 1995

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Data collection and analysis tools

Cause analysis tools Evaluation and decision making tools Tools for generating ideas and organizing information; Tools for data gathering Pande et al. 2002

Tools for process and data analysis Tools for statistical analysis Tools for implementation and process management Tools for working with ideas Process Flow Tool VOC Data Collection Tools

George et al. 2005

Descriptive Statistic Tools Variation Analysis Tools Identifying and Verifying Causes Tools Selecting and Testing Solution Tools

Chakraborty and Tan 2012

Cause analysis tools Data collection and analysis tools Evaluation and decision making tools Idea creations tools

Scheuermann et al. 1997

Process analysis tools Qualitative tools Quantitative tools

Check sheet, Control chart, Design of experiment, Histogram, Scatter diagram, Stratification, Survey Decision matrix, Multi-voting Affinity diagram, Benchmarking, Brainstorming, Nominal group technique FMEA, Mistake-proofing Flow charts, Cause-and-effect diagrams, Multi-voting, Affinity diagram, Process action teams, Brainstorming, Election grids, Task lists. PDCA, Control charts, Scatter diagrams, Pareto charts, Sampling, Run charts, Histograms.

Table 5. Proposed Classification of Six Sigma Tools by Functionality and QualitativeQuantitative Distinction CLASSIFICATION OF SIX SIGMA TOOLS Qualitative Tools Non-statistical Tools

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Description Project management tools

Creativity tools Idea Generation Tools Information Organization Tools

Quantitative Tools

Tools Project charter Gantt charts Stake Holder Analysis Communication Plan Team management Commitment Scale Mat. Project Documentation Brainstorming, VOC Affinity diagrams Tree diagrams Kano analysis

Tools

Description

CTQ (Critical to Quality) Tree

Process Flow Tools

Identifying potential causes tools

Decision making tools

Problem Solving tools

Problem Solving (Lean tools)

DATA COLLECTION TOOLS VOC data collection Sampling Check Sheets MSA Data collection Plan Operational Definitions PROCESS and DATA ANALYSIS TOOLS Flowchart Box plots SIPOC Histograms Spaghetti diagram Mean-Mode-Median Swim-lane flowcharts Range-Variance Value stream maps Run Charts Takt Time Graph Control Charts IDENTIFYING CAUSES TOOLS Root-cause analysis, Stratification, 5 whys, Pareto Charts cause-and-effect analysis Scatter plots (fishbone), Hypothesis testing interrelationship diagram Confidence Interval tree diagram t-tests, Correlation Regression, ANOVA Chi-Square, DOE IMPLEMENTATION TOOLS Multi voting Prioritization Matrix Pugh Matrix, Cost and Risk Analysis Activity Network Diagram FMEA, Pilot Study, PDCA Poka-Yoke, 5S, MUDA, Pull systems, Cell Optim.

Descriptive Statistics Tools

Trend Analysis Tools

Statistical Tools

Decision making tools

Table 6. Brief Review of Flow of Tools With Respect to DMAIC Steps Williams et al., 2003 D Affinity diagram, Project charter, CTQ, Flow diagrams, Rolled throughput yield, SIPOC, Stakeholder analysis, VOC M Control charts, Data collection forms, Data collection plan, Flow diagrams, Frequency plots, FMEA, Gage R&R, Kano A I C

model, Pareto charts, Prioritization chart, Process capability, Process sigma, Sampling, Stratification, Stratified frequency plots Affinity diagram, Brainstorming, Cause and effect diagram, Control charts, Data collection forms, DOE, Flow diagrams, Frequency plots, Hypothesis tests, Regression, Pareto, Scatter, Sampling, Stratification, Stratified frequency plots Brainstorming, Consensus, Control charts, Data collection forms, Data collection plans, DOE, Flow diagrams, Frequency plots, FMEA, Pareto charts, Prioritization chart, Process capability, Process sigma, Sampling, Stakeholder analysis, Stratification Standardization

Pyzdek and Keller, 2003 Downloaded by University of Liverpool At 06:12 19 September 2016 (PT)

D

Problem Solving tools, Process mapping, Check sheets, Pareto analysis, Cause-and-effect-diagrams, 7M tools (affinity diagrams, activity network diagram, interrelationship digraph etc.) Probability distributions, Hypothesis testing, Statistical inference, SPC, MSA

