K.MuralidharanSix Sigma for Organizational ExcellenceA Statistical ApproachSix Sigma for Organizational ExcellenceK. MuralidharanSix Sigma for OrganizationalExcellenceA Statistical Approach1 3K. MuralidharanDepartment of StatisticsFaculty of ScienceM. S. University of BarodaVadodara, GujaratIndiaISBN 978-81-322-2324-5 ISBN 978-81-322-2325-2 (eBook)DOI 10.1007/978-81-322-2325-2Library of Congress Control Number: 2015932236Springer New Delhi Heidelberg New York Dordrecht London Springer India 2015This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or partof thematerial isconcerned, specicallytherightsof translation, reprinting, reuseof illustrations,recitation, broadcasting, reproductiononmicrolmsorinanyotherphysical way, andtransmissionor information storage and retrieval, electronic adaptation, computer software, or by similar ordissimilar methodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in thispublicationdoesnotimply,evenintheabsenceofaspecicstatement,thatsuchnamesareexemptfrom the relevant protective laws and regulations and therefore free for general use.Thepublisher, theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbookarebelievedtobetrueandaccurateat thedateof publication. Neither thepublishernor theauthors or theeditors giveawarranty, express or implied, withrespect tothematerial containedherein or for any errors or omissions that may have been made.Printed on acid-free paperSpringer (India) Pvt. Ltd. is part of Springer Science+Business Media (www.springer.com)PrefaceOrganizations run successful business only when they provide satisfaction toconsumers. Competitiveness in quality is not only central to protability, but alsocrucial tobusinesssurvival. Consumershouldnot berequiredtomakeachoicebetweenpriceandqualityof products. Manufacturingandserviceorganizationsexist if they learn how to manage quality. In todays tough and challenging businessenvironment, the development andimplementationof a comprehensive qualitypolicyis not merelydesirable, it is essential. Six Sigmais a business processimprovementtool to achieve customersatisfactionthrough a systematic problem-solving approach. It is uniquely driven by close understanding of customerrequirements and reinventing business processes. It facilitates people excellence aswellastechnicalexcellenceintermsofcreativity,collaboration, communication,dedicationandabove all increases the accountabilityof what one does inanorganization.The Six Sigma philosophy works under ave-phase improvement cycle, calledDMAIC, where D for dene, M for measure, A for analysis, I for improvement andC for control. It can apply to both process improvement and product improvementor even design redesign efforts. A Six Sigma initiative includes enterprise resourceplanning (ERP), e-commerce and services, lean manufacturing, customer relation-ship management systems, strategic business partnerships, knowledge management,activity-based management, just-in-time inventory and globalization. Organiza-tional excellenceis aresult of continuous improvement, whichcanattainonlythrough systematic reduction of defects and variations in the process activities. Herecomes the importance of Six Sigma methodology.Who Will Read?Thisbookservesthreemainpurposes: rst, anacademicbookfor studentsandteachers;second,thisbookcanbeusedasareferencematerialforengineersandmanagersworkingasSixSigmaprofessionalsandBlackBelttrainers;third,thisvbook could be a user manual for practitioners and project consultants. The emphasisis laidonunderstandingandapplyingthe concepts of qualitythroughprojectmanagement and technical analysis by using statistical methods. The contents areprepared in a ready-to-use form with continuity established for each phases of SixSigmaproject. Thiswill helppractitionerstoimplement theSixSigmaprojectswithoutanyhurdles. ThreemostimportantaspectsofSixSigmaprojectSigmaestimation, sample size calculation and Sigma-level estimationare separatelytreatedindifferentchapters.Necessarytables,graphs,descriptionsandchecklistsareprovidedtoeasethereferencingof tools andtechniques. Theconcepts arecritically assessed, reasoned and explained to enable their uses in managerialdecision making. The objectives of each chapter and its continuity with subsequentchapters arealsoclearlyestablishedfor asmoothreading. Charts andplots, anumber of worked-out examples, case studies and necessary tables are provided forbetter understanding of the concepts.Studentsofundergraduate, postgraduateandresearchstudentscanmakeopti-mum use of the integrated concepts of quality engineering and management tools ofstatistics. The science of Six Sigma project management, integrated through engi-neering concepts, is explained through statistical tools and that is the uniqueness ofthis book. The book could also serve as a concise book for Six Sigma Green Belt,Black Belt and Master Black Belt training.InspirationThe content is basedon the authors own teaching experience, lecture notes,researchpublications, privatecommunications, bookreferences, articlecitationsandtrainingandconsultingmaterials. Thecontent ishighlyinspiredwithsomeavailablebooks: TheSixSigmaWaybyPeter S. Pandeet al. (2003), JuransQualityPlanningandAnalysisfor EnterpriseQualitybyFrankM. Grynaet al.(2008), Lean Six Sigma Statistics by Alastair Muir (2005), The Certied Six SigmaBlack Belt Handbook by T.M. Kubiak and Donald W. Benbow (2009), Introduc-tion to Statistical Quality Control by Douglas C. Montgomery (2009), and Statis-tical Process Control byJohnS. Oakland(2012). The author has consultedanumber of other books on Six Sigma, lean, management, engineering and generalstatistical books for integrating the things, as required by Six Sigma professionals.About the bookThis book integrates three main disciplines: Science, Engineering and Management.The authorhas tried to maintain a balance of these threedisciplinesfrom a prac-titionerspoint of view. Chapter 1islikeanintroductiontovariousSixSigmaconcepts practiced by professionals and organizations, globally. Variousvi Prefaceperceptions and their implementation styles are critically examined in this chapter.Chapter 2 details the importance of Six Sigma project management concepts. Thenecessity of model-based projects is statistically emphasized. Apart from this, theimportance of quantitative project management and its risk assessment and criticalevaluationarealsodiscussedinthis chapter. Theimportanceof process-basedprojects and models are included in Chap. 3. This is followed by the understandingof theprocessvariation, whichisanessential part of aSixSigmaproject. Thesourcesof identifyingvariationandpossibleidenticationof variationsaredis-cussed in Chap. 4. Since Sigma is being considered as a measure of variation, theestimation of Sigma is a vital issue in a statistical study. This is considered in detailinChap. 5. Anumber of methodsof estimationof Sigmaisconsideredinthechapter. Chapter 6 details one of the important issues of project management, andthat isthesamplesizedetermination. Fromapractitionerspoint ofview, manysimple and easy-to-implement methods of sample size calculations are presented inthe chapter. Chapters 711 discuss the Six Sigma philosophy, systematically,detailing with the necessary tools and techniques of statistics to execute a project.The management quality improvement topics covered in these phases are SIPOC,voice of customer, value streammapping, brainstorming, root-cause analysis,failure-mode effect analysis, sevenqualitytools, Kaizen, 5S, designedfor SixSigma,qualityfunctiondeployment, understandingofdefectperunit(DPU)anddefect per millionopportunities (DPMO), Sigma-level estimation, cost of poorquality, etc.Statistical topicsincludedescriptivestatistics, thebasicnotionsonprobabilityandprobabilitydistributions, point andinterval estimationof parameters, para-metric and nonparametric testing, correlation and regression techniques, design ofexperimentsincludingfactorial experiments, control charts, etc. Acarehasbeentaken to show every method in a simple and practical way without involving anyrigorous theoretical steps involved. The SQC/SPC part of the project managementisgiventhemaximumemphasis, astheynaturallybecometheessential toolstoimprove and control the phase of the philosophy. Most of the tools and techniquesareexplainedthroughnumericalandillustrativeexamples.TheperformanceofaSix Sigma project is evaluated through its Sigma level. The understanding of DPU/DPMOand short-termand long-termvariability of a process, etc., are therequirements for the Sigma-level estimation. This is carried out in Chap. 12. Onecanalsorefertothischapterinthebeginningoftheactualprojectexecutionforsettingupthegoalandcanbeusedtobaselinetheperformanceevaluation.Thischapter will be handy for those involved with project evaluation and target setting atany time during the project.The methods forcontinuousimprovement ispresentedin Chap. 13,where theauthorhasdiscussedvariousqualityimprovement programsofferedbyDeming,Juran,Feigenbaum,Crosby, Ishikawa, Taguchi,etc.Chapter14offerstheimpor-tanceofSixSigmamarketing,whichisagrowing areaofresearchin SixSigmaphilosophy. A Six Sigma marketing is a fact-based data-driven disciplined approachto growing market share by providing targeted product/markets with superior value.VariousissuesassociatedwithSixSigmamarketing, likestrategic, tactical, andPreface viioperational processesofmarketing, arediscussedinthechapter. ThechapteronGreenSixSigmaemphasizestheimportanceof SixSigmaprojectsfromasus-tainablebusinesspractices. GreenSixSigmaisnothingbut thequalitativeandquantitative assessment of the direct andeventual environmental effects of allprocessesandproductsof anorganization. Theactivitiesinvolvethesystematicusageofinfrastructureandmanpower, optimumuseoftechnologyandaccount-ability of sustainable business practices. The benets of Green Six Sigma are alsodetailed in the chapter.The pros and cons of Six Sigma are presented in Chap. 16. A detailed discussionon advantages and disadvantage; various limitations, dos and donts of Six Sigmaare also discussed in the chapter. The concern about the future of Six Sigma is alsogivenat theendofthechapter. Chapter17isallottedtothediscussionofcasestudies.Apart from this, a separate session on Relevance for Managers is also added atthe end of each chapter to increase the usefulness of each tools and methods. Thecitations andreferences for eachchapter aregivenat theendof eachchapter.Although Microsoft Excel, Minitab and R software have been used in thebook for preparing charts and plots, this