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1、Six 6 6s s s sSigmaSix 6 6s s s sSigma What is Six-SigmaKey TermsSixSigmaAtermcoinedbyMotorolatoexpressprocesscapabilityinpartspermillion.Asixsigmaprocessgeneratesadefectprobabilityof3.4partspermillion(PPM)ChampionAnupperlevelbusinessleaderwhofacilitatestheleadership,implementation,anddeploymentofsi
2、xsigmaphilosophies.BlackBeltAprocessimprovementprojectteamleaderwhoistrainedandcertifiedinsix-Sigmamethodologyandtoolsandwhoisresponsibleforprojectexecution.MaterBlackBeltApersonwhoisan“expert”onSixSigmatechniquesandonproject implementation,masterBlackBelt playakeyroleintrainingandcoachingofBackandG
3、reen Belts.GreenBeltSixSigmarolesimilarinfunctiontoBlackBeltbut lengthoftrainingandprojectscopearereducedtotwoweeksoftraining.Six 6 6s s s sSigmaKey TermsYellowBeltHourlypersonneltrainedinthefundamentalsofsix-sigmawhoassistandsupportinprojectexecution,usualworkwithblackandGreenBelt.ProcessMapAstep-b
4、y-steppictorialsequenceofaprocessshowingprocessinputs,processoutputs,cycletime,reworkoperations,andinspectionpoints.KeyprocessInputsVariable(KPIV)Thevitalfewinputvariables,call“x”sKeyprocessoutputsVariable(KPOV)Theoutputvariables,call“x”sDFMADesignformanufactureandassemble,Amethodologytoreduceproduc
5、tcomplexityanddesignaroundmorecapablecomponents/processesCostofpoorqualityCostassociatedwithProvidingpoorqualityproductsorservices.Canbedivideintofourcostcategories:Appraisal,Scrap,Rework,andfieldComplaint What is Six-SigmaSix 6 6s s s sSigmaWhat is Six-SigmaVisionPhilosophyAggressiveGoalMetric(Stan
6、dardofmeasurement)BenchmarkMethodToolsfor:CustomerfocusBreakthroughImprovementContinuesimprovementPeopleInvolvementSix-SigmaSix-Sigma is a problem solving process used- to produce: Reduced variation in our processes / Products improved RTY , DPU,& DPPM / Reduced cost of poor quality (COPQ) / improve
7、d capacity and productivity $s What is Six-SigmaSix 6 6s s s sSigmaSix-Sigma can be applied to every business functionSix-SigmaDESIGNPURCH.MFGMAINT.QAADMIN.SERVICE What is Six-SigmaSix 6 6s s s sSigmaSix-Sigma Focus :DelightingtheCustomerThroughFlawlessExecutionRapidBreakthroughImprovementAdvancedBr
8、eakthroughToolsthatworkPositiveandDeepCultureChange Real Financial results : Passion +Execution = Fast and Lasting ResultsWho else in the U.S has started Six Sigma Motorola ( 1987 ) Texas Instruments (1988 ) IBM (1990 ) ABB (1993 ) Alliedsignal / Koadk (1994 ) GE (1995 ) Whirlpool ,Bombardier, Polar
9、oid , Siebe & PACCAR ( 1996 / 98 ) What is Six-SigmaSix 6 6s s s sSigmaValueAnalysisConceptEngineeringKJmethodologyQFDProcessMapCauseandeffectmatrixMeasurementsystemanalysiscapabilityanalysisDescriptivestatisticsGraphicaltechniquesBoxPlots/Histograms/Scatterplots/RunchartsParetocharts/checksheets/Ti
10、meseriesplotsStatisticalprocesscontrolchart CorrelationSimplemultipleregressionMulti-VaristudiesTop Tools What is Six-SigmaSix 6 6s s s sSigmaInferentialstatisticsCentrallimittheoremConfidenceintervalFailuremodeandeffectanalysisDesign&ProcessFractionfactorialexperimentsFullfactorialexperimentsRespon
11、sesurfacemethodsTransformationsNormaldistributionSamplesizedeterminationScreeningstudiesStatisticalTolerancingDesignformanufacturabilityDesignforqualityHypothesistestingF-testChi-squaretestTestsfornormalityAnalysisofVarianceTop Tools What is Six-SigmaSix 6 6s s s sSigmaISORequiresSix-SigmaDeliversPr
12、eventionofDefectsallStagesfromDesignthroughservicingOKIdentifyingtheneedforstatisticaltechniquesrequireforestablishing,controllingandverifyingprocesscapabilityandproductcharacterization.OKInvestigationofthecauseofdefectsrelatingtoproduct,processandqualitysystem.OKContinuousimprovementofqualityofprod
13、uctsandservicesOKISO and Six-Sigma What is Six-SigmaSix 6 6s s s sSigmaLeading Six-Sigma In Operations Select the Right project :ClarifyBigPictureusingStrategicPlanEstablishPlant/productivitybaselinePrioritizeprojectsbaseonvalue,resourcesreqdtimingSelectkeyprojectswithleadershipbuy-inCheckaccountabi
14、lity:businessandpersonal Select and train the Right peopleEnsuretherightleadershipandownershipDevelopatrainingplanDedicatetimefortrainingandapplicationEnsuretherightsupportresourcesareavailable What is Six-SigmaSix 6 6s s s sSigmaLeading Six-Sigma In Operations Plan and Implement Six Sigma Improveme
15、nt Plans : MeasureprocessAnalyzeProcessImproveProcessControlprocess Manage for Excellence in operationStayfocusedFrequentlyreviewprocessandremovebarriersCheckrealbusinessimpactContinuouslycommunicateprogressLinktoperformancemanagementandR&R Sustain the GainsImplementeffectivecontrolplansConductregul
