六西格玛简介.ppt

6簡介,6SIGMA起源及主要概念6SIGMA組織及人員認證基本統計應用執行主要步驟D-M-A-I-CCaseStudy,QRA:2001/8/27,TheOriginsofSixSigmaItoriginatedinthe1980sasMotorolarespondedtothethreatofJapanesecompetitionwhichhadfarlowerdefectiverates.TheapproachspreadtoAlliedSignalandtoGeneralElectric,whoseChiefExecutiveOfficer,JackWelch,hasbeenthemostpassionateadvocateofSixSigma.Sinceintroducingitworldwidein1996,GEhasmadeover$1billionofcostsavings.,1979年，當時Motorola一位資深業務主管ArthurSundry在高階主管會議上說：Ourqualitylevelsreallystink!SixSigmaQualityProgram此名稱乃為Motorola工程師BillSmith所建議，為RobertGalvin所採納。,何謂6-Sigma?,Motorola:,衡量指標標竿研究願景Philosophy方法工具符號目標價值,s,3.4,.,s,DPMO,可用以計算與衡量任何流程,Sigma之另一稱呼為標準差,2000年達成6-Sigma水準4,1996-JackWelch,變成我們文化的一部份-成為我們生活的一部份.,59,WhereDoes“SixSigma”ComeFrom?,MikelJ.HarryoneoftheOriginalArchitectsPreviouslyHeadedQualityFunctionatABBandMotorolaNowPresident/CEOofSixSigmaAcademyinPhoenix,ArizonaHasConsultedforTexasInstruments,AlliedSignal(andothers)CurrentlyRetainedbyGEtoTeachtheImplementation,DeploymentandApplicationofSixSigmaConcepts&Tools,LearningfromThoseWhoHavehadSuccessWith6WillAccelerateitsImplementationatGE,WhatDoes“Sigma”Mean?,SigmaisaMeasureoftheConsistencyofaProcess,It(isAlsothe18thLetterintheGreekAlphabet!,Motorola公司認為數據是滿足顧客的關鍵，他們常說：1.如無法用數據表示我們所知的,那麼我們對它所知不多(Ifwecannotexpresswhatweknowinnumbers,wedontknowmuchaboutit)2.如果對它所知不多，就無法控制它(Ifwedontknowmuchaboutit,wecannotcontrolit)3.如果我們不能控制它，那只有靠運氣了(Ifwecannotcontrolit,weareatthemercyofchance),Why“SixSigma”?,ProvenSuccessfulin“Quality-Demanding”Industriese.g.,Motorola,TexasInstruments(manyprocessstepsinseries)ProvenMethodtoReduceCostsHighlyQuantitativeMethodScienceandLogicInsteadofGutFeelIncludesManufacturing&Service(closetocustomer)andProvidesBridgetoDesignforQualityConceptsHasSupportandCommitmentofTopManagement,ItWorks!,6有多小?,Sigma,PPM,0.002,0.5742,63.37,2,700,45,500,317,310,面積,一般教室2倍,約6甲地,約30個天安門廣場,略大於台北市,東莞市,台灣省的面積,時間,1秒鐘,4.8分鐘,9小時,半個月,約9個月,5年,6-Sigma狹隘解釋-DPPM,6Overview,6isSeveralOrdersofMagnitudeBetterThan3!,Sigma:AMeasureofQuality,6的品質水準,0.002DPPM,Cp=2,中心值1.5的偏移,3.4DPPM,Cpk=1.5,或用DPMO(DefectsPerMillionOpportunities)表示,偏移1.5,在動態的真實世界中，每一件事都在不停的變化著溫度溼度工具的磨耗原料的差異.1.5乃由機率、估計、經驗而來,參考資料:Evans,D.H.(1975):StatisticalTolerancing:TheStateoftheArt,PartIII.ShiftsandDrifts.,6的四個假設,常態分配1.5偏移和已知缺點乃隨意分佈，且不同零件製程相互獨立,品質改善的流程,1.定義產品或服務2.鑑定顧客及其需求3.列出滿足顧客需求所需之條件4.定義(規劃)流程5.防範流程錯誤並消除浪費6.