六西格玛工序控制与工序能力教材课件

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Six-SigmaDec18,20011BPTLConfidentialSix-SigmaSix-Sigma1BPTLCon

數据分布2BPTLConfidential

NormalExponentialWeibullLognormaltc2fContinuousDistributionsSamplingDistributions數据分布3BPTLConfidential

Themostwidelyusedmodelforthedistributionofcontinuousrandomvariable.Arisesinthestudyofnumerousphysicalphenomena,suchasthevelocityofmolecules.正態分布PlotisknownasProbabilityDensityFunctionofX4BPTLConfidentialThemostwidelyusedmodelforManynaturalphenomenaandman-madeprocessesareobservedtohavenormaldistributions,orcanbecloselyrepresentedasnormallydistributed.Forexample,thelengthofamachinedpartisobservedtovaryaboutitsmeandueto:temperaturedrift,humiditychange,vibrations,cuttinganglevariations,cuttingtoolwear,bearingwear,rotationalspeedvariations,fixturingvariations,rawmaterialchangesandcontaminationlevelchangesIfthesesourcesofvariationaresmall,independentandequallylikelytobepositiveornegative,thelengthwillcloselyapproximateanormaldistribution.正態分布5BPTLConfidentialManynaturalphenomenaandmanFirstintroducedbyFrenchmathematicianAbrahamDeMoivrein1733.Madefamousin1809byGermanmathematicianK.F.Gausswhenhealsodevelopedanormaldistributionindependentlyanduseditinhisstudyofastronomy.Asaresult,itisalsoknownastheGaussiandistribution.Duringmidtolatenineteenthcentury,manystatisticiansbelievedthatitwas“normal”formostwell-behaveddatatofollowthiscurve.正態分布-歷程表KarlFriedrichGauss6BPTLConfidentialFirstintroducedbyFrenchmat正態分布易于理解,具有特性,統計學提供了許多基于正態分布的強有力的分析方法來幫助人們做決定.因此,我們通常會試圖用正態分布去近似模擬其它分布(如可能)或轉化數据以“使”它遵從正態分布.它是分析過程能力的首選分布形式.正態分布7BPTLConfidential正態分布易于理解,具有特性,統計學提供了許多基于正態分布Anormaldistributioncanbecompletelydescribedbyknowingonlythe:Mean(m)Variance(s2)正態分布的一些特性DistributionOneDistributionTwoDistributionThreeWhatisthedifferencebetweenthe3normaldistributions?X~N(m,s2)18BPTLConfidentialAnormaldistributioncanbecA~Normal(A,A²)B~Normal(B,B²)A~Normal(A,A²)B~Normal(B,B²)A~Normal(A,A²)B~Normal(B,B²)WhatisthedifferencebetweenprocessA&Bforeachcase?正態分布的一些特性9BPTLConfidentialA~Normal(A,A²)B~Normal(B,BThemean,medianandmodeallcoincideatthesamevalue-m.Thereisperfectsymmetry.µ+¥-¥MeanMedianMode2Themeanrepresentsthearithmeticaverageofallobservationsinadataset. Ifasetofobservationsisarrangedinanincreasingorderofmagnitude(rankeddata),themiddlevalueiscalledthemedian.Ifthenumberofobservationsisodd,themedianisthevalueofthemiddlenumber.Ifthenumberofobservationsiseven,thereare2middlenumbers,andthemedianistheaverageofthe2values.Themodeistheobservationthatoccursmostfrequentlyinthesample.正態分布的一些特性10BPTLConfidentialThemean,medianandmodeallTheareaundersectionsofthecurvecanbeusedtoestimatethecumulativeprobabilityofacertain“event”occurring:µPointofInflection1s+¥-¥68.27%95.45%99.73%m+/-3sisoftenreferredtoasthewidthofanormaldistribution3正態分布的一些特性11BPTLConfidentialTheareaundersectionsoftheLet’scomputethecumulativeprobabilitiesofthefollowingdistributions:+¥-¥m=3.5s=0.61.8+¥-¥20.0m=16.6s=2.8+¥-¥m=-1.5s=0.9-2.80.5正態分布的一些特性12BPTLConfidentialLet’scomputethecumulativepMiniTab:CalcðProbabilityDistributionsðNormal...EntermvalueEntersvalueEnterxvalue正態分布的一些特性13BPTLConfidentialMiniTab:EnterEnterEnter正態分布什么是6σ???14BPTLConfidential什么是6σ???14BPTLConfidential6σ簡介15BPTLConfidential6σ簡介15BPTLConfidentialTheFocusofSixSigmaIdentifyingcritical