M A Knowledge discovery tools, Run charts, Descriptive statistics, Histograms, SIPOC, SPC, Run charts etc. I C L

Process capability analysis, Statistical Analysis of Cause and Effect, Testing common assumptions, Regression and correlation analysis, Analysis of categorical data (chi-square test etc.), Non-parametric methods -Basic graphical tools, FMEA, Hypothesis testing, Confidence intervals, ANOVA, Correlation and regression analysis, Reliability models and measures, Cost analysis, Forecasting, Basic queuing systems -Simulation and modeling Project management tools and techniques, Gantt charts, PERT-CPM-type project management systems etc., Risk assessment, Reliability and safety analysis, FMEA, DOE Muda, VSM, Takt time, Spaghetti charts, 5S, Pull systems, Kaizen, Constraint management tools

Hagemeyer et al., 2006 D M A I C

Project scope contract, Process mapping, CT matrix

D

Project selection, Probabilistic risk thinking and strategic planning, Decision analysis, Process mapping, Project management tools, Mathematical programming techniques for resource allocation and project selection QFD and Kano analysis, Gap analysis, Sampling (data quantity and data quality), Measurement system analysis, SPC Part I (concepts, implications of instability), Capability analysis, Monte Carlo simulation and statistical distributions Basic graphical improvement tools, FMEA, Hypothesis testing , Confidence intervals, ANOVA, Correlation and regression analysis, Reliability models and measures, Cost analysis, Forecasting, Basic queuing systems, Simulation and modeling DOE (factorial, fractional factorial blocking, nested and RSM) and blocking), Robust design, Optimization and control of queues, Mathematical programming techniques, Heuristics, Sensitivity analysis Mistake proofing, Validation testing, Control plans, SPC Part II (control charts), Basic control charts

Process mapping, Cause and effect, FMEA, Gage R&R, Graphical techniques Process mapping, Graphical technique, Multi-vari studies, Hypothesis testing, Correlation and regression Process mapping, DOE, Simulation, Optimization Control plans, Statistical process control, Gage control plan, Preventive maintenance, Poka yoke/Mistake proofing

Tang, 2007 M A I C

Meran et al., 2013 D M A I C

Project Charter, SIPOC, Project Management, Time-Resource-Budget Planning, Risk and Stakeholder Management Project Communication, Customer Needs Table, Kano Model, CTQ Operational Definition, Sampling Strategy, Measurement System Analysis (MSA), Data Collection Plan, Understand Variation, Visual display, Location and Spread Parameters, Process Performance, Process Capability and Stability Cause and Effect Diagram, FMEA, Spaghetti, Value Stream Map, Data stratification, Confidence Intervals, Hypothesis Tests, ANOVA, Correlation, Regression, DOE 5 S, Poka Yoke, Workplace Layout, SMED, TPM, Generic and Replenishment Pull System, Pugh Matrix, Pilot Study Process Documentation, Dashboards, Audits

Table 7. Deliverables-Tools Diagonal Matrix (developed based on Tang et al. (2007)) Tools of Define - - - ->

- - -> Tools of Control Story Board

Histogram

VOC

Deliverables.

Pugh Matrix

Tools

Identify customer needs

•

•

Measure

• • •

Analysis Improve Control

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Define

• • •

• • • •

• •

• •

• • • • •

• •

• • • • •

Prioritize Potential Solutions

•

•

• •

•

•

•

•

• •

• •

• • •

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Table 8. Tools As A Critical Success Factor (CSF) Of Six Sigma Publication

Number of CSFs

CSFs which are related to 'Tools and Techniques'

Saraph et al. 1989

8

Ahire et al. 1996

12

Yusof and Aspinwall 1999 Antony and Banuelas 2002 Brun 2011

10

Under Training: Training basic and advanced statistical tools Benchmarking SPC Usage Improvement Tools and Techniques Understanding tools and techniques within six sigma Understanding tools and techniques within six sigma

12

Laureani and Antony 2012

19

Tools and techniques

Ismyrlis and Moschidis 2013

6

Utilization of quality-statistical tools and data analysis

Albliwi et al. 2014

34

-wrong selection of Six Sigma tools -narrow view of Six Sigma as a set of tools

Description

Out of 18, 5 articles cited 'Tools and Techniques of Six Sigma' as CSF Out of 31, 7 articles cited 'Tools and Techniques of Six Sigma' as CSF The article is directly named as 'Six Sigma’s critical success factors and toolbox'