確保持續改善,廣義解釋-流程改善(改造)/設計,Six-Sigma如何創造不一樣局面?,願景(Vision)哲學(Philosophy)積極目標(Aggressivegoal)量化指標(Metric,standardofmeasurement)方法(Method)工具用於:顧客焦點(Customerfocus)突破性改善(Breakthroughimprovement)持續改善(Continuousimprovement)人員參與(PeopleInvolvement),Six-Sigma願景,Six-Sigma的願景是將我們所做的每一件事,透過達成Six-Sigma水準的表現,交付世界級品質產品或服務以取悅客戶.,Six-Sigma哲學,Six-Sigma哲學是應用結構化、系統化觀點於我們事業各嶺域達成突破性改善,推行6-Sigma之必要條件重點攻擊與變格管理相聯接依核心流程(非功能)組織黑帶或碩士級黑帶儘量聯接與事業相關重點,共同與言追求即早勝利(大且易見)支持基礎結構/追溯系統改變衡量系統以更有效推動專案行動選擇與工作直接相關專案高層參與-克服障礙,品質改善的流程,1.定義產品或服務2.鑑定顧客及其需求3.列出滿足顧客需求所需之條件4.定義(規劃)流程5.防範流程錯誤並消除浪費6.確保持續改善,Six-Sigma整合改善、設計與績效管理方法論,Six-Sigma所使用的三個主要方法論:流程改善(DMAIC)、流程設計與再設計(DFSS)與績效管理,DMAIC用以改善現有流程、產品、服務、設計等等DFSS用以產生新的流程、產品、服務、設計等等績效管理是一個系統用以將策略連接戰術、設定優先順序、資源整合持續達成DMAIC與DFSS目標,流程改善方法論,流程設計與再設計方法論,績效管理方法論,產品變異的來源,設計製程材料元件,6品質方案的架構,5階段問題分析解決流程(DMAIC),提高目標,另一主題,第一階段第二階段第三階段第四階段第五階段,管制(Control),改善(Improve),分析(Analyze),衡量(Measure),定義(Define),選擇專案成立專案小組確認CTQsY,定義衡量指標($?)衡量系統驗證,定義不良基準線設定目標確認X,重點少數xs效果測試(PilotSoln)Y=f(x),確認效果持續性,So.WhatisSixSigma?,“THESIXSIGMABREAKTHROUGHSTRATEGY”,DMAIC,KeyCustomerOpportunitytogroworthreatofloss,Isthecustomertellinguswhentheissueis?,SixSigmaProjectIdentified,Define-Scopeit,Measure-Howarewedoing,Improve-Implement,Control-Makesureitsticks,Problemhasquickfix?,Fixit!,Analyze-RootCause,Preliminarylookathowwethinkwearedoing,Setupcustomermeeting,Define/RefineCTQsWhatsimportanttothem?,HowarewedoingontheseCTQs,Howcanweimprove?,SixSigmaIsAGrowthTool,YES,YES,NO,NO,D,M,A,I,C,CustomerImprovementContinuousGrowth,Six-Sigma架構,MOA(MarketOpportunityAnalysis),事業策略展開BusinessStrategyDeployment,推行組織(ImplementingOrganization),跨功能團對合作Cross-functionalTeaming,(GainingCommitment),(CultureChange),(InformationTech),(TrainingSystems),確認關鑑業務流程IdentifyingCriticalBusinessProcesses,專案選擇與審查(ProjectSelection&Charting),專案管理(ProjectManagement),DFSSFlow(DesignforSix-Sigma),DMAICFlow,意識(Awareness),統計工具(StatisticalTools),管理工具(ManagementTools),推廣(Promotion),6-Sigma基礎架構,市場機會分析,全體承諾,訊息科技,文化改變,訓練體系,Structure,6ProjectswiththeGEBusinesses,ChampionsorLeadersarethoseseniormanagerswhowillensurethatresourcesareavailablefortrainingandprojects,andwhowillbeinvolvedinprojectreviews.,Champion,MasterBlackbelt,Blackbelt,Greenbelt,扮演角色,綠帶/黑帶(GB/BB),碩士黑帶(MBB),負專案全責-黑帶(專職)/綠帶(兼職)專注於1-2專案小組依專案特性挑選出,流程盟主(ProcessChampion),專職之職位協助多個專案小組開發導入專家資源,管理之責任專注於一個關鍵流程或次流程被BU流程改造委員會依流程性質而選出,專案小組領導技巧專案管理技巧問題分析與解決技巧,跨功能工作經驗分析/技巧專長流程之指導/監督/教育技能,負責流程功能/目標達成/維持關鍵項目之管制/主導定期流程審查負責跨功能介面問題與議題之解決,跨功能認識與了解溝通/談判技巧原因分析技能專案小組領導技巧,負責專案