aspectsofthebusinesswithproblemsoropportunitiesforimprovement.TargetingthosecriticalareasanddesignatingimprovementeffortsasSixSigmaBlackBeltprojects.Selectingtoppeopletoworkontheprojects--fulltime.Ensuringthesepeoplehavethetime,tools,andresourcestheyneedtosucceed.16BPTLConfidentialTheFocusofSixSigmaIdentifyCustomerFocus:AModelForSuccessTechnologyTechnologyCapabilityCapabilityOrganizationOrganizationPeoplePeopleProcessesProcesses商務上的生存競爭有賴于我們多大程度上讓我們的客戶滿意.客戶滿意才能体現品質,价格,和貨期的意義.品質,成本,准時走貨無不依耐于工序能力.WhatpurposeisSix-sigma?17BPTLConfidentialCustomerFocus:AModelForSSixSigmaVisionTheVisionofSixSigmaistodelightcustomersbydeliveringworld-classqualityproductsthroughtheachievementofSixSigmalevelsofperformanceineverythingwedo.WhatpurposeisSix-sigma?SixSigmaPhilosophyThephilosophyofSixSigmaistoapplyastructured,systematicapproachtoachievebreakthroughimprovementacrossallareasofourbusiness.18BPTLConfidentialSixSigmaVisionTheVisionofPPMProcessCapabilityDefectsperMillionOpp.SixSigma-AggressiveGoalWhatpurposeisSix-sigma?19BPTLConfidentialPPMProcessDefectsperSixSigmStatisticalDefinitionofn-SigmaLSLLSLUSLUSLProcessWidthmoDesignWidthTTscaleLSLLSLUSLUSLscaleTT+nsscale-nsThisistheso-calledn-sigmaSigmaisastatisticalunitofmeasurethatreflectsprocesscapability.Thesigmascaleofmeasureisperfectlycorrelatedtosuchcharacteristicsasdefects-per-unit,parts-permilliondefective,andtheprobabilityofafailure/error.20BPTLConfidentialStatisticalDefinitionofn-SiStatisticalDefinitionof6σThisisthesix-sigmawesaidLSLLSLUSLUSLProcessWidthmoDesignWidth-3sst+3sstTT.001ppm>USL.001ppm<LSLscaleLSLLSLUSLUSLscaleTT+6sstscale-6sst21BPTLConfidentialStatisticalDefinitionof6σT3Sigma6Sigma5Sigma4Sigma93.32%99.379%99.9767%99.99966%HistoricalCurrentIntermediateLong-RunSigmaLong-TermYieldStandard6σ-PerformanceTarget22BPTLConfidential3Sigma6Sigma5Sigma4SCharacterizeOptimizeBreakthroughUSLTLSLUSLTLSLTUSLLSLUSL’LSL’TheStrategy23BPTLConfidentialCharacterizeUSLTLSLUSLTLSLTUSLBreakthroughStrategyCharacterizationPhase1:MeasurementPhase2:AnalysisOptimizationPhase3:ImprovementPhase4:ControlTheBreakthroughPhases24BPTLConfidentialBreakthroughStrategyCharacteriPhase2:AnalysisCapabilitystudy(Cpk)GR&RstudyCause&effectanalysisFishboneandC&EmatrixDotplot,Boxplot,Histogramchart,ParetochartTheBreakthroughPhases

Analysistoolandmethod25BPTLConfidentialPhase2:AnalysisCapabilitystImprovementAnalysisrolledthroughputyieldSetupprocessMapSetupFMEAandcontrol………….TheBreakthroughPhases

Improvementtoolandmethod26BPTLConfidentialImprovementAnalysisrolledSet工序能力分析Dec18,200127BPTLConfidential工序能力分析27BPTLConf學習目標工序控制与工序能力工序能力:規格,工藝和控制的界限工序潛力与工序表現短期与長期工序能力“6σ”品質28BPTLConfidential學習目標工序控制与工序能力28BPTL工序控制与工序能力

1. 工序控制意即工序運作處于統計控制狀態,換言之,普遍的原因是變化的僅有來源.鑒于“用事實說話”,即一個人僅需要用源于工序的數据來判定工序是處于受控狀態.過程的跟蹤表現來証實它是否建立了長時間穩定的數据分布表現,典型地,用帶有“僅從工序中的數据計算出的”控制圖表.