16、artrainingfocusedontheprocessReviewquarterlythesixsigmasystemeffectivenessContinuallyidentifyandlunchnewproject What is Six-SigmaSix 6 6s s s sSigmaPhase 0:Define*ScopeandBoundary*DefineDefects*TeamCharterandChampion*Estimated$Impact*LeadershipapprovalPhase 1: Process Measurement*MapprocessandIdenti
17、fyInputsandOutputs*CauseandeffectsMatrix*EstablishMeasurementSystemcapability*EstablishProcessCapabilityBaselineSix Sigma Process Improvement Roadmap What is Six-SigmaSix 6 6s s s sSigmaPhase 11: Process Analysis*CompleteFMEA*PerformMulti-VariAnalysis*IdentityPotentialCriticalInputs*DevelopPlanforNe
18、xtPhasePhase 111: Process Improvement*VerifyCriticalInputs*OptimizeCriticalInputsPhase IV: Process Control*ImplementControlPlan *VerifyLongTermCapability*ContinuouslyImproveProcessSix Sigma Process Improvement Roadmap What is Six-SigmaSix 6 6s s s sSigmaDesign for Six Sigma RoadmapStep1. Define/Meas
19、ureProductCharter,Stage/GateCriteria&MetricsDetermineCustomerneedsDevelopQFDMatrixStep2.AnalysisProductCompleteFMEAReviewDataandPrioritizeKeyInputVariablesPerformGageStudiesonEssentialMeasurementSystems What is Six-SigmaSix 6 6s s s sSigmaDesign for Six Sigma RoadmapStep3. OptimizeProductDefineCriti
20、calInputsusingDOEEvaluateImpactofScaleSensitiveVariablesusingDOEOptimizeProduct/processusingStatisticalTolerancingandDesignforMFGDevelopProcessMapwithKeyInputandOutputVariablesStep4.ControlProductDevelopControlPlanCompleteCapabilityAnalysis/Prediction What is Six-SigmaSix 6 6s s s sSigmaSuggested Pr
21、oject FiltersSignificantlyImprovesDefects/1000,Scrap,WarrantyClaims,TimetoMarket50%reductioninDefects/1000,50%reductioninscrap50%reductioninWarrantyClaims50%improvementinproductlunchcycletimeFocusesonhighimpact/highriskproductSignificantlyreducesfieldinquiresImprovesCustomerService What is Six-Sigma
22、Six 6 6s s s sSigmaProject Status Sheet What is Six-SigmaSix 6 6s s s sSigmaProject Chart What is Six-SigmaSix 6 6s s s sSigma Process Improvement PlanKey TermsKPIVKeyprocessinputvariableorCriticaltoprocess(CTP)variableAssociatedwiththeXsKPOVKeyprocessoutputvariableorCriticaltoQuality(CTQ)Associated
23、withtheYsY=(X1,X2,Xn)TypicalforProcessImprovementControl the existing systemIdentifyInputsthatarenotincontrolandcontrolthemDeliverable:goodProcesscontrolPlanOptimize the existing SystemProcessincontrolbutinputSpecificationarenotoptimumDoesperformedtounderstandtherelationshipsbetweentheXsandtheYsSix
24、6 6s s s sSigmaTypical for Process ImprovementRedesign the existing SystemProcessisoptimizedbutnotproducingcompetitiveproductcharacteristicsLink-upbetweenmanufacturingandTechnologygroupsthekeytosuccessCreate a new SystemProcessisredesignbutstillnotproducingcompetitive productcharacteristicstobenumbe
25、roneinmarketTechnologylinkisstrongesthere Process Improvement PlanSix 6 6s s s sSigmaImprovementStrategiesImprovementStrategiesCharacterizationOptimizationTechnicalBreakthrough2.StatisticalProblem3.StatisticalSolution4.PracticalSolution1.PracticalProblemY=(X1,X2,Xn)OverallApproachOverallApproach Pro
26、cess Improvement PlanSix 6 6s s s sSigmaProcess Improvement RoadmapStep 1: Process Measurement Planprojectandidentifykeyprocessinput/outputvariablesPerformgagestudiesonessentialmeasurementsystemPerformShort-termcapabilitystudiesandevaluatecontrolplanStep11:Process Analysis CompleteFMEAandevaluatecon
27、trolplan CompleteMulti-Varistudiestoidentifypotentialkeyinputs ReviewDataandprioritizekeyinputvariables Process Improvement PlanSix 6 6s s s sSigmaProcess Improvement Roadmap Step111: Process Improvement VerifycriticalinputsusingDOE DeterminetheoptimumoperatingwindowUpdatethecontrolplanStep1V:Proces
28、s control Finalizetheprocesscontrolplan Ongoingverificationofthestabilityandcapabilityoftheprocess Process Improvement PlanSix 6 6s s s sSigmaFourPhasesand8keyToolsFourPhasesand8keyToolsMeasureAnalysis$AdvancedToolsaccelerateResultsImproveControl Process Improvement PlanSix 6 6s s s sSigmaMeasurepro
29、cessMapsMeasurementSystemsCapabilityAnalysisHistogramControlChartAnalyzeCauseandEffectMatrixFMEADesignofExperiments(DOE)Multi-VariStudiesDOE/EvolutionaryoperationsControlPlanStatisticalprocessControlChartsImproveandControl3-6CriticalKPIVs4-8CriticalKPIVs8-10KPIVs10-15KPIVs30-50KPIVsAllXs1st“HitList”
30、ScreenedListFoundCriticalXsControllingCriticalXsDynamics of Process Improvement Plan-The Funnel Effect Process Improvement PlanSix 6 6s s s sSigmaDefiningCTQsBusiness case ( Describes why the project is important to do )Problem and Goal Statement ( Describes what Problem or issue is )Clarifying Cust