進度/小組工作計劃,並將之與管理層級聯接開發衡量與管制系統(如,資料蒐集計劃/流程管制表等),開發BB/帶動專案小組成功/提供流程改善與統計技巧的專長亦可能被指派加入流程管理小組,專長,職責,敘述,選擇核心專案小組成員訣竅(coreteam)*理想人數:57人*訓練展開之前先選定小組成員與黑帶,再讓這些人一起受訓*取得各階主管支持的承諾*流程盟主最好來自事業部流程改造委員會,以利溝通與學習*專案執行期間,專案小組成員花在專案的時間可至每週20小時-每週小組會議為46小時-每週改善專案為1016小時*改善專案包括延伸小組成員,包括事業部財務代表與其他重要資源,Sub-ProcessOwners,ProcessOwner,ProcessTeam,MBB,ProcessChampion,Members,BB(GB),ImprovementTeam,MBB,ProcessManagementTeams,Improvement/DesignProjects,BU6-SigmaCouncil,ProcessManagementSystem&Organization,Process,Roles&Responsibilities,Measurement,ProcessReview,Linking&Leveraging,ProcessChampion,35,6個Sigma管理(6Program)理念:品質是由企業文化改變出來的策略:創新(Innovation)/突破(Breakthrough)/組織運作/衡量(measures)例:流程簡化(Simplification)重點:企業文化塑造/大量資源投入改造/有效量化執行成果(KPIs$),基本統計分析工具,常態分配(NormalDistribution)變異數與標準差(Variance&Sigma)特性要因圖(CauseandEffectDiagrams)品質機能展開(QFD)量測系統分析(GaugeR&R)實驗計畫(DOE)變異數分析(ANOVA)相關與回歸分析(Correlation&Regression)管制圖(ControlChart)電腦應用程式(Computersoftware),常態分配(NormalDistribution),標準差一群觀察值與平均數之差，稱為離均差，各離均差之平方的平均數（即變異數）再予開方所得即為標準差。,Z-ScaleofMeasure,Z,=,AUnitofMeasureEquivalenttotheNumberofStandardDeviationsthataValueisAwayfromtheTargetValue,-3.0,-0.5,3.0,Z-Values,USL,LSL,2.5,0.5,3.0,=ProcessMean,Z,T,Target,0,A3Process,ProblemSolvingApproach,6HelpsusIdentifyandReduceVARIATIONdueto:-InsufficientProcessCapability-UnstableParts&Materials-InadequateDesignMargin,Define,Whatdowewanttoknow?-Whatisourproblem?-Whatisourdefect?,PracticalProblemProjectCTQsSolidY,SpecDefinition,andDefectDefinitionBuildingaJustifiableBusinessCaseApprovedCharter(R0),WhatdidwelearnDowehaveaviableproject?,特性要因圖,The%VariationDuetotheMeasurementMethodGAGER&R,GAGE:TheinstrumentusedformakingMeasurementsthatwewanttovalidate.,REPEATABILITY:DoesthesameoperatorgetthesameresultsWhenmeasuringthesamepartseveraltimes?,REPRODUCIBILITY:Dodifferentoperatorsgetthesameresultswhenmeasuringthesamepartseveraltimes?,CAUTION:ACalibrationStickerdoesnotimplythatGageR&Risacceptable!,Measure,Whatdowewanttoknow?,StatisticalProblemProjectY,SpecDefinition,andDefectDefinitionGageR&RonYDataProcessMapL1toShowZValueswithLinktoFinancialsRationalizationforFocusedYDescriptiveStatisticsforFocusedY,WhatdidwelearnMeanproblem?Variance?Both?,時間,GOOD,BAD,3Sigma,6Sigma,BreakthroughImprovement,Six-Sigma突破,表現,如果我們充份瞭解與掌握X,為何我們要持續測試與檢驗Y?,Y相依(Dependent)輸出(Output)結果(Effect)不良結果(Symptom)監測(Monitor),X1.Xn互相獨立(Independent)輸入(Input-Process)原因(Cause)問題(Problem)控制(Control),為了獲得好的結果,我們是否要專注於Y或X的行為?,f(X),Y=,專注於X而非Y,SixSigma焦點,CTQs(成本,品質,交期,顧客滿意度)每單位缺點數複雜度DPPMRolledThruputYieldSix-Sigma分數流程底限(Baseline)流程標竿(Benchmarking)KPOVsKPIVs偏移與漂移(Shift&Drift),Six-Sigma衡量指標,現有衡量指標,良率RMA數量返修數量顧客抱怨數?,LeadershipMustAsktheRightQuestionsWhatGetsMeasuredGetsManaged,Six-Sigma衡量指標(Metrics),Six-Sigma衡量指標-定義,CTQs:重要顧客滿意參數.