Measure Perance sigma.ppt

MeasurePerformance,IntroductionandDetermineWhattoMeasure,1.0DefineOpportunities,2.0MeasurePerformance,3.0AnalyzeOpportunity,4.0ImprovePerformance,5.0ControlPerformance,1.1ValidateBusinessOpportunity1.2DocumentandAnalyzeProcesses1.3DefineCustomerRequirements1.4BuildEffectiveTeams,2.1Determinewhattomeasure2.2Managemeasurement2.3Understandvariation2.4DetermineSigmaPerformance2.5Excellentteamperformance,3.1processstratificationandAnalysis3.2determinerootcauses3.3validaterootcauses3.4managecreativity,4.1Generateimprovementideas4.2evaluateandselectsolution4.3presentrecommendations4.4Implementchange,5.1DevelopandExecutepilotplan5.2planandimplementsolution5.3processintegration5.4closureandrecognition,ReviewandTransition,InSection1.4,welearnedhowto：Understandtheroleofeffectiveteamsinprocessimprovement.Applyteamevaluationtoolstoidentifyopportunitiestoimproveteameffectiveness.Section2.0，MeasurePerformance,coversthefollowingareas:,PreparedTeam,2.1Determinewhattomeasure,2.2ManageMeasurement,2.4DetermineSigmaperformance,2.3UnderstandVariation,2.5ExcellentTeamPerformance,Summaryof2.0“MeasurePerformance”,2.1DetermineWhattoMeasureUnderstandtherolethatdataplaysinprocessimprovementUnderstandthecauseandeffectrelationshipsthatoccurinsidetheteamsprocessDeterminetheindicatorsneededtoevaluatecurrentprocessperformance2.2ManageMeasurementUnderstanddifferenttypesofdataandhoweachtypecanprovidetheteamwithdifferentinsightsandknowledgeofaprocessDevelopoperationaldefinitionsanddatacollectionplansthatbuildvalidityandconsistencyinthedatawhichtheteamgathers2.3UnderstandVariationUnderstandtheconceptofvariationandhowaprocesscanbeevaluatedbyassessingitsvariationovertimePlotandcalculatethevariationoftheteamsbusinessprocessGainhandsonexperiencewiththeuseofthestatisticalsoftwarepackageMINITABTM2.4DetermineSigmaPerformanceUnderstandthevariouscalculationsassociatedwithdeterminingprocesssigmaCalculatethesigmaperformanceoftheteamsprocessCalculatetherolled-upSigmaforthebusiness2.5ExcelTeamPerformanceUnderstandtheroleofhigh-performanceworkteamsinprocessimprovementUseteamdiagnosticsandassessmentstoevaluatetheteamstrengthsandopportunitiesforimprovingitsownperformance,MeasurePerformance-2.1,DetermineWhattoMeasure,2.1DetermineWhattoMeasure,ObjectiveToidentifydifferenttypesofmeasuresandanunderstandingofhowthemeasuresrelatetocriticalcustomerrequirements.KeyTopicsPerformanceMeasurementInput,Process,andOutputIndicatorsIndicatorRelationships,PerformanceMeasures-CustomerValueAchieved?,ProcessElementsandIndicatorRelationships,Effectiveimprovementrequiresinformationfromtheentiresupplier-customer,causeandeffectrelationship.,Process,StartBoundary_,EndBoundary_,Input,ProcessandOutputIndicators,EfficiencyMeasuresCostpertransactionTimeperactivityAmountofreworkTurnaroundtimeVariabilityofanactivity,EfficiencyMeasuresPercentdefectiveNumberoferrorsTotalresponsetimeInvoice/billingaccuracyRevenue,InputIndicators,ProcessIndicators,OutputPerformanceIndicators,CTQSCTPS,ProcessOutputIndicatorsincludeCTQsthestandarddeviationofsis1.2minutes;andcriticalcustomerrequirementorCCRis10minutes.,SigmaCalculationTable,*note:Thistabledoesnotincludea1.5shift.Ifyouenterthistablewithlong-termdatathenyoucalculatelong-termSigmaandifyouenterwithshort-termdatathenyoucalculateshort-termSigmaBothMotorolaandGECapitalassumethatyouentertheirAbridgedSigmaTablewithlong-termdataandexitwithashort-termSigma.Inordertodothis,theyassumeashiftof1.5Sigmabetweenshort-andlong-termSigma.Therefore,iflong-termyieldequatestoastandardnormalareaof4.5Sigma(or3.4DPMO)thentheyassumea1.5shiftandreportshort-termSigmaof6.0.,*,*,UpperandLowerCCRs,Combineintoasingleyield,CalculationsDefectsgreaterthanUSL