31、omer Requirements ( What do you Provide your customers :) Services :Delivery / Order information / repair / technical support Products :Equipment / Invoices / Packing Slips Can be tangible or intangibleProjectDefinition:KeypreparationphaseDEFINEMEASUREANALYZEIMPROVECONTROL Project DefinitionSix 6 6s
32、 s s sSigmaDefiningCTQs( How to find out what the Customer wants? ) Customer surveys Concept engineering Focus groups Quality Function deployment Customer needs mapping Operational Definitions Project Scoping ProjectDefinition:Keypreparationphase DEFINEMEASUREANALYZEIMPROVECONTROL Project Definition
33、Six 6 6s s s sSigma Use for Process MapInputstoCauseandEffectsMatrixInputstoFMEAInputstoControlPlanSummaryInputstoCapabilitySummaryEvaluateexperimentalDesigns-Tracksvariablesstudied-AllowsevaluatedesignsrobustnesstonoisevariablesTwo type of Process MappingProcessmappingforKPIVsandKPOVs-useasfirstste
34、pinsixsigmaprocess-criticalinordertosuccessfullyimproveprocessvariationMappingSix 6 6s s s sSigmaTwo type of Process Mapping ( Continue )“AsIs/CanBe”mapping-excellentmethodforidentifyingnon-valueaddedsteps-necessaryfirststepincycle-timereductionprojects-excellentfordiscreteprocessesAwelldefinedKPIVp
35、rocessmapcanbeusedtodeveloptheAsIs/CanbemapProcess Mapping Steps Identify the process and its external inputs and customer outputsidentifyexternalinputs:rawmaterial/identifyendcustomeroutputs:ifprocessisunderdevelopment,thenuseproductdesignQFDtoidentifyfinalproductspecifications.MappingSix 6 6s s s
36、sSigmaProcess Mapping Steps （Continue ) Identify all steps in the processincludeallvalue-addedandnon-value-addedsteps List key output variables at each stepincludebothprocessandproductoutputvariables List key input variables and classify processinputsascontrollable,noise,orstandardoperatingprocedure
37、sControllableinputs:KPIVsthatcanbechangedtoseetheeffectonKPOVs,sometimescall“Knob”variablesNoiseinputs:inputvariablesthatimpacttheKPOVsbutaredifficultorimpossibletocontrolStandardoperatingprocedures:qualitativevariableswhicharespecifiedinthestandardprocedureforrunningtheprocessCriticalinputs:KPIVsth
38、athavebeenstatisticallyshowntohaveamajorimpactonthevariabilityoftheKPOVsMappingSix 6 6s s s sSigmaPreparing the process MapTeamEffortmanufacturingengineers/lineoperators/linesupervisors/maintenancetechniciansInputstoMappingbrainstormingoperatormanualsengineeringspecificationsoperatorexperience6Ms(ma
39、n,machine,materials,method,environment)Optional Mapping Symbolsyoucanusethesesymbolstohelptheseparatesteps,onlygreenisvalueadded.ProcessSteporOperationStorage/queueQualityCheckorInspectionDecisionTransportormovementMappingSix 6 6s s s sSigmaExample of Detailed MapAnother FormatMappingSix 6 6s s s sS
40、igmaMappingSix 6 6s s s sSigmaMappingSix 6 6s s s sSigmaMappingSix 6 6s s s sSigmaNon-Value Added AnalysisAsIs/CanBeMappingOftenduringthedesignoranalysisofaprocesswefindmanystepswhicharenotvalue-addedDefinitionofvalue-addedCustomerrecognizesthevalueChangestheproductDonelightthefirsttimeRequiredbylaw
41、,regulation,orcontract,orforHS&EorethicalconsiderationsMappingSix 6 6s s s sSigmaAs Is / Can Be Analysishowtoanalyzeaprocessmap-step&/asis/canbeValidatetheprocessmapwitha“walkthrough”bytheentireteam(establishbaseline)Identifyvalue-addedandnecessarystepIdentifyotherstreamliningactivitiestoimproveproc
42、essflowDetermineentitlementanddevelop“canbe“map(considerbenchmarking“best-in-class”/“worldclass”processesValidatecan-bemap/Developimplementation/implementDefinitionsBaseline:theperformanceoftheexistingprocessEntitlement:theperformanceoftheexistingprocess,allowingforonlyvalueaddedandnecessarytasks/ac
43、tivitiesBest-in-class:thebestperformancefortheprocessanywherewithintheindustryWorldclass:thebestperformancefortheprocessanywhereMappingSix 6 6s s s sSigma“As Is / Can Be” Mapping ViewsThereareusually3versionsofeach“AsIs/CanBe”MapWhatyouWantittobe-Whatyoubelieveitis-Whatitactuallyis-NecessaryStepsDef
44、initionAstepmaybenon-value-addedbutnecessaryif:Itisrequiredbylaw,regulation,orcontractItisrequiredforhealth,safety,environmental,orethicalconsiderationsMappingSix 6 6s s s sSigma C & E MatrixCause and Effects MatrixThisisasimpleQFD(QualityFunctionDeployment)matrixtoemphasizetheImportanceofunderstand
45、ingthecustomerrequirements Relatesthekeyinputstothekeyoutputs(customerrequirements)usingtheprocessmapastheprimarysource Keyoutputsarescoredastoimportancetothecustomer KeyinputsarescoredastorelationshiptokeyoutputsResults:ParetoofkeyinputstoevaluateintheFMEAandcontrolPlansResults:Inputintothecapabili