通常包括品質,成本,交期等.KPOVs:關鍵流程輸出變數(KeyProcessOutputVariables).流程中由KPIVs反應矯正措施之結果KPIVs:關鍵流程輸入變數(KeyProcessInputVariables).直接與其他KPIVs相關,影響改變流程輸出之變數,ChangingFocusFromOutputtoProcess,IdentifyingandFixingRootCausesWillHelpusObtaintheDesiredOutput,f(X),Y=,SomeBasic6-RelatedTools,ScatterDiagram,OverSlept,CarWouldNotStart,Weather,FamilyProblems,Other,ParetoDiagram,FrequencyofOccurrence,ReasonsforBeingLateforWork,ArrivalTimeatWork,TimeAlarmWentOff,Analyze,Whatdowewanttoknow?,StatisticalProblemUnderstoodLinkProcessMaptoFishbonew/C,N,XLabelingEnsureDataisCollectedforAllXsDrillDowntoVitalFewXsviaANOVA,GLM,T-test,F-testListofVitalFewXsQuantifiedFinancialOpportunities,WhatdidwelearnWhatwerethecausalXs?Howdidweidentifythem?,PM/CE/CNX/SOP,ProcessMapping,Why?,*ProcessvisualfoundationforcurrentsituationandanalysisAidsinidentifyingbottlenecks,redundanciesandwasteLookforNonValueAddLookforVariables(CNX),How?,DeterminebeginningandendofprocesstobemappedInvolvepeopleknowledgeableabouttheprocessBrainstormsteps&groupinmajorprocessareasLayoutactivitiesinsequenceValidatebyphysicallywalkingthroughprocess,PM/CE/CNX/SOP,CE:Cause&EffectSourcesofVariation,Output(s)&Specs,PeopleMaterialMachine,XC,CN,C,N,X,X,MeasurementMethodEnvironment,Everyvariableonthediagramshouldbelabeledaseither:C=ConstantN=NoiseX=ExperimentalvariableorFactor,PM/CE/CNX/SOP,SOP:StandardOperatingProcedures,StandardOperatingProcedurearerulesthatwedefinetoensurethatwehaveConsistentprocessesineverythingwedo.BasedongoodjudgmentCommonsenseEngineeringknowledgeRememberISO9000!Makesurewehavedefinedprocessesandthattherulesarebeingobeyedbyall.,數據分析,1.Samplesizerisk,Istheriskofsaythereisadifferencewhentherereallyisntone(生產者冒險率)Istheriskofnotfindingadifferencewhentherereallyisone(消費者冒險率)/ishemagnitudeorsizeofthedifferencebeentested.Thisissometimescalledthetestsensitivity.,ABasicSampleSizeTable,AppliestoContinuousDataOnly,/,Forexample:The1stadhesivehasanaverageof13.2andastandarddeviationof3.27ThepracticalsignificanceissuchthatanyalternativeAdhesivemusthaveanaveragestrengthof20ormoretomakethechangeworthwhile.Q:For=5%&=10%whatshouldbethesamplesizeineachleveloftheexperiment?,Ans:Howbigofachangeisimportant?