六西格玛绿带培训教材(英文版)ppt课件

版本:1.00日期:May2003,6西格玛绿带培训教材ONE,1,DAY1第一天(定义阶段):-6西格玛及精简优化与COQ(質量成本）的关系COQ的脑力风暴-FirstPassYieldExerciseII初始直通率的練習IPO（輸入輸出流程）andflowdiagram（IPO和流程圖）FlowanalysisofdroppingcardsontotargetRepeatingtheexercise重復練習Resultsanddiscussions結論和檢討-西格玛培训中的某些质量改进工具脑力风暴技术第一天結束wrapup通過以上的教學引導學員對品質成本的認識運用六西格瑪就是有效的降低品質成本,課程安排,2,DAY2第二天(VarianceReduction降低变差的理解):-ThepowerofPlatochartandthe80/20rules柏拉圖表的功能和80/20的規則ConstructionofaPlatoChartusingcomputerflowdiagramanditsassociatedsymbols流程圖和其制作符號含義Two实例offlowdiagram(usingacommonscenario)兩個流程圖的實例（使用通用的情節）Barriersthathinder6西格玛implementation阻礙開展執行六西格瑪的因素-Break-WhatisFMEA什么是FMEAExampleofFMEA關于FMEA的實例GroupexerciseonFMEAofbarriersto6西格玛implementationFMEApresentations關于FMEA的介紹-Lunch-Conceptofprecisionandaccuracy對准確和准確的理解（Cp和Ca）Howdoesitlinktothemeanand标准偏差（如何將平均值和標准偏差聯系起來）Precisionandaccuracyexample(i.e.Selectionoffundmanager准確和精確的實際例子CatapultexerciseI彈弓拋物發射器的思維練習一-Break-Introducingconceptofvariancereduction(i.e.PF/CE/CNX/FMEA/SOP)介紹降低變差的觀念Variancereduction脑力风暴exerciseforCatapult用彈弓發射器進行降低變差的腦力風暴練習CatapultexerciseII彈弓拋物發射器思維練習二ComputationofCatapultexerciseresultaftervariancereduction評估計算彈弓發射器游戲中的數據來了解降低變差的含義Discussionofvariancecontributors討論降低變差的意義第二天wrapup在以上學習中通過彈弓發射器游戲的了解在游戲中掌握了解在六西格瑪中(VarianceReduction）降低变差重要性,3,DAY3(MeasurePhase測量階段):Recapofstatisticalterminology全新的統計學朮語Histogramandanormaldata對直方圖和常態數據的理解Constructionofhistogram對直方圖的解釋Transformationofdata數據的轉換CalculateCp,Cpkfromnon-normaldata計算非正態數據的Cp,Cpk-Break-Theimportanceofgoodmeasurement正確的測量方法的重要性Direct和indirectmeasurement(i.e.Introductiontoscatterdiagram)Riskofwronginterpretation錯誤解釋的風險-Underandvarianceconceptinmeasurementsystem在變異范圍內的測量系統的觀念-IntroductiontoGaugerepeatabilityandreproducibility(GRProject/CandidateSelection,CandidateSelection,Tofillin;Characteristicsof6西格玛candidateScore-sheet和SummaryLeadershipValuesScore-sheet6西格玛CandidatesLeadershipValuesSummary6西格玛Candidates,ProjectSelection,Tofillin;6西格玛ProjectSelectionSummaryEaseofImplementationAssessmentROIImpactAssessment,Candidatesmustscoregreaterthan2.5ptsforeachtoqualify,Candidatesmustscoreatleast0.9ptsintheinthe6西格玛ProjectSelectionSummarytoqualify,6西格玛ProjectSummary,Matchingrightprojecttotherightpeople,30,Phase2;6西格玛培训和applicationof6西格玛工具s,CollectBaselineDataonProject,yieldCOQCostCycleTimeInventorylevel,Tofillin;6西格玛R0ProjectReviewSheet6西格玛COQTemplate6西格玛ProjectProgressReportTogetallrelevantpartiesapprovalsignatories,Attend6西格玛GB/BBAcademic培训,Applicationof6西格玛工具toProject(s),PF/CE/CNX/SOPsFMEAMSAPARETOPROBABILITYDISTRIBUTIONANOVADOESTATISTICALINTERVALSPC,CreateCertificationTemplate,FollowDMAICPresentationSummaryRevA,tocompleteeachphaseoftheproject,流程to6西格玛GB/BBcertification,31,Phase3;CertificationofCandidate,CompleteClosureTechnicalReport,Presentationof6西格玛CertificationProject(s),SiteAssessmentofProject(s),IssuePlaque/CertificateAchievementtocandidate,UpdateCandidateLORCareerProfileon培训和Recognition,FinancetoverifyprojectsavingsChampions和MBBtoassesscandidateunderstanding和applicationof6西格玛工具sCandidateCertificationEvaluationForm,流程to6西格玛GB/BBcertification,FinancetoverifyprojectsavingsChampions和MBBtoassesscandidateunderstanding和applicationof6西格玛工具sCandidateCertificationEvaluationForm,32,RequirementsforCertification,Completionof6西格玛培训courseSuccessfulprojectcompletion(goalachievement和documentation)Demonstrationontheunderstandingof6西格玛工具sEffective和successfulcompletionofstepsto“holdthegain”Completionofeachprojectwithin1yr绿带Certification;completionof2projectswithminimumsavingofUS$25,000perproject黑带Certification;completionof2projectswithminimumsavingofUS$100,000perproject,交付ablesforCertification,Demonstrationofsix-sigmathough流程Completionof6西格玛R0ProjectReviewSheetCompletionof6西格玛ProjectProgressReportCompletionof6西格玛COQTemplateCompletionofDMAICPresentationSummaryCompletionofClosureTechnicalReport,33,Certification结构,CandidateCertificationBoardSiteLeaderChampionsMaster黑带CertificationBoardReview流程CandidatetodistributetheClosureReportSummarytotheboardatleastoneweekbeforethereviewdate(maybewaivedatthediscretionofthesiteleader)MBBtoactasthechairoftheboardCandidatetopresentprojectdetailsusingusingthought流程mapwithemphasisonhoweach工具wasappliedQuestions,clarifications和reviewbytheboard,34,Certification结构(cont),BoardmemberstoratecandidateusingCertificationEvaluationFormPassif;CandidateTechnicalAssessmentisgreaterthan20ptsforGreenbelt和greaterthan40ptsforBlackbelt流程Variation和MeasurableResultsEvaluationisatleast4ptsforeachcategoryInformcandidateoftheoutcome,35,SampleForms,Characteristicsof6西格玛Candidates,LeadershipValuesScore-sheet,36,SampleForms;LeadershipValuesSummary,37,SampleForm;ClosureTechnicalReport,38,SampleForm;CandidateCertificationEvaluationForm,39,Definitionofa流程A流程isanactivitywhichutilizeinputsfromexternalsource和transformthemintodesiredoutput(s).,Example:Manufacturing流程es(i.e.wirebonding,injectionmolding,glasssawing)Financial流程es(i.e.doublebookkeeping,产品costing)HR流程es(i.e.recruiting,ranking和appraisal,培训)Dailyactivity(i.e.parkingacar,buyinglunch,brushingyourteeth),40,IPO(Input-流程-Output)Diagram,PeopleMaterialEquipmentPoliciesProceduresMethodsEnvironment,PerformaserviceProducea产品Completeatask,utilizingexternalINPUTStoachievethedesiredOUTPUT(S),Avisualrepresentationofa流程whichlistsinputvariables和outputcharacteristics,41,WhatisthepurposeofIPO,Ahighlevelinterpretationofa流程,whichenableeaseofunderstanding,throughoutliningthe关系hipsbetweeninputvariables和outputresponse(s).,42,Whatisadistribution?,Itisapatternformbythecollectionofdata,groupingtheoutcomehorizontally(x-axis),和indicatestheobservedfrequencyoftheoutcomevertically(y-axis).Instatistic,thisgenerateatheoreticalpatternwherebyinformationofentirepopulationcanbeobtainedfromobservinglimitedsamples.,43,CharacteristicofanormaldistributionIthasasinglepeak和abellshapecurveItisadistributionforcontinuousdata-Themean(average)isisatthecenterofthecurveThevariancedescribethespreadingofdata,44,为什么isdistributionimportanttoa流程Theoutputofa流程canmostofthetimeassociateswithastatisticaldistribution,givingopportunityforengineertoanalyzethedatastatistically,hencearrivingconclusionwithastatisticalconfidence和atalowercost.,45,流程CapabilityStudy,流程capabilitypotential,CpBasedontheassumptionsthat:,Cp=流程capabilitypotentialCpk=流程capabilityindexItisameasurementofthecapabilityofa流程,byindexingthe流程naturaltolerancewithrespecttothedevicespecification(i.e.customertolerance),流程isnormal,Itisa2-sidedspecification,流程meaniscenteredtothedevicespecification,Spreadinspecification,Naturaltolerance,46,流程CapabilityIndex,Cpk,1.Basedontheassumptionthatthe流程isnormal2.Anindexthatcomparethe流程centerwithspecificationcenter,Thereforewhen,Cpk0.30CheckifthespecificationlimitsisreasonableorattainableIfP/TOT0.30Checktheitemsthatwerepartofthemeasurementsystemstudy和seeiftheyarerepresentingatleast80%oftheactualtotal流程variability.CheckIfthemeasurementsystemequipmentisthebestcondition和isperforminguptospecifications.(ordowehavenochoicebuttouseit)IfP/TOLorP/TOTcloseto0.3butifthe流程isoperatingathighcapabilityCpk2,thenthemeasurementsystemismostprobablynottheproblem,ImprovingPoorMeasurementSystem,135,Discussingrouponhowtomeasurethediameterofthecatapultball和determinethe流程steps.InyourgroupmeasurethecircumferenceofthegroupofCatapultBall提供dtoyou.Eachgroupistomeasurethe10Ballsthreetimes,n=3.Collectthedatafromtheothertwogroups.Oncethedataisavailable,combinetheresult和conducttheGRforstatisticaldependenceevent,=0.3/0.4=0.75,164,SolvingtheproblemwithatableWhatistheprobabilitythatadrawnboxisstriped,giventhattheboxisred?,Symbolically=P(Striped|Red),Whatistheprobabilitythatthedrawnboxisred?,Whatistheprobabilityofdrawingaredstripedbox?,Whatistheconditionalprobabilityofthedrawnboxtobestripedwhendrawnred?,=P(Striped和Red)/P(Red)=0.4/0.6=0.667,165,“Jointprobabilitiesunderstatisticaldependence”,Weknowthattheformulaforconditionalprobabilityunderstatisticaldependenceis:P(A|B)=P(A和B)/P(B),IfweshiftP(A和B)totheleft和P(A|B)totheright,wewillhave:P(A和B)=P(A|B)xP(B),166,Withreferencetothescenarioof10boxesinabag,whatistheprobabilitytodrawagreendottedbox?P(Dotted和Green)=P(Dotted|Green)xP(Green)=0.75x0.4=0.3,167,PosteriorProbability(BayesTheorem),Posteriorprobabilitydefinesthatcertainprobabilitieswerealteredafterthepeopleinvolvedobtainedadditionalinformation.Thisnewprobabilitiesareknownasrevised,orposteriorprobabilities.,AChefhasformulatedanewchickenrecipe和basedonhisexperiencewithformulatingasteakrecipe,theprobabilityofsellingarecipewellistoincreasetheamountofgarlicpowderintheingredients.However,afterintroducingthenewrecipeforoneweek,hefoundthatthenewchickenrecipedoesnotsellaswellastheoldone,hemustthereforerevisehispriorprobabilities和useotheringredientsintherecipe.,CalculatingposteriorprobabilitiesAssumingthatwehaveequalnumbersof2typesof“biased”diceinabowl.OnetypeofthebiaseddiewillrolloutavalueofFive40%ofthetime,和theothertypewillrolloutthevalueFive,70%ofthetime.Ifonediceisdrawn和rolltothevalueFive,whatistheprobabilitythatitisatype1dice?,168,Type1Type2,0.40.7,Calculatingposteriorprobabilities(Cont),Tofindtheprobabilitythatthedicewehavedrawnistype1,weshouldadopttheformulaforconditionalprobabilityunderstatisticaldependence:P(B|A)=P(BA)/P(A),P(Type1|Five)=P(Type1,Five)/P(Five)=0.20/0.55=0.364,Thereforetheprobabilityofdrawingatype1diceis0.364,169,Calculatingposteriorprobabilities(Cont),Assuch,whatistheprobabilityofdrawingatype1dicebeforethedicewasrolled?0.5,Whatistherevisedprobabilityofdrawingatype1diceafterthedicewasrolled和havingavalueofFive?0.364,Ifwearetorollthesamediceagain和achieveavalueofFive,whatistheprobabilitythatitisatype1dice?,P(Type1|2Fives)=P(Type1,2Fives)/P(2Fives),Type1Type2,0.4x0.4=0.160.7x0.7=0.49,=(0.08/0.325),=0.246,170,Furtherexampleofposteriorprobabilities更多的實際例子,Kennethisamanagerofaautomation设计company和haspreviously8engineeringstaffsreportingtohim.Basedonhisassessmentsonthe8engineers,heisonlysatisfiedwiththeperformanceof6ofhisengineers.Hefurtherconcludedfrompast5yearsobservationthatifaprojectwasassignedtothoseengineerswhohadmethisworkexpectation,85%ofthetimetheprojectwillbecompletedbeforedateline.Ontheotherhand,the2engineerswhoseperformanceisunsatisfactory,hasonly35%ofthetimecompletedtheirprojectsbeforedateline.Oneofthe2“unsatisfactory”engineerhadresignedfromthecompany8monthsago,和hisreplacement,Joehadsincethenjointhecompanyforaperiodof6months,和itisnowtimeforKennethtoreviewJoesprobationstatus,whichhewouldliketodothisthroughprobabilitystudy.Duringthepass6monthsinthecompany,Joehadsuccessfullycompleted3projectsbeforethegivendateline.Basedonthisinformation,whatisthechancethatJoesactualabilityisuptoKennethexpectation?,171,Furtherexampleofposteriorprobabilities(cont),Event=EmployingthecorrectorincorrectpersonStrike=Successinclosingtheprojectbeforedateline,P(Correct|3Strikes)=P(Correct,3Strikes)/P(3Strikes),=(0.4606/0.4713),=0.9773,IfJoehascompleted3successiveprojectsbeforedateline,theposteriorprobabilitythatheisthecorrectcandidateforthejobis0.9773(or97.73%).,CorrectIncorrect,0.853=0.61410.353=0.0429,172,Furtherexampleofposteriorprobabilities(cont),IfJoedoesnotmeethisdatelinetargetforthe4thproject,doesitmeanthatKennethhasmakethewrongjudgement,和whatistheprobabilityassociated?,CorrectIncorrect,0.853x0.15=0.09210.353x0.65=0.0279,P(Correct|SSSN)=P(Correct,SSSN)/P(SSSN),=(0.0691/0.0761),=0.9080,IfJoedoesnotmeetthedatelineforhis4thprojects,thenKennethwillbe90.8%surethatJoeisthecorrectcandidateforthejob.,173,174,IntroductiontoProbabilityDistribution,Whatisprobabilitydistribution?Itisatheoreticalfrequencydistributionthatdescribehowoutcomeareexpectedtovary,和areusefulmodelsinmakinginferencesunderconditionsofuncertainty.,175,ExampleofstatisticalinferenceusingprobabilitydistributionMartinisoneoftheauthorizedmagazinedistributorsforthemonthlybusinessjournal“FinancialTimes”.Thedistributioncontractwiththemagazinepublisherhasstatedclearlythatnobackissuesareallowedinthestoreinordertopreventreadersfromobtaining/misledbyback-datedmarketinformation,causingcreditability和liabilityimpacttothepublisher.Duetothepopularityofthemagazine,alldistributorareallowedtoplaceonlyoneordereverymonth,和thepublisherwillnotrefundanyexcessorderplacedbythedistributorifthemagazinewasnotsoldoutforanyparticularmonth.EachmagazinecostUS$2,和thedistributorearnUS$3fromeachcopysold.Inordertomaximizehisprofitbyreducingloss,Martindecidetouseprobabilitystudytohelphimmakehisdecisiononthenumberofmagazinetoordereachmonth.Hecollectedhissaledataoveraperiodof1yearasbelow:,176,Exampleofstatisticalinferenceusingprobabilitydistribution(cont)Thereare2typesofpossiblelosses;costofobsolescence(i.e.excessorderthathastobethrowaway),和costoflossopportunity(i.e.costoflosingsales).,Costofobsolescence=(MonthlyOrder-MonthlySale)xUS$2xP(M_Sale)wherenegativevalueequaltonoloss,Costoflossopportunity=(MonthlySale-MonthlyOrder)xUS$3xP(M_Sale)wherenegativevalueequaltonoloss,TotalLosses=ObsolescenceCost+OpportunityCost,177,Exampleofstatisticalinferenceusingprobabilitydistribution(cont),Thereforeinordertomaximizehisprofit,Martinwillneedtoorder12000magazinepermonth.,178,TypesofProbabilityDistributions,Whatisthedifferencebetweenfrequency和probabilitydistributions?Frequencydistributionisalistingofobservedfrequenciesforalltheoutcomesthatoccurredwhenanexperimentwasdone,whileprobabilitydistributionisalistingoftheprobabilitiesforallthepossibleoutcomesifthesameexperimentistobecarriedout.,DiscreteprobabilitydistributionsAdistributionofprobabilitieswhichallowedtotakeonalimitednumberofvaluesforitsoutcomes.(i.e.therollingofadice)BinomialdistributionPoissondistribution,ContinuousprobabilitydistributionsAdistributionofprobabilitieswhichallowedtotakeonaanynumberofvalueswithinagivenrangeofoutcomes.(i.e.therollingofadice)NormaldistributionStudentTdistribution,179,BinomialDistributions,Whatisthebinomialdistributions?Aprobabilitydistributionofdiscreterandomvariable,resultingfromanexperimentknownasBernoulli流程.,Conditionsfortheuseofbinomialdistributions(i.e.Bernoullitrial)?Eachexperimentaltrialhasonlytwopossibleoutcomes:successorfailure,headortail.Probabilityoftheoutcomeofanytrialremainsfixedovertime(i.e.statisticalindependence).和theoutcomeofoneeventdoesnotaffecttheoutcomeofthesubsequentevent.,Characteristicofbinomialdistributionp=Probabilityofsuccessq=Probabilityoffailurer=Numberofsuccessdesiredn=Numberofundertakentrials,180,Probabilitymassfunctionforbinomialdistributionn!Probabilityofrsuccessesinntrials=-xprxqn-rr!(n-r)!,ExampleofusingbinomialdistributionPaulisamanufacturingmanagerofadiskdrivecompanywhohasfive流程engineersreportingtohim.Heisfacingasituationwherehisengineersareoftenlateforwork,和after某些observation,hehasdeterminedthatthereisa0.4chancethatanyoneengineerwillbelate.Ifatanyonetime,the产品ionwillrequired3流程engineerstorunsmoothly,whatistheprobabilitythathis产品ionwillrunsmoothlyatpresentsituation?,Probabilityofsuccess(late),p=0.4Probabilityoffailure(early),q=0.6Numberoftrial(engineers),n=5Numberofsuccess(late),r=2orless,181,n!Probabilityofrlatearrivaloutofnstudent=-xprxqn-rr!