is not a prerequisite for using this book.Vadodara, Gujarat, India K. Muralidharanviii PrefaceAcknowledgmentsThis book has come to fruition because of the generosity shown by many profes-sionalcolleagues,friendsandwell-wishers. Iexpressmydeepsenseofgratitudeandregards toall of them. I sincerelyacknowledgeProf. SubhaChakraborthy(Universityof Alabama), Prof. W.H. Woodall (VirginiaTechUniversity), Prof.D.C.Montgomery(ArizonaStateUniversity)andProf. JijuAntony(Heriot-WattUniversity)fortheirhelpful contributionstothecontent ofthebook. Isincerelythank the head, Department of Statistics, University of Pune, for permitting me touse the statistical tables. In putting together the professional perspectives, I place onrecord many university department heads, colleagues and librarians for theirassistance in materials and academic collaborations.My colleagues at the Maharajah Sayajirao University of Baroda have been verysupportive and cooperative in rendering their assistance towards this project. Twoof mycolleagues Dr. (Mrs.) KhimiyaTinani andDr. (Mrs.) Rupal Shahneedspecial mention as they have done an excellent job of verifying and correcting theproblems andtheir solutions inthe book. I sincerelyacknowledge Prof. Ven-kateswarlu and Prof. J.P. Parikh at the Department of English, Maharajah SayajiraoUniversity of Baroda, for their assistance towards reading the material for language,grammarandsyntax. IalsoplaceonrecordDr. Aarti MujumdarandDr. MilanSagar of Cambridge Education for providing their professional editorial service.I also thank Prof. B.K. Kale (University of Pune) and Prof. Ashok Shanubhogue(Sardar Patel University), as they remain as a constant inspiration to me to take upthe task and assignments throughout my professional career. Thanks are also due tomy industry friends Mr. Rakesh Singh (from Trendz Process Consulting, Hydera-bad), Mr. Rajesh Nambiar (Panacea Software, Baroda) and Mr. Vimal Vyas (Sie-mens, Vadodara) for enlightening me on the importance of Six Sigma concepts inindustries and manufacturing industries.I thankmywifeLathikaandsons VivekandVarunfor their patienceandsilence, rendered throughout the writing of the book.If the readersnd that proper acknowledgement has not made to any particularindividuals, authors, references, citations, etc., kindly treat this it is not intentionaland request that you bring the same to my notice for future mention.ixContents1 Six Sigma Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Six Sigma Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 61.3 Six Sigma Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.4 Six Sigma Tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.5 Six Sigma Deliverables. . . . . . . . . . . . . . . . . . . . . . . . . . . 111.6 Lean Six Sigma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121.7 Six Sigma: The Belt Systems . . . . . . . . . . . . . . . . . . . . . . . 141.8 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 16References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Six Sigma Project Management . . . . . . . . . . . . . . . . . . . . . . . . . . 192.1 Project Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.2 SWOT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202.3 Project Phases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212.4 Alignment with the Business Strategy . . . . . . . . . . . . . . . . . 222.5 Project Stakeholders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232.6 Managing the Stakeholders. . . . . . . . . . . . . . . . . . . . . . . . . 242.7 A Six Sigma Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252.7.1 Probability Model-Based Project . . . . . . . . . . . . . . . 272.7.2 Regression Model-Based Project . . . . . . . . . . . . . . . 272.8 Quantitative Project Management . . . . . . . . . . . . . . . . . . . . 282.9 Project Risk Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . 292.9.1 Quantifying the Risk . . . . . . . . . . . . . . . . . . . . . . . 302.10 Critical Evaluation of a Project . . . . . . . . . . . . . . . . . . . . . . 312.11 Role of Computing Technology in Project Management. . . . . 332.12 Launch and Execution Process . . . . . . . . . . . . . . . . . . . . . . 342.13 Closure of the Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34xi2.14 The Climate for Success . . . . . . . . . . . . . . . . . . . . . . . . . . 342.15 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 35References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 Six Sigma Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.2 Process Characterization. . . . . . . . . . . . . . . . . . . . . . . . . . . 423.3 Process Perception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443.4 Process Capability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443.5 Process Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453.6 Process Improvement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463.7 Process Control. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463.8 Relevance or Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 47References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Understanding Variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494.1 Types of Variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.1.1 Special Cause Variation. . . . . . . . . . . . . . . . . . . . . 504.1.2 Common Cause Variations. . . . . . . . . . . . . . . . . . . 504.2 Causes of Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524.3 Need for Measuring Variation. . . . . . . . . . . . . . . . . . . . . . . 534.4 Measurement Variations. . . . . . . . . . . . . . . . . . . . . . . . . . . 544.5 Measurement System Characteristics . . . . . . . . . . . . . . . . . . 554.6 Measures of Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . 574.7 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 62References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 655 Sigma Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675.2 Some General Estimators of Standard Deviation . . . . . . . . . . 685.3 Estimation of Standard Deviation Through Control Charts . . . 745.3.1 Default Method Based on IndividualMeasurements . . . . . . . . . . . . . . . . . . . . . . . . . . . 745.3.2 Sigma Estimation for Subgroups . . . . . . . . . . . . . . . 755.3.3 MVLUE Method Based on Subgroup Ranges. . . . . . 765.3.4 MVLUE Method Based on Subgroup StandardDeviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 765.4 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 77References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 796 Sample Size Determination. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 816.1 Accuracy and Precision . . . . . . . . . . . . . . . . . . . . . . . . . . . 816.2 Sample Size When Characteristic of Interest Is Mean . . . . . . 836.3 Sample Size When Characteristic of Interest Is Proportion . . . 86xii Contents6.4 Sample Size When Characteristic of Interest Is Counts . . . . . 916.5 Sample Size When Characteristic of InterestIs Difference of Means . . . . . . . . . . . . . . . . . . . . . . . . . . . 926.6 Sample Size When Characteristic of InterestIs Difference of Proportions . . . . . . . . . . . . . . . . . . . . . . . . 936.7 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 95References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 977 Dene Phase. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 997.1 Project Charter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 997.1.1 The Problem Statement . . . . . . . . . . . . . . . . . . . . . 997.1.2 The Goal (or Result) Statement. . . . . . . . . . . . . . . . 1007.1.3 Customer Identification . . . . . . . . . . . . . . . . . . . . . 1017.1.4 Process Models. . . . . . . . . . . . . . . . . . . . . . . . . . . 1047.2 Defining Team Roles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1067.3 Managing the Project Team . . . . . . . . . . . . . . . . . . . . . . . . 1097.4 Planning Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117.4.1 Gantt Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1127.4.2 Affinity Diagram. . . . . . . . . . . . . . . . . . . . . . . . . 1137.5 Process Map and Flowchart . . . . . . . . . . . . . . . . . . . . . . . . 1147.6 Quality Function Deployment (QFD). . . . . . . . . . . . . . . . . . 1167.6.1 House of Quality. . . . . . . . . . . . . . . . . . . . . . . . . 1167.6.2 Kanos Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 1177.7 Understanding Defects, DPU, and DPMO. . . . . . . . . . . . . . 1187.8 Incorporating Suggestions, Improvements, and Complaints . . . 1207.9 Readying for the Next Phase. . . . . . . . . . . . . . . . . . . . . . . 1207.10 Define Check Sheets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1217.11 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 121References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1228 Measure Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1238.1 Initiating Measure Phase. . . . . . . . . . . . . . . . . . . . . . . . . . 1238.2 Process Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1248.2.1 Voice of Customer. . . . . . . . . . . . . . . . . . . . . . . . 1258.2.2 Voice of Process. . . . . . . . . . . . . . . . . . . . . . . . . . 1278.3 Adding Value Through Customer Service . . . . . . . . . . . . . . 1288.4 Value Stream Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . 1298.5 Data Collection Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1308.5.1 Unit of Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 1318.5.2 Characteristics of Interest . . . . . . . . . . . . . . . . . . . . 1318.5.3 Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1328.6 Cycle Time, Takt Time, Execution Time, and Delay Time . . . 134Contents xiii8.7 Measurement System Analysis. . . . . . . . . . . . . . . . . . . . . . 1358.7.1 Assessing Bias in Continuous Measurements. . . . . . 1368.7.2 Assessing Bias of Attribute Data. . . . . . . . . . . . . . . 1418.8 Descriptive Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1468.8.1 Measures of Accuracy . . . . . . . . . . . . . . . . . . . . . . 1478.8.2 Measures of Symmetry and Shape . . . . . . . . . . . . . 1498.9 Describing Sources of Variation . . . . . . . . . . . . . . . . . . . . . 1538.9.1 Pareto Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1538.9.2 Control Charts. . . . . . . . . . . . . . . . . . . . . . . . . . . 1548.9.3 Cause and Effect Diagram . . . . . . . . . . . . . . . . . . . 1558.9.4 Prioritization Matrix. . . . . . . . . . . . . . . . . . . . . . . 