46、tystudystepinthemeasurementphase Results:InputintotheinitialevaluationoftheprocesscontrolplanSix 6 6s s s sSigmaCause & Effect Matrix StepIdentifyCustomerrequirements(outputs)fromProcessMapRankorderandassignpriorityfactortoeachoutputs(usuallyona1to10scale)Identifyallprocessstepsandmaterials(inputs)f
47、romtheprocessMapEvaluatecorrelationofeachinputtoeachoutputlowscale:changesintheinputvariable(amount,quality,etc)havesmalleffectonoutputvariableHighscale:changesintheinputvariablecangreatlyaffect theoutputvariable.Crossmultiplycorrelationvalueswithpriorityfactorsandaddacrossforeachinput C & E MatrixS
48、ix 6 6s s s sSigma C & E MatrixSix 6 6s s s sSigmaNote:ThistableprovidestheinitialinputtotheFMEA.Wheneachoftheoutputvariables(requirements)arenotcorrect,thatrepresentspotentialEFFECTS.Wheneachinputvariableisnotcorrect,thatrepresentsFailureModes.1.ListtheKeyProcessOutputVariables2.Rateeachvariableona
49、1-to-10scaletoimportantancetothecustomer3.ListKeyProcessInputVariables4.Rateeachvariablesrelationshiptoeachoutputvariableona1-to-10scale5.SelectthetopinputvariablestostarttheFMEAprocess;DeterminehoweachselectedinputvarablecangowrongandplacethatintheFailureModecolumnoftheFMEA. C & E MatrixSix 6 6s s
50、s sSigmaLinking the C&E Matrix to other ToolsC&EMatrixCapabilitySummaryFMEAControlPlanSummaryOutputsInputsTheKeyOutputsarelistedandevaluated.KeyInputsareexploredTheKeyInputsareevaluated. C & E MatrixSix 6 6s s s sSigmaThePurposeofthisworksheetistoguideactionsneededtogetstatisticalcapabilitydata.Thef
51、ormaddressesboththeMeasurementsystemsandtheprocesscapability.anyblankspacesinthefromneedtobeaddressesbyactions C & E MatrixSix 6 6s s s sSigmaForeveryinputintheC&EmatrixPareto,aninitialassessmentofthecontrolplanisdone,thishelpspicklowhangingfruitatthefrontendofaprocessimprovementproject C & E Matrix
52、Six 6 6s s s sSigma Failure Mode and Effects AnalysisDefinition - FMEAAstructuredapproachto:-Identifyingthewaysinwhichaproductorprocesscanfail-estimatingtheriskassociatedwithspecificcauses-prioritizingtheactionsthatshouldbetakentoreducetherisk-evaluatingthedesignvalidationplanProductorthecurrentcont
53、rol plan(ProcessPrimaryDirective:Identifywaystheproductorprocesscanfailandeliminateorreducetheriskoffailure Six 6 6s s s sSigma Failure Mode and Effects AnalysisHistoryFirstusedinthe1960sintheAerospaceindustryduringtheApollomissionsIn1974theNavydevelopedMIL-STD-1629regardingtheuseofFMEAInthelate1970
54、s,automotiveapplicationsdrivenbyliabilitycostsLatertheautomotiveindustrysawtheadvantagesofusingthistooltoreducerisksrelatedtopoorquality.Early80s:MicroElectronicIndustrystartedtoapplyFMEAtoassistinimprovingthe“yieldofmemorydevices”.Mid80s:AutomotiveindustriesstartedtoapplyFMEAtothemanufacturingproce
55、sses.90s:TQS9000recommendedadoptionofFMEA.Six 6 6s s s sSigmaWhere do Risk Come FromCumulativeRisk:RawMaterialVariationPoorlydevelopedSpecificationLimitsMeasurementVariation(OnlineandQC)MachineReliabilityVagueWorkmanshipStandardsUnclearcustomerExpectationsPotentialSafetyHazardsPoorcontrolplans&SOPsP
56、oorProcesscapability Failure Mode and Effects AnalysisSix 6 6s s s sSigmaType of FMIEAsSystemusedtoanalyzesystemsandsub-systemsintheearlyconceptanddesignstages.Focusesonpotentialfailuremodesassociatedwiththefunctionsofasystemcausedbythedesign.Design-usedtoanalyzeproductdesignsbeforetheyarereleasedto
57、production.FocusesonProductFunction.Processusedtoanalyzemanufacturingandassemblyprocesses.FocusesonProcessInputs. Failure Mode and Effects AnalysisSix 6 6s s s sSigmaRole of Process FMEAKeytoolofprocessteamtoimprovetheprocessinapreemptivemanner(beforefailureoccur)*ThebestFMEAresultsareNEVERSEEN!Used
58、toprioritizeresourcestoinsureprocessimprovementeffortsarebeneficialtocustomerUsedtodocumentcompletionofprojectsShouldbeadynamicdocument,continuallyreviewed,amended,updated Failure Mode and Effects AnalysisSix 6 6s s s sSigmaPurposes of Process FMEAAnalyzesnewmanufacturingprocessesIdentifiesdeficienc
59、iesintheProcessControlPlanEstablishesthepriorityofactionsEvaluatestheriskofprocesschangesIdentifiespotentialvariablestoconsiderinMulti-variandDOEstudiesGuidesthedevelopmentofnewmanufacturingprocessesHelpssetthestageforbreakthroughFMEA TeamTeamapproachisnecessaryResponsibleManufacturingEngineerleadst
60、heteamRecommendedrepresentatives:DesignQualityReliabilityMaterialsTestingSupplier Failure Mode and Effects AnalysisSix 6 6s s s sSigmaFMEA Inputs and OutputsInputs-ProcessMap-C&EMatrix-ProcessHistory-ProcesstechnicalproceduresOutputs-ListofactionstopreventCausesortodetectFailureModes-HistoryofAction