/=(20-13.2)/3.27=2.07=5%=10%Sofollowthetablewefindthesamplesizeis5,2.T-test:ComparingMeans3.F-test:ComparingVariances(Between2Groups)4.ANOVA:(AnalysisOfVariance)(Betweenmulti-groups),Improve,StatisticalControlPoka-YokePlan(ifApplicable)ConfirmedVitalXsAreTheyStatisticallySignificant?SampleSizeCalculationForConfirmationRunDOEPlan(ifApplicable)RegressionEquationLinkedtostatisticalProblemSOPChangesand/orOptimalSolutionIdentifiedPlantoImplementSOPChangesand/orOptimalSolution,WhatcontributiondideachvitalXhavetotheY?HowcanwecontroltheXs?,Whatdowewanttoknow?,Howdowedetermineamodel,Correlation&Regression,Correlationtellsifyouhavearelationshipbetweentwovariables(YandX,ortwoXs)Regressionisusedtoidentifythenatureoftherelationship,andbeabletopredictYwhilebetterunderstandingYandpossiblyimprovingthecontrollabilityofY,Correlation,Correlations(Pearson)Correlationofpullandtemp=-0.978,RegressionAnalysis(Minitabsoftware)Theregressionequationispull=353-2.30tempPredictorCoefStDevTPConstant353.1113.5626.050.000temp-2.295200.09001-25.500.000S=0.3460R-Sq=95.6%R-Sq(adj)=95.4%AnalysisofVarianceSourceDFSSMSFPRegression177.83277.832650.280.000Error303.5910.120Total3181.423UnusualObservationsObstemppullFitStDevFitResidualStResid121509.31229.97520.1181-0.6630-2.04R311514.97785.84380.0864-0.8660-2.59R,DOE(Designofexperiment),1.篩選主要因子2.尋找最佳因子組合3.結果再現性驗證,找尋最佳之生產條件(製程參數),DesignofExperiments,6Overview,SCREENING,OPTIMIZATION,CHARACTERIZATION,ForExperimentsInvolvingaLargeNumberofFactorsUsefulinIsolatingthe“VitalFew“fromthe“TrivialMany”,ForExperimentsInvolvingaRelativelySmallNumberofFactorsUsefulWhenStudyingRelativelyUncomplicatedEffects&Interactions,ForExperimentsInvolvingOnly2or3FactorsUsefulWhenStudyingHighlyComplicatedEffects&Relationships,DOEisMoreEffectiveThanTestingOneFactorataTime,Control,Whatdowewanttoknow?,StatisticalControlPoka-YokePlan(ifApplicable)MeasurementofFinalCapabilityUsingConfirmationRunComparisonofBeforeandAfterDistributionsHowDoYouControlorPoka-YoketheVitalXs?IstheLearningTransferrableAcrosstheBusinessWhatsthePlan?WhoOwnstheProjectDocumentationFile?FinalFinancialResultsSignedOffWhatSpinOffProjectsAreThere?,Howwillthischangethewaywework?,MistakeproofingFMEAProcessMonitor(SPC,Controlchart)Riskvs.Benefit,Controltools,ShortTermCapability,ShortTermCapabilityRatio,(Cp),Cp=,LSL,-,6,USL,Example,6,3.0,-,