1588.10 Dealing with Uncertainty: Probability Concepts . . . . . . . . . . 1608.10.1 Principles of Counting. . . . . . . . . . . . . . . . . . . . . . 1638.11 Random Variables and Expectation . . . . . . . . . . . . . . . . . . . 1678.11.1 Discrete Random Variables . . . . . . . . . . . . . . . . . . 1678.11.2 Continuous Random Variables . . . . . . . . . . . . . . . . 1708.11.3 Jointly Distributed Random Variables. . . . . . . . . . . 1748.12 Probability Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1828.12.1 Binomial Distribution. . . . . . . . . . . . . . . . . . . . . . 1828.12.2 Poisson Distribution. . . . . . . . . . . . . . . . . . . . . . . 1858.12.3 Hypergeometric Distribution. . . . . . . . . . . . . . . . . . 1908.12.4 Normal Distribution . . . . . . . . . . . . . . . . . . . . . . . 1948.12.5 Distributions Arising from the Normal. . . . . . . . . . . 1988.12.6 Exponential Distribution . . . . . . . . . . . . . . . . . . . . 2038.12.7 Gamma Distribution. . . . . . . . . . . . . . . . . . . . . . . 2078.12.8 Weibull Distribution. . . . . . . . . . . . . . . . . . . . . . . 2088.12.9 Sampling Distributions . . . . . . . . . . . . . . . . . . . . . 2118.13 Capability Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2148.13.1 Process Potential Index (Cp Index) . . . . . . . . . . . . . 2158.13.2 Process Performance Index (Cpk Index) . . . . . . . . . . 2158.14 Baseline Performance Evaluation . . . . . . . . . . . . . . . . . . . . 2198.15 Measure Checklists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2208.16 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 221References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2359 Analyze Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2379.1 Process Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2379.2 Brainstorming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2389.3 Failure Modes and Effects Analysis. . . . . . . . . . . . . . . . . . . 2409.3.1 Design FMEA. . . . . . . . . . . . . . . . . . . . . . . . . . . 2429.3.2 Process FMEA . . . . . . . . . . . . . . . . . . . . . . . . . . . 2439.4 Histogram and Normality. . . . . . . . . . . . . . . . . . . . . . . . . . 2449.4.1 Probability Plotting . . . . . . . . . . . . . . . . . . . . . . . . 2449.4.2 Normal Probability Plot . . . . . . . . . . . . . . . . . . . . . 245xiv Contents9.5 Parameter Estimation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2479.5.1 Point Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 2489.5.2 Confidence Interval Estimation . . . . . . . . . . . . . . . . 2519.6 Testing of Hypothesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . 2579.6.1 Parametric Tests . . . . . . . . . . . . . . . . . . . . . . . . . . 2599.6.2 Nonparametric Tests . . . . . . . . . . . . . . . . . . . . . . . 2699.6.3 Goodness-of-Fit Tests. . . . . . . . . . . . . . . . . . . . . . 2839.7 Modeling Relationship Between Variables . . . . . . . . . . . . . . 2899.7.1 Scatter Diagram and Correlations Study. . . . . . . . . . 2909.7.2 Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . 2959.7.3 Nonlinear Regression . . . . . . . . . . . . . . . . . . . . . . 3149.8 Analysis of Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3259.8.1 One-Way Classification or One-FactorExperiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3269.8.2 Two-Way Classification or Two-FactorExperiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3339.8.3 Three-Way Classification . . . . . . . . . . . . . . . . . . . . 3419.9 Root Cause Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3459.9.1 Fault Tree Analysis . . . . . . . . . . . . . . . . . . . . . . . . 3469.9.2 5-Whys Techniques . . . . . . . . . . . . . . . . . . . . . . . 3489.10 Readying for the Improve Phase . . . . . . . . . . . . . . . . . . . . . 3489.11 Analyze Checklists. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3499.12 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 349References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36110 Improve Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36310.1 Balanced Scorecard (BSC) . . . . . . . . . . . . . . . . . . . . . . . . . 36310.2 Kaizen Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36510.3 5S Implementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36610.4 The 3Ms Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36710.5 Kanban. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36810.6 Design of Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . 36910.6.1 Principles of Experimentation. . . . . . . . . . . . . . . . . 37210.6.2 Classification of Design of Experiments. . . . . . . . . . 37410.6.3 General Two-Factor Factorial Design . . . . . . . . . . . 37510.6.4 22Factorial Design . . . . . . . . . . . . . . . . . . . . . . . . 37710.6.5 23Factorial Design . . . . . . . . . . . . . . . . . . . . . . . . 38410.7 Robust Designs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39610.7.1 Robust Parameter Design. . . . . . . . . . . . . . . . . . . . 39810.8 Process Mapping for Improvement . . . . . . . . . . . . . . . . . . . 40310.8.1 Improving a Process Data . . . . . . . . . . . . . . . . . . . 40410.8.2 Improving a Stable Process . . . . . . . . . . . . . . . . . . 409Contents xv10.9 Simulation Techniques. . . . . . . . . . . . . . . . . . . . . . . . . . . . 41010.9.1 Model Selection and Validation. . . . . . . . . . . . . . . 41110.10 Implementation and Validation . . . . . . . . . . . . . . . . . . . . . . 41710.11 Improve Check Sheets . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41910.12 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 419References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42311 Control Phase. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42511.1 Control Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42511.2 Statistical Process Control . . . . . . . . . . . . . . . . . . . . . . . . . 42711.2.1 Describing Variations . . . . . . . . . . . . . . . . . . . . . . 42811.2.2 Control Charts. . . . . . . . . . . . . . . . . . . . . . . . . . . 42911.2.3 Control Charts for Variables. . . . . . . . . . . . . . . . . . 43111.2.4 Control Charts for Attributes . . . . . . . . . . . . . . . . . 44211.2.5 Cumulative Sum Chart . . . . . . . . . . . . . . . . . . . . . 45711.2.6 EWMA Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46111.2.7 Economic Design of Control Charts . . . . . . . . . . . . 46411.2.8 Role of Process Monitoring . . . . . . . . . . . . . . . . . . 46611.2.9 Nonparametric Control Charts . . . . . . . . . . . . . . . . 46811.3 Process Capability Studies . . . . . . . . . . . . . . . . . . . . . . . . . 47511.4 Poke Yoke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48111.5 Designed for Six Sigma . . . . . . . . . . . . . . . . . . . . . . . . . . . 48211.6 Quality Function Deployment . . . . . . . . . . . . . . . . . . . . . . . 48411.7 Standardization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48511.8 Standard Operating Procedures and Work Instructions . . . . . . 48511.9 Process Dashboards. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48611.10 Change Management and Resistance . . . . . . . . . . . . . . . . . . 48811.11 Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48811.12 Control Check Sheets . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48911.13 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 490References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49812 Sigma Level Estimation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50112.1 Sigma Level for Normal Process. . . . . . . . . . . . . . . . . . . . . 50112.2 Sigma Level for Non-normal Process. . . . . . . . . . . . . . . . . . 50612.3 Long-Term Versus Short-Term Sigma . . . . . . . . . . . . . . . . . 50612.4 Cost of Poor Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51212.5 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 513References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51413 Continuous Improvement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51713.1 Demings Quality Philosophy . . . . . . . . . . . . . . . . . . . . . . . 51813.2 Crosbys Quality Philosophy . . . . . . . . . . . . . . . . . . . . . . . 520xvi Contents13.3 Jurans Quality Philosophy. . . . . . . . . . . . . . . . . . . . . . . . . 52213.4 Feigenbaums Quality Philosophy . . . . . . . . . . . . . . . . . . . . 52313.5 Ishikawa Quality Philosophy . . . . . . . . . . . . . . . . . . . . . . . 52313.6 Taguchi Quality Philosophy . . . . . . . . . . . . . . . . . . . . . . . . 52413.7 Management Systems Standards . . . . . . . . . . . . . . . . . . . . . 52613.8 Six Sigma Quality Philosophy. . . . . . . . . . . . . . . . . . . . . . 52813.9 Lean Six Sigma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52913.10 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 531References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53214 Marketing Six Sigma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53314.1 What is Six Sigma Marketing? . . . . . . . . . . . . . . . . . . . . . . 53414.2 The Leading and Lagging Indicators . . . . . . . . . . . . . . . . . . 53714.3 Measurement-Based Key Marketing Indicators . . . . . . . . . . . 53814.4 Relevance of Supply Chain Metrics in Marketing . . . . . . . . . 53914.5 Importance of Data in Marketing . . . . . . . . . . . . . . . . . . . . 54114.6 Six Sigma Marketing Value Tools. . . . . . . . . . . . . . . . . . . . 54314.7 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 545References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54615 Green Six Sigma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54915.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54915.2 Green Six Sigma Tools and Techniques. . . . . . . . . . . . . . . . 55115.3 Sustainability Issues of Green Six Sigma . . . . . . . . . . . . . . . 55315.4 Benefits of Green Six Sigma . . . . . . . . . . . . . . . . . . . . . . . 55415.5 Green Six Sigma: Some Quality Guidelines . . . . . . . . . . . . . 55415.6 Green Six Sigma: Moving Toward Excellence. . . . . . . . . . . 55615.7 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 556References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55716 Six Sigma: Some Pros and Cons. . . . . . . . . . . . . . . . . . . . . . . . . 55916.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55916.2 Six Sigma: Advantages and Disadvantages. . . . . . . . . . . . . . 