61、sTaken Failure Mode and Effects AnalysisSix 6 6s s s sSigma FMEA - Step by Step1.ForeachProcessInput,determinethewaysinwhichtheinputcangowrong(TheseareFailuremodes2.ForeachFailuremodeassociatedwiththeinputs,determineEffects:3.IdentifypotentialCausesofeachFailuremode4.ListtheCurrentControlsforeachCau
62、se5.AssignSeverity,OccurrenceandDetectionratingstoeachCause6.CalculateRPN7.DetermineRecommendedActionstoreduceHighRPN8.TakeappropriateActionsandDocument9.RecalculateRPNs Failure Mode and Effects AnalysisSix 6 6s s s sSigmaDefinition of terms - Failure ModeFailureModethewayinwhichaspecificprocessinpu
63、tfails-ifnotdetectedandeithercorrectedorremoved,willcauseeffecttooccur.Canbeassociatedwithadefect(indiscretemanufacturing)oraprocessinputvariablethatgoesOutSideofspecification.AnythingthatanoperatorcanseethatswrongisconsideredaFailureMode.ExampleTemperaturetoohighIncorrectPOnumberSurfacecontaminatio
64、nPitsonsubstratePainttoothin Failure Mode and Effects AnalysisSix 6 6s s s sSigmaForeachcritical(highvalue)processInputdeterminethewaysinwhichtheinputcangowrong(FailureModes)OneareaofhighriskinthemanufacturingprocessIsHeatStakingoftheLatchAssembly,WewillanalyzetheLooseWeld,eventhoughtherearemanymore
65、potentialfailuremodes.ProcessStepKeyProcessInputFailureModesWhatcangowrongEffectsCausesLatchassemblyHeatstakingLooseWeld Failure Mode and Effects AnalysisSix 6 6s s s sSigmaDefinition of Terms Effect Effect-impact on customer requirements ,Generally externalcustomerfocus,butcanalsoincludedownstreamp
66、rocesses.Examples:Temperaturetoohigh:damagecomponentIncorrectPOnumber:AccountsreceivabletraceabilityerrorsSurfacecontamination:PooradhesionPits:InternalopensonsubstratePainttoothin:Poorcoverage Failure Mode and Effects AnalysisSix 6 6s s s sSigmaForeachFailureModeassociatedwiththeinputs,determineEff
67、ectsTheseeffectsareinternalrequirementsforthenextprocessand(or)tothefinalcustomer,Inthiscasewewilllookatoneeffect,eventhoughtherecanbeseveral.ProcessStepKeyProcessInputFailureModesWhatcangowrongEffectsCausesLatchassemblyHeatstakingLooseWeldDoordoesntlatchNote that the relationship between the failur
68、e Mode and the Effect is not always 1-to 1. Failure Mode and Effects AnalysisSix 6 6s s s sSigmaNotethattherelationshipbetweenthefailureModeandtheEffectisnotalways1-to1.Linking Failure Modes to EffectsFailureMode1FailureMode2Effect1FailureMode1Effect1Effect2FailureMode1FailureMode2Effect1 Failure Mo
69、de and Effects AnalysisSix 6 6s s s sSigmaDefinition of Terms - CauseCauseSourcesofprocessvariationthatcausestheFailureModetooccur.Example:Temperaturetoohigh;afaultytemperaturesensor.IdentificationofCausesshouldstartwithFailureModesassociatedwiththehighestseverityratings.ExamplesTemperatureTooHigh:T
70、hermocoupleoutofcalibrationSurfaceContamination:excessfluxfromhandsolderingIncorrectPOnumber:TypographicalerrorPits:Highparticlecountincleanroompainttothin:Highsolventcontent Failure Mode and Effects AnalysisSix 6 6s s s sSigma3. Identify Potential Causes of each Failtre ModeAsinmostcases,wehaveseve
71、ralcausesforonefailuremodeeffectcombinationProcessStepKeyProcessInputFailureModesWhatcangowrongEffectsCausesLatchassemblyHeatstakingLooseWeldDoordoesntlatchMisalignmentofhornWrongweldTemperatureOperatormisalignspartDefinition of Terms Current ControlsCurrentControlsSystematizedmethodsdevicesinplacet
72、opreventordetectfailuremodesorCauses(beforecausingeffects). Failure Mode and Effects AnalysisSix 6 6s s s sSigmaDefinition of Terms Current Controls ( Continue )Preventionconsistsoffoolproofing,automatedcontrolandset-upverificationsControlsconsistsofaudits,checklists,Inspection,laboratorytesting,tra
73、ining,SOPs,Preventivemaintenance,etc.Whichismoreimportanttoprocessimprovement,Preventionordetection?ExamplesThermocoupleortofcalibration:PMofthermocoupleExcessfluxfromhandsoldering:OperatortrainingTypographicalerror:SpellgrammarproofsoftwareHighparticlecountincleanroom:NoneHighsolventcontent:None Fa
74、ilure Mode and Effects AnalysisSix 6 6s s s sSigma4.List the current Controls for each CauseForeachFailureMode/CausewelisthowweareeitherpreventingtheCauseordetectingtheFailureMode,wewilllisttheprocedurenumberwherewehaveaSOPProcessStepKeyProcessInputFailureModesWhatcangowrongEffectsCausesCurrentContr
75、olLatchassemblyHeatstakingLooseWeldDoordoesntlatchMisalignmentofhornAlignmentFixtureWrongweldTemperatureHeatSensorCalibrationOperatormisalignspartNoneThisishowtheFMEAidentifiesinitialholesintheCurrentControlPlan-processteamscanstartworkingontheseholesrightaway Failure Mode and Effects AnalysisSix 6