(-3.0,Cp=,Cp=,1,LSL,USL,2.5,0.5,3.0,ProcessMean,T,Target,A3Process,ThePotentialPerformanceofaProcess,ifitWereonTarget,LongTermCapability(Cpk),LongTermCapabilityRatio,Example,Cp=,1(previouschart),Target,=,-0.5,=,0,Cpk,1-,(-0.5,-,0,3,=,Cpk,=,0.83,-,Off-TargetPenalty,ThePotentialPerformanceofaProcess,CorrectedforanOff-TargetMean,LSL,USL,2.5,0.5,3.0,ProcessMean,T,Target,A3Process,LCL,UCL,RangeChart,SomeBasic6-RelatedTools,MonitorsChangesinAverageorVariationOverTime,Riskvs.Benefit,Benefit,Low,High,Low,Med,High,Risk,1,2,2,PerformConfirmationRuns,3,3,Justdoit2.Probablystop3.“Hireaconsultantunlessyouhavehighconfidenceandexperience”,23456,308,53766,8076,2102333.4,PPM,SIGMALEVEL,DEFECTSperMILLIONOPPORTUNITY,IRSTaxAdvice,BestCompanies,AirlineSafety,AverageCompany,GE,AverageCompanyin3to4Range,SomeSigma“Benchmarks”,突破策略,A,B,C,D,E,F,G,改善專案,突破要項,流程認知,定義,衡量,分析,改善,控制,產品能力分析,流程能力分析,專注於Y,專注於X,目標=Y=f(X1,X2,.,Xn),DMAICBlackBelts展開改善方法,定義Define,衡量Measure,分析Analyze,改善Improve,管制Control,1.建立專案審查小組2.確認支持者/小組成員/各類所需資源3.實施先期作業,4.確認專案小組目標5.定義現狀6.收集與展現資料,7.決定流程/製程能力8.確認變異來源9.確認問題,10.產生改善構想11.決策評估12.進行實驗13.矯正計劃14.實施15.效果確認,16.管制計劃展開17.持續監控成孝18.標準化/防呆,專案審查工具ProjectIDTools專案定義表格專案管理流程SSPI工具箱,SSPI工具箱ProcessMapping價值分析腦力激盪優缺點列舉法多數表決法柏拉圖魚骨圖QFDFMEA查檢表RunCharts管制圖GageR&R,Cp&Cpk研究多變量統計分析BoxPlotsMarginalPlots假設檢定實驗設計法交互作用分析迴歸分析變異數分析(ANOVA)KJ法魚骨圖FMEA,腦力激盪BestPracticesBenchmarking實驗設計法/田口方法假設檢定ProcessMapping樹狀圖(TreeDiagrams)計劃評核術(PERT)PDPC/FMEA甘特圖,查檢表RunCharts直方圖散佈圖管制圖柏拉圖內部稽核審查會Poka-Yoke,ProblemSolvingApproach,KeyComponentsof“BREAKTHROUGHSTRATEGY”,IdentifyCTQ&CTP(CriticaltoProcess)VariablesDoProcessMappingDevelopandValidateMeasurementSystems,BenchmarkandBaselineProcessesCalculateYieldandSigmaTargetOpportunitiesandEstablishImprovementGoalsUseofParetoChart&FishboneDiagrams,UseDesignofExperimentsIsolatethe“VitalFew”fromthe“TrivialMany”SourcesofVariationTestforImprovementinCenteringUseofBrainstormingandActionWorkouts,SetupControlMechanismsMonitorProcessVariationMaintain“InControl”ProcessesUseofControlChartsandProcedures,AMixofConceptsandTools,WillAlsoIntegratewithNPIProcess,DisciplinedChangeProcess,ANewSetofQUALITYMEASURES,CustomerSatisfactionCostofPoorQualitySupplierQualityInternalPerformanceDesignforManufacturability,WillApplytoManufacturing&Non-ManufacturingProcessesandbeTracked&ReportedbyEachBusiness,Target,USL,LSL,Target,USL,LSL,Target,USL,LSL,CenterProcess,ReduceSpread,Off-Target,Unpredictable,On-Target,ProblemSolvingApproach,“LowerSpecificationLimit”,“UpperSpecificationLimit”,LessVariationMeansFewerDefects&HigherProcessYields,Baselining&BenchmarkinganExistingProcess,p(x),Defects,Benchmark,Baseline,Entitlement,Baselining=CurrentProcess/Benchmarking=UltimateGoal,Why6-Sigmasosuccessful?