56016.3 Six Sigma: Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 56316.4 Six Sigma: Dos and Donts. . . . . . . . . . . . . . . . . . . . . . . . 56416.5 Six Sigma: The Future. . . . . . . . . . . . . . . . . . . . . . . . . . . . 56616.6 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 567References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56817 Six Sigma: Some Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . 56917.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56917.2 Case Study-1: Reduction in Extruder-Specific PowerConsumption in Duplex . . . . . . . . . . . . . . . . . . . . . . . . . . . 570Contents xvii17.3 Case Study-2: To Improve Product and Service Qualityof CFL Lamps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57417.4 Case Study-3: Customer Complaint Resolution ThroughRe-engineering Debit Card and PIN Issuance Process. . . . . . 57917.5 Relevance for Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . 582Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613xviii ContentsAbout the AuthorK. Muralidharanis professor and head of the Department of Statistics, Faculty ofScience, Maharajah Sayajirao University of Baroda, Vadodara. As well as directorof the Population Research Centre, Maharajah Sayajirao University, ProfessorMuralidharanisanadjunct facultyat IITGandhinagar. Hedidpost-doctoral fel-lowship from the Institute of Statistical Science, Academia Sinica, Taiwan. He is aninternationally certied Six Sigma Master Black Belt fromIndian StatisticalInstitute, Bangalore.xixAbbreviationsAIAG Automotive Industry Action GroupAIC Akaike information criterionAMA American Marketing AssociationANOVA Analysis of varianceAP Action PlanASQ American Society for QualityBB Black beltsBIC Bayesian information criterionBIBD Balanced incomplete block designBIS Bureau of Indian StandardsBSC Balanced score cardCA Comparative AnalysisC&E Cause and effectCED Cause and effect diagramCI Condence intervalCL Control limitCLT Central limit theoremCMM Capability maturity modelCMMI Capability maturity model integrationCOPIS Customer-Output-Process-Input-SupplierCOQ Cost of qualityCOPQ Cost of poor qualityCOV CovarianceCPM Critical path methodCRD Completely randomized designCRT Current reality treeCSF Critical success factorsCTC Critical to costCTD Critical to deliveryCTQ Critical to qualityCTP Critical to processCTS Critical to safetyxxiCUSUM Cumulative sumCV Coefcient of variationCVM Customer value mappingDER Debt-equity ratioDFSS Designed for Six SigmaDIDOV Dene-Identify-Design-Optimize-VerifyDMAIC Dene-Measure-Analyze-Improve-ControlDMADV Dene-Measure-Analyze-Design-ValidateDMEDI Dene-Measure-Explore-Develop-ImplementDOE Design of experimentsDPO Defects per opportunityDPMO Defects per million opportunitiesDPU Defect per unitEDA Exploratory data analysisELEV Empirical limited expected valueEMAS Eco-Management and Audit SchemeEMS Environmental management standardsERP Enterprise Resource PlanningESS Error sum of squaresEWMA Exponentially weighted moving averageFCF Free cash owFMEA Failure mode effect analysisFTA Fault tree analysisGB Green beltsGOFT Goodness-of-t-testGRPI Goals-roles and responsibilities-processes-proceduresGSS Green Six SigmaID Interrelationship diagramIDEA Identify-Dene-Evaluate-ActivateIPO Input-Process-OutputIQR Inter-quartile rangeISO International Organization for StandardizationIT Information technologyITES Information technology enabled servicesJUSE Union of Japanese Scientists and EngineersKBD Key business driversKMI Key marketing indicatorsKPI Key performance indicatorsKPIV Key process input variablesKPOV Key process output variablesLCL Lower control limitLER Loss elimination ratioLMAD Launch-Manage-Adapt-DiscontinueLSD Latin square designLSL Lower specication limitxxii AbbreviationsLSS Lean Six SigmaMAD Median absolute deviationMBB Master black beltsMBO Management by objectivesMD Mean deviationMIS Management information systemMRL Mean residual lifeMSA Measurement system analysisMSE Mean square errorMTBF Mean time between failuresMVLUE Minimum Variance Linear Unbiased EstimateMVUE Minimum variance unbiased estimateNVA Non value addedPERT Project (or program) evaluation and review techniquePBIBD Partially balanced incomplete block designPDCA PlanDoCheckActPM Project managementPPM Parts per millionPVM Product value mappingQC Quality controlQCI Quality council of IndiaQE Quality engineeringQFD Quality function deploymentQM Quality managementQPM Quantitative process managementQD Quartile deviationRBD Randomized block designRCA Root cause analysisROI Return of investmentR&R Repeatability and reproducibilityRPN Risk priority numberSC ED Stratication Cause and Effect DiagramSD Standard deviationSIC Schartz information criterionSIPOC Supplier-Input-Process-Output-CustomerSMART Specic-Measurable-Achievable-Relevant-TimelySOP Standard operating proceduresSOW Statement of workSPC Statistical process controlSQC Statistical quality controlSS Six SigmaSSM Six Sigma MarketingSWOT Strength-Weakness-Opportunities-ThreatsTLA Time Line AnalysisTOP Total opportunityAbbreviations xxiiiTPM Total productivity maintenanceTQC Total quality controlTQM Total quality managementTRIZ Theory of inventive problem solvingUCL Upper control limitUMVUE Uniformly minimum variance unbiased estimateUAPL Understand-Analyze-Plan-LaunchUMC Unit manufacturing costUSL Upper specication limitVA Value addedVAM Value analysis mappingVSM Value stream mappingVIF Variance ination factorVOC Voice of customerVOP Voice of processWIP Work in progressWIQ Work in queueWTA Willingness to acceptWTP Willingness to payxxiv AbbreviationsChapter 1Six Sigma Concepts1.1IntroductionSixSigmaisadisciplined, project-oriented, data-drivenapproachandamethod-ology for eliminating defects in a processfrom manufacturing to transactional andfromproduct toservice. It is amanagement philosophyattemptingtoimproveeffectivenessandefciency. It isuniquelydrivenbycloseunderstandingofcus-tomer requirements and reinventing business processes. The approach relies heavilyonadvancedstatisticalmethodsthatcomplementtheprocess andproductknowl-edge to reducevariationin processes[6, 8,12, 14]. Theconcept,if implementedproperly, helps to reduce the defects signicantly and exceptionally raises the levelof performance. It is a cornerstone of strategic planning to providerst-class serviceand products to customers. More detailed reviews and extensive Six Sigma bibli-ographieswereprovidedbyBradyandAllen[3] andNonthaleerakandHendry[25]. ForarecentoverviewofSixSigma, onemayrefertothearticlebyMont-gomery and Woodall [20].Themaingoal ofSixSigmaistoidentify, isolate, andeliminatevariationordefects in a manufacturing or transaction process. Six Sigma is a business processtool toachievecustomersatisfactionbyreducingvariations. Tomakeaproductdefectfree, itisessentialtominimizethevariationofaprocess.Atitscore, SixSigma revolves around few key concepts like the following: Defect: Failure to deliver what the customer wants Variation: What the customer sees and feels Critical to Quality: Those attributes most important to the customer Stable Operations: Ensuring consistent, predictable processes to improve whatthe customer sees and feels Process Capability: What your process can deliver Design for Six Sigma: Designing to meet customer needs and process capability Springer India 2015K. Muralidharan, Six Sigma for Organizational Excellence,DOI 10.1007/978-81-322-2325-2_11SixSigmaasaqualityimprovementtooladvocatesthepracticeofmeasuringvariability of a process, which may then be controlled by continuous improvement.In fact, the application of Six Sigma begins with translating a practical problem intoa statistical one. An optimal solution is found using appropriate statistical tools andthen implemented as a practical solution to real-life situation [12].At General Electric, Six Sigma is a measurement.The Six Sigma qualityini-tiative, verybriey, meansgoingfromapproximately35,000defectspermillionoperations, which is average for most companies, including GE, to fewer than fourdefects per million in every element in every process that this company engages inevery day (General Electric Company) [13].The other perceptions of Six Sigma concept as proposed by various authors areas follows:Six Sigma is a quality initiative that employs statistical measurements toachieve 3.4 defective parts per millionthe virtual elimination of errors [23].Six Sigma is a comprehensive, statistics-based methodology that aims toachieve nothing less than perfection in every single company process andproduct [27].Six Sigma alters the paradigm fromxing defective products to correcting theprocess so that perfect products are made [17].A Six Sigma initiative is designed to change the culture in an organization byway of breakthrough improvement in all aspects of the business [5].SixSigmaisaprogramthatcombinesthemosteffectivestatisticalandnon-statistical methods to make overall business [28].Six Sigma is a highly disciplined process that helps us focus on developing anddelivering near-perfect products and services. The central idea behind Six Sigmaisthat youcanmeasurehowmanydefectsyouhaveinaprocess, youcansystematically gure out howtoeliminate themandget as close to zerodefects as possible. Six Sigma has changed the DNA of GEit is the way weworkineverythingwedoineveryproduct wedesign(General Electricatwww.ge.com).Six Sigma is a business improvement approach that seeks tond and eliminatecauses of mistakes or defects inbusiness processes byfocusingonprocessoutputs that are of critical importance to customers [30].SixSigmaisausefulmanagementphilosophyandproblem-solvingmethod-ology but it is not a comprehensive management system.SixSigmaisamethodologywithaccompanyinghighlystructuredprocessesusingefcientstatisticalapproaches foracquiring,assessing,and applying thecustomer, competitor, enterprise, andmarket intelligencetoproducesuperiorproduct, process and enterprise innovations and designs with the goal of creatinga sustainable competitive advantage [19].To this list of denitions, I would like to add a practical denition underlying thenecessity of Six Sigma process improvement.2 1 Six Sigma ConceptsASixSigmainitiativeisacustomerfocusedproblem-solvingapproachwithreactiveandproactiveimprovementsofaprocessleadingtosustainablebusinesspractices. The sustainable business practices include innovation, improvement,competition, environmental compliance, customersatisfaction, andgrowthoftheorganization.The above denition entails organization to undergo structured