76、6s s s sSigmaRisk Priority Number ( RPN )TheoutputofanFMEAisthe“RiskPriorityNumber”TheRPNisacalculatednumberbasedoninformationyouprovideregardingthepotentialfairemodes,Theeffects,andThecurrentabilityoftheprocesstodetectthefailuresbeforereachingthecustomerItiscalculatedastheproductofthreequantitative
77、ratings,eachonerelatedtotheeffects,causes,andcontrols:RiskPriorityNumberisnotsacredScalingforSeverity,OccurrenceandDetectioncanbelocallydeveloped.Othercategoriescanbeadded.Forexample,oneBlackbeltaddedanImpactscoretotheRPNcalculationtoestimatetheoverallimpactoftheFailureModeontheprocess. Failure Mode
78、 and Effects AnalysisSix 6 6s s s sSigmaFMEA ModelCauseDetectionFailureMode(Defect)DetectionEffectDetectionPreventionControlMaterialorProcessinputProcessStepExternalcustomerordownstreamprocessstepWhichisabestcase?Whichisaworstcase? Failure Mode and Effects AnalysisSix 6 6s s s sSigmaDefinition of RP
79、N TermsRPN = Severity X Occurrence X Detection Severity(ofEffect)-importanceofeffectoncustomerrequirementscouldalsobeconcernedwithsafetyandotherrisksiffailureoccurs(1=NotSevere,10=VeryLikely)Occurrence(ofCause)frequencywithwhichagivenCauseoccursandcreatesFailureMode.Cansometimesrefertothefrequencyof
80、aFailureMode(1=NotLikely,10=VeryLikely)Detection(capabilityofControls)abilityofcurrentcontrolschemetodetectorPrevent:thecausesbeforecreatingfailuremodethefailuremodesbeforecausingeffect1=LikelytoDetect,10=NotLikelyatalltoDetect Failure Mode and Effects AnalysisSix 6 6s s s sSigmaFMEA ScoringThereare
81、awidevarietyofscoring“anchors”,bothquantitativeorqualitative.Twotypesofscalesare1-5or1-10.The1-5scalesmakeiteasierfortheteamstodecideonscoresThe1-10scaleallowsforbetterprecisioninestimatesandawithvariationinscores.The1-10scaleisgenerallyconsideredtobethebestoption. Failure Mode and Effects AnalysisS
82、ix 6 6s s s sSigmaAlmostcertaindetectionRemote:FailureisunlikelyNoeffect1VeryhighchangeofdetectionMinordefectnoticedbydiscriminatingcustomers2HighchangeofdetectionLow:RelativelyfewfailuresMinordefectnoticedbysomecustomers3ModeratelyhighchangeofdetectionMinordefectnoticedbysomecustomers4Moderatechang
83、eofdetectionReducedsecondaryfunctionperformance5LowchangeofdetectionModerate:OccasionalfailureLossofsecondaryfunction6VerylowchangeofdetectionReducedprimaryfunctionperformance7RemotechangeofdetectionHigh:RepeatedfailuresLossofprimaryfunction8VeryremotechangeofdetectionPermanentdamagetodatawithwarnin
84、g9CannotdetectVeryhigh:FailureisalmostinevitablePermanentdamagetodatawithoutwarning10AbilitytoDetectLikelihoodofOccurrenceSeverityofEffectRatingExample Rating Scale Failure Mode and Effects AnalysisSix 6 6s s s sSigma5.AssignSeverity,OccurrenceandDetectionratingstoeachCause6.CalculateRPNS7.Determine
85、RecommendedActionstoreduceHighRPNsWhattodoaboutthehighRPNs*Reviewresultsandinsights*Determinepotentialnextsteps:Datacollection/Experiments/Processimprovement/ProcesscontrolimplementationsActionsarerecommendedforonlythehighRPNs(ThekeyisFOCUS!)8.TakeappropriateActionsandDocument Failure Mode and Effec
86、ts AnalysisSix 6 6s s s sSigma9. Recalculate RPNsTheFMEAshouldbere-evaluatedbythegroupasnewrecommendedactionsAreidentified,completedandrecorded. Failure Mode and Effects AnalysisSix 6 6s s s sSigmaMethodologyTwomajorapproaches:StartingwithQFD/Cause&EffectMatrixStartingwithFMEAdirectlyfromtheProcessM
87、apApproaches to FMEAsApproachone(C&EMatrixFocus)-StartwithkeyinputswiththehighestscoresfromtheC&EMatrixanalysis-FillouttheFMEAworksheetforthoseinputs-CalculateRPNsanddeveloprecommendedactionsforthehighestROPs-completetheprocessFMEAforotherinputsovertimeApproachtwo(CustomerFocused):-FillouttheFailure
88、ModeandEffectscolumnsoftheworksheet.CopytoFMEAformandrateSeverity.-Forhighseverityratings.listcauseandrateoccurrenceforeachcause-Forthehighestseverity*occurrenceratings,evaluatecurrentcontrols-ForhighestRPNsdeveloprecommendedactions Failure Mode and Effects AnalysisSix 6 6s s s sSigmaApproaches to F
89、MEAs ( continue )ApproachThree(Comprehensive)-Goodapproachforsmallprocesses-FillouttheFMEAworksheetbeginningwiththefirstprocessstepandendingwiththelast-ScoreSEV,OCCandDETforallcauses-DeveloprecommendedactionsforhighestRPNsApproachFour(SuperFocused)-PickthetopParetodefectitemorFailureMode-FocustheFME
90、AprocessononlythatdefectorFailureMode-Purpose:To“kill“thatFailureMode. Failure Mode and Effects AnalysisSix 6 6s s s sSigma Failure Mode and Effects AnalysisSix 6 6s s s sSigma Failure Mode and Effects AnalysisSix 6 6s s s sSigma MSA - GR&RProcedure for performing an R&R study Calibratethegage,orass