(n-r)!,Exampleofusingbinomialdistribution(cont),Forr=0,5!P(0)=-(0.40)(0.65)0!(5-4)!=0.07776,Forr=1,5!P(1)=-(0.41)(0.65-1)1!(5-1)!=0.2592,Forr=2,5!P(2)=-(0.42)(0.65-2)2!(5-2)!=0.3456,Forr=3,5!P(0)=-(0.43)(0.65-3)3!(5-3)!=0.2304,Forr=4,5!P(1)=-(0.44)(0.65-4)4!(5-4)!=0.0768,Forr=5,5!P(2)=-(0.45)(0.65-5)5!(5-5)!=0.01024,Totalprobability=0.0776+0.2592+0.3456+0.2304+0.0768+0.01024=1,182,Exampleofusingbinomialdistribution(cont),P(r650=10.99911=0.00089,Assuchthereisonly0.089%chancethatarandomcandidatewilltakemorethan650hourstocompletethe培训.,197,Whatistheprobabilitythatacandidateselectedatrandomwilltakesbetween360hours和510hourstocompletethe培训?,Exampleofusingnormaldistribution(cont),Z1=(Xm)/=(360400)/80=-0.5,Z2=(Xm)/=(510400)/80=1.375,Assuch60.69%chancethatarandomcandidatewilltakebetween360hours和510hourstocompletethe培训.,198,NormaldistributionasanbinomialdistributionapproximationNormaldistributioncansometimesbeusedasanapproximationforbinomialdistribution,givingtheconditions:a)np5b)nq5,ExampleWhatistheprobabilityofgetting5,6,7,or8tailsin10tossesoffaircoin?,p=0.5,q=0.5,n=10,r=5,6,7,or8Frombinomialprobabilitydistributionstable,P(5,6,7,8)=P(5)+P(6)+P(7)+P(8)=0.2461+0.2051+0.1172+0.0439=0.6123,199,Toimprovetheaccuracyoftheapproximation,subtract和addacontinuitycorrectionfactorof0.5totherange5to8respectively.Theareaunderthisrangeiswhatweareinterestedin.,200,Hence,P(4.5x8.5)=0.9864-0.3745=0.6119(approxequalto0.6123bybinomialdistribution),201,IntroductiontoSampling取樣的介紹,Whatispopulationinstatistic?Apopulationinstatisticreferstoallitemsthathavebeenchosenforstudy.,Whatisasampleinstatistic?Asampleinstatisticreferstoaportionchosenfromapopulation,bywhichthedataobtaincanbeusedtoinferontheactualperformanceofthepopulation,Population,Sample2,Sample6,Sample8,Sample1,Sample3,Sample7,Sample4,Sample5,202,Samplingdistribution-adistributionofsamplemeansIfyoutake10samplesoutofthesamepopulations,youwillmostlikelyendupwith10differentsamplemeans和sample标准偏差s.ASamplingdistributiondescribestheprobabilityofallpossiblemeansofthesamplestakenfromthesamepopulation.,203,Whensamplesizeincreases,thestandarderror(orthestddeviationofsamplingdistribution)willgetsmaller.,Samplingdistribution(cont)取樣分配,204,CentralLimitTheorem中心線規則,205,Exampleofsamplingdistribution,Thepopulationdistributionofannualincomeofengineersisskewednegatively.Thisdistributionhasameanof$48,000,和a标准偏差of$5000.Ifwedrawasampleof100engineers,whatistheprobabilitythattheiraverageannualincomeis$48700和more.,206,Exampleofsamplingdistribution(cont),Therefore,mean=48000sigma=500X=50000Z=(48700-48000)/500=700/500=1.4,Fromthestandardizednormaldistributiontable,P(X$48700)=0.9192Therefore;P(X$48700)=1-0.9192=0.0808Thus,wehavedeterminedthatithasonly8.08%chancefortheaverageannualincomeof