problem-solvingapproachthroughproperdatacollectionanddelivertheexpectedcustomersatis-faction. The growth of the organization may be valued in terms of itsnancial gain,stakeholder condence, employee retention, productivity, and resource utilization.This denition also warrants the importance and necessity of dedicated people whocan improve a process with zero variation and sustain the improvements for a longperiod of time ensuring the success of a Six Sigma initiative.Technicallyspeaking, SixSigma is describedas a data-drivenapproachtoreduce defects in a process or cut costs in a process or product, as measured by sixstandard deviations between the mean and the nearest specication limits. Sigma(or ) is the Greek letter used to describe variability or standard deviation, such asdefects per units. Figure 1.1 shows a normal distribution of a population, with itsmean() inthe center andadatapoint onthecurveindicatingone standarddeviation (1 ) to the right of the mean.How well a desired outcome (or target) has been reached can be described by itsaverage or mean (), which is nothing but the sum of all data points divided by thenumberofdatapoints. Thestandarddeviation()describeshowmuchvariationactuallyexists withinadataset, whichis calculatedas thesquareroot of thevariation from the mean. A detailed discussion on the measures of standard devi-ation and the estimation procedures are given in Chap. 5.If a process is described as withinSix Sigma, theterm quantitativelymeansthat the process produces fewer than 3.4 defects per million opportunities (DPMO).That represents an error rate of 0.0003 %; conversely, that is a defect-free rate of99.9997 %. Note that the sigma measure compares your performance to customerrequirements (dened as target), and the requirements vary with the type of industryor business. = Population meanStandard deviation(distance from mean) =Fig. 1.1 A normaldistribution1.1 Introduction 3The sigma value of a process describes the quality level of that process.Aqualitylevel of Ksigmaexists inaprocess whenthehalf toleranceof themeasuredproductcharacteristicisequaltoKtimesthestandarddeviationoftheprocess [14]:K process standard deviation halftolerance ofspecificationHowever, this denition alone does not account for the centering of a process. Aprocess is centered when X = T, where X is the process average or mean and T is thetarget value, which is typically the midpoint between the customers upper speci-cationlimit (USL) andthelower specicationlimit (LSL). Aprocess is off-centered when the process average, X, does not equal the target value T. The off-centeringof aprocess is measuredinstandarddeviations or sigma. Table1.1presents theDPMOcorrespondingtodifferent Sigmalevels under various off-centering of the process.Note that the value or number of defects of a process is a function of the sigmavalue (quality level) of the process. The true value of the quality level of a processis the number of defects that occur when the process is centered; that is, when theoff-centering value is 0 sigma. In the case of Six Sigma, there are 0.002 defects permillion or 2 defects per billion. On the other hand, Motorolas concept of 6 sigmaallowsashiftinthemeanof1.5sigma[9]. Therefore, MotorolasvalueofSixSigma assumes an allowable shift of 1.5 sigma and thus also shows a defect rate notexceeding 3.4 per million. The value of 3.4 defects per million in a centered processimplies a process quality level between 4 and 5 sigma.The role of the sigma shift is mainly academic. The purpose of Six Sigma is togenerateorganizationalperformanceimprovement. Itisuptotheorganizationtodetermine, based on customer expectations, what the appropriate sigma level of aprocessis. Thepurposeofthesigmavalueisacomparative guretodeterminewhether aprocessisimproving, deteriorating, stagnant, ornon-competitivewithothers in the same business. It should not be the goal of all processes. Geoff [10]justies that every process does not perform as well in the long term as they do inTable 1.1 DPMO for different sigma levelOff-centering 3 3.5 4 4.5 5 5.5 6 0 2700 465 63 6.8 0.57 0.038 0.0020.25 3557 665 99 11.7 1.09 0.0805 0.00470.5 6442 1382 236 32 3.4 0.29 0.0190.75 12,313 2990 578 88.5 11 1.02 0.11 22,782 6213 1350 233 32 3.4 0.291.25 40,070 12,225 2980 577 88.4 10.7 11.5 66,811 22,750 6210 1350 233 32 3.41.75 105,651 40,059 12,224 2980 577 88.4 112 158,656 66,807 22,750 6210 1350 233 324 1 Six Sigma Conceptsthe short term. As a result, the number of sigmas that will t between the processmean and thenearestspecication limitmay well drop over a period of time.Toaccount for thisreal-lifeincreaseinprocessvariationover time, anempiricallybased1.5sigmashiftisintroducedintothecalculation.Accordingtothisidea,aprocessthat ts6sigmabetweentheprocessmeanandthenearest specicationlimit in a short-term study will in the long termt only 4.5 sigmaeither becausethe process mean will move over time, or because the long-term standard deviationof the process will be greater than that observed in the short term, or both. This isexplained in Fig. 1.2.Hence, the widely accepted denition of a Six Sigma process is a process thatproduces 3.4 defective parts per million opportunities (DPMO). This is based on thefact that a process that is normally distributed will have 3.4 parts per million beyonda point that is 4.5 standard deviations above or below the mean. So the 3.4 DPMOof a Six Sigma process in fact corresponds to 4.5 sigma, namely 6 sigma minus the1.5 shift introducedtoaccountforlong-termvariation.Thisallowsforthefactthat special causes may result in deterioration in process performance over time andis designed to prevent underestimation of the defect levels likely to be encounteredin real-life operation.Asuccessful implementationofaSixSigmaapproachrequirescompaniestoconsider changes in methodologies across the enterprise, introducing new linkagesandcommunications.ThreebenchmarkexamplesofhowSixSigmapermeatesacorporate philosophy and becomes a business initiative can be found by studyingMotorola, Allied Signal, and General Electric (GE). Motorola created Six Sigma asa rallying point to change the corporate culture to compete better in the Asia-Pacictelecommunications market. Motorolas mainfocus was onmanufacturinganddefect reduction. Allied Signal rebuilt its business with bottom-line cost6 - 5 - 4 - 3 - 2 - 1 - 0 1 2 3 4 5 61.5 shiftLSL USL36Fig. 1.2 A Six Sigma process with 1.5 shift1.1 Introduction 5improvementusingSixSigma. Eventually, AlliedSignalextendeditsSixSigmaimplementationintoitsbusinessandtransactionalprocessesforcost control. GErevolutionized howan entire enterprise disciplines itself across its operations,transactions, customerrelations, andproductdevelopmentinitiatives. Theycouldachieve this using an approach called Design for Six Sigma (DFSS), a methodologyfor product and development.The proven benets of Six Sigma system are as diverse as to: Reduces costs, defects, and cycle time Generates sustained success Sets a performance goal for everyone Enhances value to customers Accelerates the rate of improvement Encourage development of new process, product, and service Improves market share Executes strategic change Encourages cultural change Promotes learning and cross-pollination.Foraserviceindustry, it helpstoimpart best servicesandskills. It facilitatespeopleexcellenceaswell astechnical excellenceintermsofcreativity, collabo-ration, communication, dedication, andaboveall increasestheaccountabilityofwhat one does in an organization [14, 22, 26].1.2Six Sigma MethodologyThe Six Sigma philosophy works under a structured problem-solving approach. Theproblems generally concerned with eliminating variability, defects, and waste in aproduct or process all undermine customer satisfaction. The working philosophy isgenerally called denemeasureanalyzeimprovecontrol (DMAIC), where DeneDene the problem or project goals that need to be addressed MeasureMeasure the problem and process from which it was produced AnalyzeAnalyzedataandprocesstoidentifytherootcausesofdefectsandopportunities ImproveImprove the process bynding solutions tox, diminish, and preventfuture problems ControlImplement, control, andsustaintheimprovementsandsolutionstokeep the process on the new courseThe DMAICphilosophy applies toboth process improvement andproductimprovement or evendesignredesignefforts. The keyelements ina DMAICproject are team discipline, structured use of metrics and tools, and execution of awell-designedproject planthat hasclear goalsandobjectives. LeanSixSigma(LSS) modies the DMAICapproachbyemphasizingspeed. Leanfocuses on6 1 Six Sigma Conceptsstreamlining a process by identifying and removingnon-value-addedsteps. Aleaned production process eliminates waste. Target metrics include zero wait time,zero inventory, scheduling using customer pull, cutting batch sizes to improve ow,linebalancing, andreducingoverall processtime. LeanSixSigmasgoal istoproduce quality products that meet customer requirements as efciently andeffectively as possible.If a process cannot be improved as it is currently designed, another well-knownSix Sigma problem-solving approach can be applied. The DMADV process is usedto fundamentally redesign such a process. Thisve step approach is as follows: DeneDene the problem and/or new requirements MeasureMeasure the process and gather the data that are associated with theproblem or in comparison with the new requirements AnalyzeAnalyzethedatatoidentifyacause-and-effectrelationshipbetweenkey variables DesignDesign a newprocess so that the problemis eliminated or newrequirements are met ValidateValidate the new process to be capable of meeting the new processrequirementsA second redesign approach has been developed to incorporate elements from aLeanSixSigmaapproachtheDMEDIprocess.ThisissimilartoDMADVandadds tools from the Lean methodology to ensure efciency or speed. The steps areas follows: DeneDene the problem and/or new requirements MeasureMeasure the process and gather the data that are associated with theproblem or in comparison with the new requirements ExploreExplorethedatatoidentifyacause-and-effect relationshipbetweenkey variables DevelopDevelopanewprocesssothat theproblemis eliminatedor newrequirements are met ImplementExecute the new process under a control planAnothervariant ofSixSigmaimprovement cyclesisdesignedforSixSigma(DFSS) approach. DFSSensures that the newproduct or service meets stake-holders needs, provides ahighlevel of performance, andis robust toprocessvariations. While DMAIC is a reactive approachxing past problems, DFSS