*Itsseeking“breakthrough”ratherthan“improvement”.*Topmanagementinvolvement(Champion)*Focusoncross-functionalcriticalbusinessprocesses*Full-timemanpowerdedication*Quantitativedataoriented-$(datastratificationandconfirmation)*Alotoftraining(especiallystatisticaltraining)*P-D-C-A,第9章：推行6-Sigma成功關鍵因素*尋求“突破”而非“改善”*高階主管積極參與(Campaign)*著眼於跨部門/功能重要事業流程*全職(Full-time)人力專注活動推動*量化指標導向$(datastratificationandconfirmation)*許多訓練課程(尤其是統計課程)*非常注重Check與Act(P-D-C-A),123,6SigmaisProcessKnowledge,6sigma,Science=Processknowledge=6sigmaquality=SuccessArt&Magic=Confusion=FireFighting=WasteWeveAllSeentheResults:Teams&/orIndividuals*Flounder*Panic*Fail*Cover-up,Moreprocessknowledgewillimproveourcompetitiveness,APracticalExample(The“Cookbook”),6Overview,6.andBakingBread,Usinga12StepProcess,WhatisImportanttotheCustomer?RiseTextureSmellFreshnessTaste,Y=Taste!,Measure,HowCouldWeMeasureTaste(Y)?PanelofTastersRatingSystemof1to10Target:AverageRatingat8Desired:NoIndividualRatings(“defects”)Below7,Y=12345678910,Target,Defects,Worst,Best,But.IsthistheRightSystem?,Measure,HowCouldWeApproachThis?BlindfoldedPanelRatesSeveralLoafSamplesPut“Repeat”PiecesfromSameLoafinDifferentSamplesConsistentRatings*onPiecesfromSameLoaf=“Repeatability”ConsistentRatings*onSamplesAcrossthePanel=“Reproducibility”,“Repeatability”&“Reproducibility”SuggestValidMeasurementApproach,PanelMember,Loaf1Loaf2Loaf3,A589B491C492D898E482F591G892,*Within,OneTasteUnit,Measure,Thisisa3Process!,7Defects(ratingsbelow7),24Ratings(fromourpanel),=,.292,292,000Defectsper1,ooo,oooLoaves,OR,Analyze,HowDoWeApproachThis?BakeSeveralLoavesUnder“Normal”ConditionsHaveTasterPanelAgainDotheRatingAverageRatingis7.4ButVariationistooGreatfora6Process,HowdoweDefineImprovement?BenchmarktheCompetitionFocusonDefects(i.e.tasterating7)DetermineWhatisan“AcceptableSigmaLevel”SetImprovementObjectivesAccordingly,Maybea5ProcessWillSuffice!,1,000,000-100,000-.10,000-.1,000-.100-.10-.1-,234567,“BETTERBREAD”BakingProcess,BestCompetitor,RangeforImprovement,DefectsPerMillion,SigmaScale,Analyze,HowdoweDeterminethePotentialSourcesofVariation(Xs)?HavetheChefsBrainstormSomeLikelyOnes