91、urethatithasbeencalibratedHavethefirstoperatormeasureallthesamplesonceinrandomorder.Continueuntilalloperatorshavemeasuredthesamplesonce(thisisTrial1)Repeatsteps2-4fortherequirednumberoftrials.UsetheformprovidedtodeterminethestatisticsoftheR&Rstudy.RepeatabilityReproducibilityStandarddeviationsofeach
92、oftheabove%R&R%ToleranceanalysisAnalyzeresultsanddeterminefollow-upaction,ifany.Six 6 6s s s sSigmaRepeatability Thevariationbetweensuccessivemeasurementsofthesamepart,samecharacteristic,bythesamepersonusingthesameinstrument.alsoknownastest-retesterror;usedasanestimateofshort-termvariation.Estimated
93、bythe pooled ( average ) standard deviationofthedistributionofrepeatedmeasurementsReproducibilityThedifferentintheaverageofthemeasurementsmadebydifferentpersonsusingthesameordifferentinstrumentwhenmeasuringtheidenticalcharacteristic.Goodreproducibility:theshiftamongdifferentoperatorsarelittle.Poorre
94、producibility:theshiftamongdifferentoperatorsaremore. MSA - GR&RSix 6 6s s s sSigmaPrecision to tolerance Ratio P/ T=5.15*MS / ToleranceAddresseswhatpercentofthetoleranceistakenupbymeasurementerror.Bestcase:10%Acceptable:30%IncludesbothrepeatabilityandreproducibilityOperatorxUnitxTrialexperimentTheP
95、/Tratio(%ToleranceInMinitab)isthemostcommonestimateofMeasurementsystemprecision.Thisestimatemaybeappropriateforevaluatinghowwellthemeasurementsystemcanperformwithrespecttospecifications.Specifications,however,maybetootightortooloose.Generally,theP/Tratioisagoodestimatewhenthemeasurementsystemisonlyu
96、sedtoclassifyproductionsamples.Eventhen,ifprocesscapability(Cpk)isnotadequate,theP/Tratiomaygiveyouafalsesenseofsecurity. MSA - GR&RSix 6 6s s s sSigma %R&R= MS / Total x 100%Addresseswhatpercentofthetotalvariationistakenupbymeasurementerror.IncludesbothrepeatabilityandreproducibilityOperatorxUnitxT
97、rialexperimentAsatarget,lookfor%R&R30%The%R&RisthebestmeasurefortheprocessimprovementleaderThisestimateshowwellthemeasurementsystemperformswithrespecttotheoverallprocessvariation%R&Risthebestestimatewhenperformingprocessimprovementstudies.IfCp0=1.0,then%R&R70%If1.0Cp01.5,then%R&R=1.5,then%R&R15Ifnot
98、practicalorpossible,choosenumberoftrialssothat:ifS*O4,trials=6 ifS*O5,trials=5ifS*O8,trials=4 ifS*O Quality Tools Gage R&R Study OR Gage Run Chart( Number of Distinct Categories must be at least 4 for Process Improvement use ) MSA - GR&RSix 6 6s s s sSigma SPCHow Do We Manage Data - Today SPCS=Stati
99、sticaltechniquesusedtoexamineprocessvariationP=Process,ANYProcessC=Controllingtheprocessthroughactivemanagement Where Did SPC Come From ?1920s-WesternElectric/Dr.WaltershewhartUsedtoidentifycontrolled&uncontrolledvariationalsoknownascommon&specialcausesTriestofindtheprocesssignalsinallofthenoiseUses
100、controlchartasmaintoolSix 6 6s s s sSigmaCauseCommon Cause ( Noise )IspresentineveryprocessIsproducedbytheprocessitselfCanberemovedand/orlessenedbutrequiresafundamentalchangeintheprocessSpecial Cause ( signals )Existsinmostoperations/processCausedbyuniquedisturbancesoraseriesofthemCanberemoved/lesse
101、nedbybasicprocesscontrolandmonitoring SPCSix 6 6s s s sSigmaTwo general kinds of DataAttribute - Thedataisdiscrete(COUNTED).ResultsFromusinggo/no-gogages,orfromtheinspectionofvisualdefects,visualproblems,missingparts,orfrompass/failoryes/nodecisionsVariables - Thedataiscontinuous(measured).Resultsfr
102、omtheactualmeasuringofacharacteristicsuchas diameterofahose,electricalresistance,ect. SPCSix 6 6s s s sSigmaChoosing the correct control chartWhattypeofdata?ContinuousDatacollectedingroupsorindividuals?X-BarRX-BarSGroups(Averages)IndividualsmovingrangeDiscreteCountingspecificdefectsordefectiveitems?
103、IstheprobabilityofAdefectLowPoissondistributionSpecifictypesof“Defects”Ifyouknowhowmanyarebad,doyouknowhowmanyaregood?BinomialdistributionDefectiveItemsAreaofOpportunityconstantineachsamplesizeyesIndividualsmovingrangeNoNoConstantsamplesize?yesU-ChartC-ChartNoyesP-ChartNP-ChartNoyes SPCSix 6 6s s s
104、sSigmaDetecting Lack of control“Rulesoftheroad”Startwithrule#1andpatternDetectionrulesIfhighsensitivityisneed,gowith#2,3,&4Rule#1:OnepointoutsidetheUCLorLCL(3-sigmalimit)Rule#2:Twoofthreeconsecutiveoutsidethe2-sigmalimitRule#3:Fouroffiveconsecutiveoutsidetheone-sigmalimitRule#4:Eightconsecutiveonone
105、sideofthecenterlinePatternRule:APatternrepeatsitselfRuntheMinitabmacrosInRuntheMinitabmacrosInStat Control Charts X-Bar - (Open Tests choose Rules ) SPCSix 6 6s s s sSigma CapabilitySteps to a Capability Study1.Setuptheprocesstoyour“bestguess”bestsetupandrecordthevaluesofyoukeyprocessinputvariables.