is usedinaproactivewaytoavoidproblemsinthe rst place. DFSSapproachenableslaunchingnewproductsandservicesontimeandonbudget andtarget gainingincremental revenues sooner, achieving greater market share, and ensuring that thecompanygeneratesdifferentiatedproductsandservicesthat target customer andstakeholder needs. DMADV is one of the important methodologies used in DFSS.This methodology works with the followingve steps: DeneIdentify the Customer and project IdentifyDene what the customers want, or what they do not want1.2 Six Sigma Methodology 7 DesignDesign a process that will meet customers needs OptimizeDetermine process capability and optimize design VerifyTest, verify, and validate designThe concept of Six Sigma at GE deals with measuring and improving how closethe company comes in delivering on what it planned to do. Six Sigma provides awayforimprovingprocessessothat thecompanycanmoreefcientlyandpre-dictably produce world-class products and services. Specically, the DMAICaccording to Paul [27] is as follows: DeneWho are the customers and what are their priorities? MeasureHow is the process measured and how is it performing? AnalyzeWhat are the most important causes of defects? ImproveHow do we remove the causes of the defects? ControlHow can we maintain the improvements?1.3Six Sigma ToolsMost ofthedecision-makingtoolsforSixSigmaareborrowedfromthesubjectstatistics. These tools along with the management inputs are systematically used intheorganizational processtoget themaximumyield. Someofthetoolsmaybeintegrated in two or more phases to establish the initial performance of the processandsomeofthemareexclusivelyusedforconrmatoryanalysisandcontinuousimprovement. The DMAIC phasewise tools are presented in Fig. 1.3. It is expectedthatabasic-toadvance-levelknowledgeisessentialtocarryoutproperanalysisand interpretation.Apart fromtheabovetools, someofthetoolsusedinDMADVthat arenotcoveredinDMAICare as follows: Multi-Generational Project Plans (MGPP),Analytical Hierarchy Process (AHP), Kano Analysis, KANSEI Engineering, TRIZ(Theory of inventive problem solving), Pugh Analysis, Taguchi Optimization, andCapability Maturity Model Integration (CMMI) and Simulation methods etc.Six Sigma is being utilizedin almost everyindustry these days, like manufac-turing industries, automotive and aerospace industries, IT/ITES developmentindustries,processindustries,pharmaceuticalindustries,etc.Asdiscussedearlier,Six Sigma is as much about peoples excellence as it is about technical excellence.Creativity, collaboration, and dedication are innitely more powerful than a corpsofsuper-statisticians. Thus, aSixSigmaprocesscaninspireandmotivatebetterideas and performance from people and create synergy between individual talentsand technical prowess. Very often, the signicantnancial savings from Six Sigmamay exceed in value by the intangible benets. In fact, the changes in attitude andenthusiasmthat comefromimprovedprocessesandbetter informedpeopleareoften easier to observe, and more emotionally regarding than dollar savings.8 1 Six Sigma ConceptsASix Sigma initiative includes Enterprise Resource Planning (ERP), e-CommerceandServices, LeanManufacturing, Customer RelationshipManagement (CRM)Systems, Strategic business Partnerships, Knowledge Management, Activity-basedManagement, Just-in-time inventory and Globalization. For Six Sigma measures tobe applied effectively across the organization, strict guidelines need to be followed.Otherwise, the measurement system and identication of critical-to-quality (CTQ)characteristics will be redundant, ultimately leading to a total chaos in theorganization.Inthenexttwosubsections,wegivetheSixSigmatasksanddeliverablesforeach phase in a concise form.Define Project charter, Gantt chart/timeline, Process mapping, flow chart, Pareto chart and Control charts, QFD/House of quality,Cost of quality,Trend analysis, Suggestions/Complaints, Surveys/Interviews/Focus groupMeasureSurveys/Interviews/Focus group, sample size determination, Data collection, Check sheets/Spreadsheets, SIPOC diagram, Descriptive Statistics, Charts and plots, Normal probability plots, Capability analysis, Pareto charts/Control charts/time series chart Measurement System Analysis,Gage studies, Process map/flow chart, Project charter, Gantt chart/timeline preparationAnalyzeCause and Effect diagram, FMEA, Histogram,Scatter diagram and Correlations study, Testing of Hypothesis, Confidence intervals,Pareto charts/Control charts,Time series chart, Regression Analysis, ANOVA, DOE, Response Surface Methods,Reliability analysis, Multivariate techniques, High level process mapImprove Affinity diagram, Testing of Hypothesis, Confidence intervals, ANOVA, MANOVA, Multi-vari chart, General linear models, Logistic regression, Probit analysis, DOE, factor analysis, FMEA, DOE, Proess map/flow chart, Simulation/Trial and error, Implementation and ValidationControl Control charts, Process map/Flow chart, Poka-Yoke, Standardization,SOP/Work instructions, Process Dashboards, Capability studeis, MSA and Gage R&R, Yield calculation, Documentation, final report and presentation. Fig. 1.3 DMAIC phasewise tools1.3 Six Sigma Tools 91.4Six Sigma TasksDene phase Identify sources of data Collect baseline data from existing process Determine current process performance Validate measurements and collection systemMeasure phase Conduct root cause analysis Validate gaps in requirements versus current metrics Quantify opportunity to close gaps Prioritize root causes Measure and map y f xAnalyze phase Conduct a revised root cause analysis to identify the vital few causes Validate gaps in requirements versus current metrics with vital causes Quantify opportunity to close gaps Prioritize root causes and identify the most contributing one Establish y f x and identify critical variablesImprove phase Develop potential improvements or solutions for root causes Develop evaluation criteria to Prioritize solution options for each root causes Examine solutions with a short-term and long-term approach. Weighthecostsandbenetsof quick-hitversusmoredifcult solutionoptions Select and implement the improved process and metric Measure results Evaluate whether improvements meet targets Evaluate for riskControl phase Document a new or improved process and measurements Validate collection systems and the repeatability and reproducibility of metricsin an operational environment Dene the control plan and its supporting plans like the following: Communicationsplanoftheimprovementsandoperationalchangestothecustomers and stakeholders Implementation plan10 1 Six Sigma Concepts Risk management plan Cost/benet plan Change management plan Train the operational stakeholders Establish the tracking procedures in an operational environment: Monitor implementation Validate and stabilize performance gains Jointly audit the results and conrmnal nancials.1.5Six Sigma DeliverablesDene phase Preparation of project charter and statement of work (SOW), which includes Process and problem Scope and boundaries Team, customers, and critical concerns Improvement goals and cost of poor quality (CoPQ) Gantt chart/timeline preparation Process map/owchart Stepwise documentation and follow-up steps Exit ReviewMeasure phase Initial Sigma level and cost calculations Process capability analysis Measurement System Analysis and Gage R&R Gantt chart/timeline SIPOC diagram/high level process map Stepwise documentation and follow-up steps Exit ReviewAnalyze Phase Identify root causes using cause-and-effect diagram, and through statisticalanalysis Validate root causes Stepwise documentation and follow-up steps Exit Review1.4 Six Sigma Tasks 11Improve Phase Select root causes and countermeasures Improve implementation plan Validate solutions or suggest improvement using statistical analysis Stepwise documentation and follow-up steps Exit ReviewControl Phase Prepare control plan for Tolerances, controls, and measures Charts and monitor Standard operating procedures (SOP) Design a response plan, design re-design of control plans Validated in-control process and benets for process capability MSA and Gage R&R documentation Stepwise documentation and follow-up steps Exit review1.6Lean Six SigmaLean Six Sigma is a process improvement program that combines two ideas: Leanacollectionof techniques for reducingthetimeneededtoprovideproductsorservicesand Six Sigmaa collection of techniques for improving the quality bycombining the two. Lean Six Sigma is a proven business management strategy thathelps organizations operate more efciently. As we know, a business process is aseries of interconnected sub-processes. The tools and focus of Six Sigma is thereforetox processes.Lean concentrateson theinterconnectionbetweenthe processes.ThecentralthemeofSixSigmaisdefectreduction,wheretherootcausesofthedefects are examined and improvement efforts are focused on those causes.InLeanSixSigma(sometimesreferredtoLeanor Leanmanufacturing), theemphasis is on reducing costs by eliminating product and process waste [29]. It alsofocuses on eliminating non-value-added activities such as producing defectiveproduct, excess inventory charges due to work-in-process and nished goodsinventory, excess internal and external transportation of product, excessiveinspection, and idle time of equipment or workers due to poor balance of work stepsin a sequential process. The goal of Lean manufacturing has long been one of the12 1 Six Sigma Conceptsgoals of industrial engineering [11]. According to Muir [21], the two philosophiescan be summed up as: Reduce the time it takes to deliver a defect-free product orservicetothecustomer.It isnot thequestionofwhetherthecustomerwantsitright or quickly, but both.Theoperatingphilosophyof Leanis toeliminatewastethroughcontinuousimprovement. This is achieved through the following: dening value from the clients perspective identifying the value stream only making what the client pulls keeping the ow moving continuously and always improving the processAs seen earlier, the Six Sigma process improvement works with the philosophyof DMAIC techniques. In Lean Six Sigma, it develops with the identication of theproblems andends withretainingthebenets of theprogram. Thus, thestepsfollowed in Lean Six Sigma are RDMAICS,where theadditionalR stands forrecognize and S stands for sustain. It is important to identify the signicant gaps ina business problem by articulating the business strategy. This will decide what themanagement wantstodeliver. OnceaSixSigmaproject