=0.299(29.9%)AreafromzerotoUSL=1-0.299=(0.711(71.1%)DefectslessthanLSL=0.013(1.3%)AreafromzerotoLSL=0.013(1.3%)Yield=0.711-.013=0.70(70%)LookupYieldof0.70inSigmaTableZ=0.5(approximately),4.CalculateSigmaPerformance,IContinuous,IIDPMOMethod,Discrete,VSigmaRoll-up,IIIHighVolume,IVLowVolume,CalculatingProcesssigma,Selecttheappropriatemethod,BreakfastExample,Nowletsreviewanexampleofhowprocessoutputs,criticalcustomerrequirements,andthestandardnormaldistributionarecombinedtodeterminetheprocesssigma.Ahotelprovidesroomservicemealstoitsguests,andfromnumerousguestsurveysandresearch,hasdesignedaservicethatguaranteesabreakfastmealdeliverywithin10minutesofthetimerequestedbyitsguest.Theyhavedeterminedanearlydeliverywillinconveniencetheguestaswellasalatedelivery,especiallyinthemorning.Datafromaoneweekoperationhasbeengatheredandisshownhere.Whatistheprocesssigmaofthebreakfastdelivery?,100,0,Frequency,DeliveryTimeDeviation,LowCustomerLimit,UpperCustomerLimit,Target,Defects,CalculatingSigmawithDiscreteData,Takinganotherlookatthe“BreakfastDelivery”datawevebeenusing,letsexamineaverydirectwaytocalculateprocessyield.Byexaminingtherawdata,wecancountthenumberofdeliverytimesthatdonotmeetcustomerrequirementsandtranslatethatdirectlyintoadefectcalculationreferredtoasDefectsPerMillionOpportunities,orDPMO。,DPMODefined,DPMO=DefectsPerMillionOpportunities=1Mxwhere：D*=totalnumberofdefectscountedinthesample:adefectdefinedasfailuretomeetaCCRorCriticalCustomerRequirementN=numberofunitsofproductorserviceO=numberofopportunitiesperunitofproductorserviceforacustomerdefecttooccurM=million*Theremustbeatleast5defectsand5non-defectstousetheDPMOformula.,DPMOExample,Usingthepreviousexample,letscalculatetheDPMOandtheprocesssigmaUsingthismethodfromthedatasetonbreakfastdeliverytimes:D=205N=725O=1（Thereisonlyoneopportunityforadefectperbreakfastdelivery.Eitherthedeliveryiswithinthecustomerlimitsornot.）DPMO=UsingtheSigmaCalculationtable,entertheDPMOcolumnandlookuptheprocesssigmadirectly.TherelationshipbetweenDPMOandprocesssigmaisasfollows:ProcessYield=1-DPUWhereDPU=Defects/unitInourexample,ProcessYield=1-.2826=0.7174or71.74%sigma=.058,SigmaCalculationforBreakfastExample,Objective:TopracticecalculatingSigmaInformationProvided:Mean=5minutesStandard=10minutesUSL=+10minutesLSL=-10minutesQ.DeterminetheSigmaforcontinuousdata,ReviewandTransition,In2.4DetermineSigmaPerformance,welearned:Thevariouscalculationsassociatedwithdeterminingprocesssigma.Howtocalculatethesigmaperformanceoftheteamsprocess.In2.5,ExcelTeamPerformance,wewilllearn:Theroleofhigh-performanceworkteamsinprocessimprovement.Howtouseteamdiagnosticsandassessmentstoevaluatetheteamstrengthsandopportunitiesforimprovingitsownperformance.,ProcessPerformanceBasedonCustomerRequirement,MeasurePerformance2.5,ExcelTeamPerformance,2.5ExcelTeamPerformance,ObjectiveToenabletheteamtoreachahighlevelofperformancefullyutilizingteammemberskills,knowledge,andexperienceworkingcollaboratively.KeyTopicsNormingStageTeamingTechniquesPerformingStage,ProductiveTeamAtmosphere,Summaryof2.0“MeasurePerformance”,2.1DetermineWhattoMeasureUnderstandtherolethatdataplaysinprocessimprovementUnderstandthecauseandeffectrelationshipsthatoccurinsidetheteamsprocessDeterminetheindicatorsneededtoevaluatecurrentprocessperformance2.2ManageMeasurementUnderstanddifferenttypesofdataandhoweachtypecanprovidetheteamwithdifferentinsightsandknowledgeofaprocessDevelopoperationaldefinitionsanddatacollectionplansthatbuildvalidityandconsistencyinthedatawhichtheteamgathers2.3understandVariationUnderstandtheconceptofvariationandhowaprocesscanbeevaluatedbyassessingitsvariationovertimePlotandcalculatethevariationoftheteamsbusinessprocessGainhandsonexperiencewiththeu