106、2.Identifyareasonablewaytocreaterationalsubgroups.3.Runtheproductoverashortperiodoftimetominimizetheimpactofspecialcausevariationaspossible.Approximately30timepointsarethetargetfordatacollection.4.Haveyourteamcarefullyobservetheprocessandtakeplentyofnotes.5.Measureandrecordvaluesforthekeyprocessoutp
107、utvariableSix 6 6s s s sSigmaSteps to a Capability Study6.RuncapabilitySix-packandreview:NormalPlotSPCCharts(checkforstability,Accuracy)Histogram7.RuntheCapabilityMacroforboththepooledandtheoverallstandarddeviations.Completetheworksheet.8.DiagnoseforMeanShiftandVarianceinflation9.EstimateLong-TermCa
108、pability10.Developactionplanbasedondiagnostics. CapabilitySix 6 6s s s sSigmaCapability summary SheetManytimeyouwillbeinterestedinthecapabilityofmorethanonekeyoutputorkeyinputvariable.Usethecapabilitysummarysheettotrackthestatusonthevariablesofinterest. CapabilitySix 6 6s s s sSigmaTypesofCapability
109、Indexes Instantaneous Capability :ProcessCapabilityoveranextremelyshortperiodoftime.Thisshouldrepresenttheverybestperformaprocessiscapableofoverashorttime.Thisshouldbeacloseestimateofprocessentitlement.canbeestimatedusingthe“bestrun”ofashort-termorlong-termstudy. Short-Term Capability : capabilityst
110、udybasedon3050datapoints.Usuallyequaltoorgreaterthanlong-termcapabilitylong-Term Capability : CapabilitystudybasesonalargenumberofdatapointsBestestimateoftrueprocesscapabilityDiagnosticscanbemadefromthisdata CapabilitySix 6 6s s s sSigmaGoal SettingThis is a generic sequence of process improvement :
111、Near Term Goal : MovethePpktoPp(Centertheprocess)Mid Term Goal : MovethePptoCpk(reduceVariation)Long-Term Goal : MoveCpktoCp(RandomVariation)Answers to Capability Questions Describe dynamics and actions for the following scenarios :Cp 1.00 Inherentrandomvariabilityissmallenoughfortheprocesstoconsist
112、entlymeetcustomerspec Cp 1.00 Inherentrandomvariabilitytolarge.Processchangerequired CapabilitySix 6 6s s s sSigmaAnswers to Capability Questions Describe dynamics and actions for the following scenarios :Ppk Cp Therearespecialcauseshiftsanddriftsthatdrivevariabilityoverandaboverandomvariation.Impro
113、vedcontrolisthefocus. Ppk is close to Cp Process in good state of statistical control Cp 1.00 and Ppk Cp Boyareyouintroublenow,EliminatespecialcauseandinvestigatepotentialimpactofAPC(Automatedprocesscontrol) CapabilitySix 6 6s s s sSigmaAnswers to Capability Questions ( Continued ) Cp 1.00 and Ppk 1
114、.00 and Ppk is close to CpLittleopportunityforimprovement CapabilitySix 6 6s s s sSigmaPerformance and Capability MatrixDoes Capability meet Customer Needs ?Does Performance meet capabilityChange ProcessImprove ControlChange ProcessImprove ControlLittle Opportunity for ImprovementNo ( Ppk Cp )Yes (P
115、pk = Pk )No ( Cp Goal )CpPpCpkPpkVariabilityBest Possible Actual ( Total )Location of process MeanMidpoint of Spec RangeActual CapabilitySix 6 6s s s sSigmaProcess Performance and Capability ProcessPerformance:TotalVariationincludingshiftsanddrifts.Istheprocesses“real”performance(PpandPpk)Capability
116、:Onlyrandomorshorttermvariability,isthe“Potential”oftheprocess(CpandCpk)ThePpkcancloselyapproachtheCpk,When:TheCustomerspecificationstrulyreflectcustomerrequirementsTheprocessinunderstatisticalcontrolThedataapproximatethenormaldistributionTheCpislikeabenchmarkorentitlementTheSigmaforcapabilityisdriv
117、enprimarilybyrandomerrorWewouldlikePpktobeveryclosetoCpStatisticalprocesscontrol(SPC)isthefirststepAutomatedprocesscontrol(APC)isnextifnecessary CapabilitySix 6 6s s s sSigmaDiagnosing Capability Data ( 1 )UsingMinitabsCapability,wecantellalotaboutthedynamicsofaprocess.Atleastfourgeneralsourcesofvar
118、iationcanoccurwithanyprocess:1.ChronicMeanShift:whenthemeanshiftsandstayshifted.2.AcuteMeanShifts:whenthemeanofthesubgroupsshiftforshortperiodsoftime3.Withinsubgroupchangesinvariationovertime4.Chronicchangesinvariation:whenvariationwithinsubgroupsgraduallygetslargerorsmallerovertime CapabilitySix 6
119、6s s s sSigmaDiagnosing Capability Data ( 2 )WecanpickupthesepatternsfrominvestigatingdifferenceCpsandCpk”swhenusingthepooled and overall standard deviations ( if subgroup size = 1 ,choose Average moving Range )WecanalsoseepatternsbetweenandwithinsubgroupsusingtheCapabilitySixpacksgraphs Go to Stat
120、Quality Tools Capability Analysis ( Normal ) or Capability Sixpack ( Normal ) CapabilitySix 6 6s s s sSigmaFinal Report FormatSix Sigma Black belt Report OutlineThe following is a generic final report format Blackbelt will submit to their Six Sigma Champions and the Director, Six Sigma Implementatio
121、n. The format may be modified based on individual projects.I. IntroductionA. Team AcknowledgmentB. Executive Summary1. Problem Description2. Solution Strategy3. Summary of Six Sigma Tools4. Results and ConclusionsSix 6 6s s s sSigmaII. Measurement PhaseA. Process DescriptionB. Process MapC. Cause &
122、Effects Matrix SummaryD. Measurement Studies (Abstracts)E. Capability Studies (Abstracts)1. Short-Term Estimates2. Long-Term EstimatesF. Summary of Measurement PhaseIII. Analysis PhaseA. Multi-vari Studies (Abstracts)B. FMEA SummaryC. Rifle Shot Studies (Abstracts)C. Summary of Analysis PhaseFinal R
123、eport FormatSix 6 6s s s sSigmaFinal Report FormatIV.Improvement PhaseA. Experiments (Abstracts)1. Objective2. Output Variables3. Input Variables and Design4. Results and ConclusionsV.Control PhaseA. Summary of Control Plan DevelopmentB. Control Plan Summary SheetC. Documented Sustainability1. Trend Charts2. Summary DataVI. Summary of Tools UsedVII. Summary of ResultsA. Six Sigma Metric ImprovementB. Business impact in Dollars