completesthroughtheDMAICprocedure,themanagementwillbeabletoidentifythetangiblebenetscomingoutoftheprojectanditsimmediateimpactcanbeassessedforretainingsimilar such projects.In order to achieve the required target, a process owis necessary to beestablished. Aperfect process has continuous ow, as products, services, andknowledge are transformed continuously without delay from step to step. A ow iscreatedbyeliminatingqueues andstops andimprovingprocess exibilityandreliability. The other aspects of establishing the continuousow is by identifyingthe value-added and non-valued activities in a process. Any activities that add novalue to the client are by denition waste. The mapping of all activities and stepsaccording to their time of occurrence required bringing a product, service orcapability to the client is called Value Stream Mapping (VSM).ImplementingLeanwilladdresswasteanditsrootcauses.Wastepointsustoproblemswithinthesystem.Leanalsofocusesonefcientuseofequipmentandpeople and minimizes issues by standardizing work. A Lean cost model says thatdecreasedcost alwaysleadstoincreasedprot. If thefocusof SixSigmaistoreduce variation in a process, then the focus of Lean Six Sigma is to reduce waste.Hence, the tools for both philosophies differ depending on the business issue to beresolved.Interestingly, bothmethodologies followDMAICproblem-solvingapproach,Lean/Kaizen events follow a fasterimprovement cycle thanSix Sigma, and Leanpursues constant and continuous improvement until all non-value-added activitiesare eliminated.1.6 Lean Six Sigma 13Six Sigma characteristics In-depth root cause analysis and solutions Builds highly trained and skilled staff Used for solving more complex, larger issues Strong, positive results take longer time to achieve Robust infrastructureLean Six Sigma characteristics Speed and exibility Involves all employees Positive results in short time frame Focused on smaller-scale projects Less scientic: often trial and errorAccording to many business analysts and quality improvement experts, Lean SixSigmaisthemost popular businessperformancemethodologyinthehistoryofcorporatedevelopment ofqualityofproductsandservices, substantiallycontrib-utingtoincreasedcustomer satisfaction. GEunder JackWelchwas a leadingproponent of Lean Six Sigma globally. Genpact (at that time known as GE CapitalInternational Services) was the rst serviceprovider intheworldtoapplythismethodologyat scalefor businessprocesses, makingthispracticeatremendoussuccess. LeanSixSigma permeates what we doandis highlyvisible inouroperations, people, processes, andleadershipdirection(http://www.genpact.com/home/about-us/lean-six-sigma-dna).1.7Six Sigma: The Belt SystemsA Six Sigma project is executed through a coordinated effort with highly respon-sible personnel of organizations. The success of any Six Sigma project also dependson these personals. The system adopts different belt training to facilitate this. Themain roles associated with a specic belt of a Six Sigma projects can be summa-rized as follows:Green Belt (GB): A Six Sigma role associated with an individual who retains hisor her regular position within therm but is trained in the tools, methods, andskills necessary to conduct Six Sigma improvement projects either individuallyoraspartoflargerteams.GBtrainingistypicallyforoneortwoweeks,andthey generally assist on major project teams or lead teams engaged in smaller,more highly specic projects.Black Belts (BB): A Six Sigma role associated with an individual who is typ-ically assigned full time to train and mentor Green Belts as well as leadimprovement projectsusingspeciedmethodologiessuchasdene, measure,analyze, improve, and control (DMAIC); dene, measure, analyze, design, and14 1 Six Sigma Conceptsverify(DMADV);anddesigedforSigma(DFSS)tools.BBstypicallyhaveaminimum of four weeks of specialized training, sometimes spread over a four-monthperiodandusuallycombinedwithconcurrent workonaSixSigmaproject. Theyleadteamsthat arefocusedonprojectswithbothqualityandbusiness impact for the organization. In most organizations, BBs train GBs andwork on other functions such as new project identication.Master BlackBelt (MBB): ASixSigmaroleassociatedwithanindividualtypically assigned full time to train and mentor Black Belts as well as lead thestrategy to ensure improvement projects chartered are the right strategic projectsfortheorganization. MBBsareusuallytheauthorizingbodytocertifyGreenBeltsandBlackBeltswithinanorganization. Theyoftenwriteanddeveloptraining materials, are heavily involved in project denition and selection, andwork closely with business leaders called Champions. The BBs and MBBs havespecialized training and education on statistical methods and other quality andprocess improvementtools that equipthem to functionas team leaders, facili-tators, andtechnicalproblemsolvers. Thesedays, manynationalandinterna-tional organizations offer education in Six Sigma quality training and offer beltcertications. The American Society for Quality (ASQ) maintains a Six SigmaBlack Belt bodyof knowledge ontheir Website (see http://www.asq.org/certication/six-sigma/bok.html).The role of Champions is to ensure that the right projects are being identied andworked on, that teams are making good progress, and that the resources required forsuccessful project completion are in place. Champions are project sponsors. Cham-pions are generally guided by project managers in the organization. The appointmentsof higher ofcials are altogether the organizations own matter of policy (for morediscussion on these aspects, see Chap. 7). Theow of involvement and responsi-bilities described above is the essence of how Six Sigma has been implemented todate and how implementation is changing the organization in terms of its growth andnancial gains. A current trend consistent with administration of quality and certainmanagement functions is to push responsibility to lower levels within organizations.How this applies to implementation of Six Sigma is through greater responsibility forproblem or opportunity identication, data collection, and analysis, and correctiveaction is being levied on Green Belts. In order to facilitate this, many organizationsinitiateYellowBeltsandevenWhiteBeltstrainingforbeginnerstobereadyforlarger rolesinSixSigmaprojectsandactivities. Theyaregenerallytrainedfortechnical aspects of management decision-making opportunities.Since Six Sigma focuses on reducing defects as a top priority for qualityimprovements [16], it is important here to note that often the large savings obtainedfromSixSigma efforts are savings fromreducingthe costs of poor qualityobtained by extracting gold in the mine, as Juran had already said 50 years ago.Further, the focus on processes and on eliminating variation has certainly increasedknowledgeabout variation, animportant part ofDemingsProfoundKnowledgesystem [7]. In recent years, also a focus on reducing lead times is also emphasizedas a side effect of process improvement.1.7 Six Sigma: The Belt Systems 15It is with these requirements, new variants of Six Sigma concepts have appeared.Some of them are FIT SIGMA [2], Ultimate Six Sigma, and Strategic Six Sigma.Furthermore, it is fundamentally important to understand what the customer wantsand needs and to use this information to guide R&D efforts on existing products ordesign of new ones [18]. While an increasing number of organizations are engagingin DFSS, it must be stressed that DFSSis hard work, requiring a relativelyimposingamount of expertiseand it is still relativelynewsothat there isprobablymore talk than work done with respect to DFSS application.Hoerl [15] states that perhaps the most critical question about the future of SixSigma is when it will begin to wind down and perhaps morph into something else.While Six Sigma will evolve over time, as in the case of TQM has and will, thereare some core strengths of Six Sigma that will be maintained so whatever the nextbig thing is, it will look at least vaguely familiar to Six Sigma. Some of these corestrengths are the use of infrastructure to supply the core people, money and otherresources, freeing top talent to work on new initiatives, and, of course, reliance onsenior leadership commitment.According to Woodall [31], and Montgomery and Woodall [20], the healthcareserviceisoneofthepotentialarea, whereSixSigmacanplaysignicantroleinimprovingtheservicesanddelivery. For continuedsuccessof SixSigma, it isnecessarytoincorporateabroaderarrayofstatistical methods, particularlythosethat aremoreappropriatefortheincreasingamountofdataavailableinapplica-tions. Nair et al. [24], for example, pointed out the need for methods that allow theeffective analysis of functional data and spatiotemporal data. The analysis offunctional data in process monitoring was recently reviewed by Woodall et al. [32].There are an increasing number of applications where somewhat more sophisticatedstatistical methods, such as these, are required in Six Sigma applications.1.8Relevance for ManagersSix Sigma can take on various denitions across a broad spectrum depending on thelevel of focus andimplementation. Amanagement canperceive it either as aphilosophy, a set of tools, a methodology, or as a set of metrics; Six Sigma is all ofthis. This chapter details all these points in an exhaustive manner highlighting theimportance of each from a project management point of view. The essence of SixSigma project is the necessity of defect reduction to the minimization of variationand then quality improvement. Therefore, the tools, tasks, and deliverables essentialfor the implementation of Six Sigma project are clearly suggested for better man-agement and business excellence.16 1 Six Sigma ConceptsExercises1:1. What is Six Sigma? What are the objectives of Six Sigma?1:2. Explain various perceptions of Six Sigma concept.1:3. State various tasks and deliverables associated with each phase of DMAIC.1:4. What is defects per million opportunities? How it helps tond the sigma levelof a process?1:5. Distinguish between a centered and off-centered process? What adjustment isdone tond the sigma level of such a process?1:6. What are the benets of Six Sigma quality philosophy?1:7. ExplainDMAICphilosophybydetailingvariousstatistical toolsappliedineach phase.1:8. Distinguish between Lean and Six Sigma. How does the operating philosophyof both differ?1:9. What is designfor SixSigma?Explain, howthetechniqueis appliedfororganizational excellence?1:10. Explain various tasks associated with each phases of DMAIC technique.1:11. Explain various deliverables associated with each phases of DMAICtechnique.1:12. What is the signicance of Leanor Leanmanufacturing?State importantfeatures of Lean philosophy.1:13. What is value stream mapping? How does it help to speed up a Lean process?1:14. What are the management roles of a Six Sigma Black Belt, Six Sigma MasterBlack Belt and Champion?References1. Basu, R.: Six sigma to operational excellence: role of tools and techniques. Int. J. Six SigmaCompetitive Advantage 1(1), 4464 (2004)2. Basu, R., Wright, J.N.: Quality Beyond Six Sigma. Butterworth-Heinemann, Oxford (2003)3. Brady, J.E., Allen, T.T.: Six sigma literature: a review and agenda for future research. Qual.Reliab. Eng. Int. 22(3), 335367 (2006)4. Breyfogle III, F.W.: Implementing sixsigma-smarter solutions usingstatistical methods.Wiley, New York (1999)5. Breyfogle, F., Cipello, J., Meadows, B.: Managing Six Sigma. Wiley Inter science, New York(2001)6. Coronado, R.B., Antony, J.: Critical success factors for the successful implementation of sixsigma projects in organization. TQM Mag. 14(2), 9299 (2002)7. Deming, W.E.: The New Economics for Industry, Government and Education. 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J. Qual. Technol. 36(3), 309320 (2004)18 1 Six Sigma ConceptsChapter 2Six Sigma Project Management2.1Project ManagementA project is a temporary endeavor to achieve some specic objectives in a denedtime[10]. Aproject mayvaryinsizeandduration, involvingasmall groupofpeople or large numbers in different parts of the organization. It is usually unique incontentandunlikelytoberepeatedagaininexactlythesameway.Projectman-agementisadynamicprocessthatutilizestheappropriateresourcesoftheorga-nizationinacontrolledandstructuredmanner toachievesomeclearlydenedobjectives, identies as strategicneeds conductedwithinadenedset of con-straints. A project involves many processes and each such process progresses withspecic objectives (see Chap. 3 for details). A project can be any of the followingtypes: Personal projects: Preparations for writing a thesis, books, dissertations; studentprojects; anyfamilyfunctions; conductinganexamination; conductingaliveshow, arranging a tour program, etc. Local projects: Organization of a public program, organization of a conferenceoraseminarprogram, anyvoluntaryprojectsexecutedbyNGOsandprivateorganizations, etc. Organizational projects: Construction of buildings or a highway, planning andlaunchinganewproduct, settingupanautomobileplant, establishinganewofce, investigatingcauseandeffect of aproductsdefects, brainstormingasession, organizing an audit check, etc. Projectsof national importance: Launchingavaccinationdrive, launchinganewsatellite, introducingaliteracycampaign/povertyremoval, preparationofannual budget, construction of metro rail/road transports, conducting a nationallevel sporting event, etc. Projects of global importance: Organizing peace missions, space explorations,environmental sustainabilitydrives, conductinganinternational level sportingevent, etc. Springer India 2015K. Muralidharan, Six Sigma for Organizational Excellence,DOI 10.1007/978-81-322-2325-2_219A project is identied through a project identication process. This is the stagewhere new opportunities and threats emerging in the environment are investigatedand suitable proposals that can be adopted by the organization are generated. This isdonethroughthegenerationof newideasbythecompanysthinktank. Brain-stormingisaveryeffectivetechniquefordoingthisexerciseinagroup. Brain-storming may be structured in which each member of the group is asked for his/heridea in a sequential manner. These ideas are then scrutinized for their viability ofexecution and implementation thereafter.Project characterization Every project involves various processes and these processes are characterizedby their inputs and outputs Theoutput ofthebusinessprocessesdependsonthestrategicplanning, cus-tomer surveys, competitive analysis and benchmarking of the process, etc. Forthesuccessinprojects,itisessentialforeveryoneinvolvedtocommittousing a common set of processes and procedures Thismakesthesharingofinformationconsiderablyeasier, particularlywhenworking across different sites, organizations, and countries.2.2SWOT AnalysisAfterhavingidentiedtheobjectivestobeachievedthroughaproject, itisgen-erallyworthwhiletoconduct astrengthweaknessopportunitiesthreats(SWOT)analysis so that the organizations strengths and weaknesses are highlighted and theopportunities and threats emerging from the environment are viewed in an objectivemanner. The purpose of this analysis is to be able to generate ideas exploring theemergingopportunities, guardingagainst thethreatswhilekeepingtheorganiza-tionsstrengthsandweaknessesinmind. Theparticipantsofbrainstormingmayalso be made a part of these exercises, so that they become aware of the require-mentsandlimitationsofthesystemtheyaredealingwith. Theextent ofconfor-mance of the various proposed solutions with the SWOT prole could also be usedto evaluate the various ideas after they are proposed during brainstorming. Some ofthe factors that ought to be considered while doing a SWOT analysis are as follows:Strengths Experience and expertise Financial position Capital raising capability Industrial contacts Foreign collaborations20 2 Six Sigma Project ManagementWeaknesses Lack of experience Lack of trained personnel Inability to cope with newer technologies Inability to raise huge investments Inability to forecast market trendsOpportunities Emerging technologies New products with new markets New processes with better features Special nancing schemes Government and other incentivesThreats Competitors Poor state of the economy Outdated process and technology Unprofessional management skills New products and services.Understanding the key customer, market, and operational conditions is input tosetting strategic direction. Identifying these components through a SWOT analysisalso helps identify the gaps in the projects (see also Thompson and Strickland [9]).2.3Project PhasesWeknowthat everyproject involvesvariousprocesses, andtheseprocessesarecharacterized by their inputs and output. In the previous chapter, we have discussedvariouscomponentsandcharacteristicsofaprocess. Theoutput ofthebusinessprocessesdependsonthestrategicplanning,customersurveys, competitiveanal-ysis, benchmarkingoftheprocess, etc. Forsuccessinprojects, itisessentialforeveryone involved to commit to using a common set of processes and procedures.This makes the sharing of information considerably easier, particularly whenworkingacrossdifferent sites, organizations, andcountries. Theprocesscanbebroken down into a number of denable phases with decision gates between each ofthe phases: Project conception Project denition Project planning2.2 SWOT Analysis 21 Project launch and execution Project closure Post-project evaluation.Theseactivitiesareoftenreferredtoaskeystrategiesas theymaycompriseseveralactualtaskscarriedoutbymorethanoneperson.Itisalsoexpectedthateach phase is carried out sequentially to generate useful data for decision making.Although each phase is treated as discrete with specic work to be completed, thisdoes not signify they are one-off activities. In reality, the phases are oftenrevisited during a project. Once a project is initiated, the need to reiterate some orall of the work done in the denition or planning phases is always a possibility asthe project moves ahead in the execution phase.For many organizations, project management is a way of management forchange. The idea for project will be created from the knowledge and experience ofthe organization, customer requirements, and market trend. The climate of projectexecution depends on the organizational culture, organizational structure, andbusinessstrategy. It isessentialforseniormanagerstocreateandworkcontinu-ously to sustain the climate for success. Failure to do this will be a disaster for theorganizationandthepeopleassociatedwiththeprojects. Collaborativeworkingacross the whole structure is a key to project success, as is recognition thatassigninganindividualtoaprojectteamisadedicatedassignmentofthewholeproject.Projects are anintegral component of SixSigma. Selecting, managing, andcompleting projects successfully are critical in deploying any systematic businessimprovement effort, not just SixSigma. Aproject shouldrepresent apotentialbreakthrough in the sense that it could result in a major improvement in the productor service. Project impact should be evaluated in terms of itsnancial benet to thebusiness, as measured and evaluated by thenance or accounting unit. Obviously,projects with high-potential impact are the most desirable. Thisnancial systemsintegration is standard practice in Six Sigma and should be a part of any DMAICproject, even if the organization as a whole is not currently using Six Sigma [6].2.4Alignment with the Business StrategyProjects andprograms areselectedonlyif theysupport achievingthebusinessstrategy and contribute to business growth. A carefully constructed business case isanessential document supportingthedecision. Someof theimportant strategicinputs are as follows: Forward planning Resource management Financial management Portfolio management.22 2 Six Sigma Project ManagementIn ordertostartanynewproject,it isessentialto knowthecommitments andliabilitiesoftheorganizationinprior. Thiswill decidethefutureofall ongoingactivitiesanditssuccesses. Theselectionofprojectsrequirestheorganizationtoplanaheadusingadequateintelligencegatheredfromthemarketplaceandcus-tomers. This will help to address the critical areas of potential business growth andlost opportunities. Adequate funding must be available to satisfy the budget of allactive projects. Otherwise, the chances of derailment of the projects become certain.It is also important to maintain a visible, authorized list of active projects and thosewaitingtostart, toinformeveryoneoftheprioritiesandrelativeimportanceofthose on the list. Timescale and completion targets need to be agreed to meet thebusiness and/or customer needs and plan the effective deployment of resources.2.5Project StakeholdersThe relationship in a project environment can only lead to success when there is aclear denition of ownership at each level in the organization with clearly denedroles and responsibilities. This avoids confusion and claries where authority existsto make decisions and avoid unnecessary slippage and delays in projects.According to Young [10], the people associated with a project can be: Someone who needs the benetsthe company senior management Someone w