“而且一個工序在受控”并不一定意味著它是一個好工序.29BPTLConfidential工序控制与工序能力

1. 工序控制29BPTLConfi工序控制与工序能力2. 工序能力“好處”是工序能力可被度量比較“工序的現狀”与“客戶的要求

”,均須以規格為依据度量一個穩定的工序狀態(受控制)在多大程度上能滿足客戶的規格.30BPTLConfidential工序控制与工序能力2. 工序能力30BPTLConf變化的類型固有的或定值的變化許多微小又不可避免的原因導致的累積效果只有微小的机會導致變化的運作工序稱為“統計控制”31BPTLConfidential變化的類型固有的或定值的變化31BPTLConfident變化的類型特定或確定的變化可能由于a)不正確的調机 b)操作者錯誤 c)有缺陷的原材料一個工序如果出現上面的變化則稱為“失控”.32BPTLConfidential變化的類型特定或確定的變化32BPTLConfidenti工序能力工序能力研究能:

顯示工序輸出的恒定性顯示輸出符合規格的程度用于和另一工序或競爭對手比較33BPTLConfidential工序能力工序能力研究能:33BPTLConfidenti工序能力與規格极限a)b)c)a)工序能力高b)工序能力能夠滿足c)工序能力不足夠34BPTLConfidential工序能力與規格极限a)b)c)34BPTLConfiden三種极限類型規格极限(LSLandUSL)

createdbydesignengineeringinresponsetocustomerrequirementstospecifythetoleranceforaproduct’scharacteristic工序极限(LPLandUPL)measuresthevariationofaprocessthenatural6limitsofthemeasuredcharacteristic控制极限(LCLandUCL)measuresthevariationofasamplestatistic(mean,variance,proportion,etc)35BPTLConfidential三種极限類型規格极限(LSLandUSL)工序能力指數工序能力的兩种度量:工序潛力Cp

工序表現Cpu

Cpl

Cpk

36BPTLConfidential工序能力指數工序能力的兩种度量:36BPTLConfide工序潛力

Cp指標顯示實際工差(6)是否超出規格.公式37BPTLConfidential工序潛力

Cp指標顯示實際工差(6)是否超出規格.公工序潛力傳統上,Cp有1.0時顯示工序能力被判為“有能力考核成績”.若數据集中于工程工差內,將僅有0.27%的工件會超差. Cp 拒貨率 1.00 0.270% 1.33 0.007% 1.50 6.8ppm 2.00 2.0ppb38BPTLConfidential工序潛力傳統上,Cp有1.0時顯示工序能力被判為“有工序潛力a)b)c)a)工序能力高(Cp>2)b)工序能力可(Cp=1to2)c)工序能力差(Cp<1)39BPTLConfidential工序潛力a)b)c)39BPTLConfidential工序潛力TheCpindexcomparestheallowablespread(USL-LSL)againsttheprocessspread(6).Itfailstotakeintoaccountiftheprocessiscenteredbetweenthespecificationlimits.ProcessiscenteredProcessisnotcentered40BPTLConfidential工序潛力TheCpindexcomparesthe工序表現TheCpkindexrelatesthescaleddistancebetweentheprocessmeanandthenearestspecificationlimit.41BPTLConfidential工序表現TheCpkindexrelatesthe工序表現 Cpk 不良率 1.0 0.13–0.27% 1.1 0.05–0.10% 1.2 0.02–0.03% 1.3 48.1–96.2ppm 1.4 13.4–26.7ppm 1.5 3.4–6.8ppm 1.6 794–1589ppb 1.7 170–340ppb 1.8 33–67ppb 1.9 6–12ppb 2.0 1–2ppb42BPTLConfidential工序表現 Cpk 不良率42BPTLConfi工序表現a)工序能力高(Cpk>1.5)b)工序能力可(Cpk=1to1.5)c)工序能力差(Cpk<1)a)Cp=2Cpk=2b)Cp=2Cpk=1c)Cp=2Cpk<143BPTLConfidential工序表現a)Cp=2b)Cp=2c)Cp=243工序潛力与工序表現(a)PoorProcessPotential (b)PoorProcessPerformanceLSLUSLLSLUSLExperimentalDesigntoreducevariationExperimentalDesigntocentermeantoreducevariation44BPTLConfidential工序潛力与工序表現(a)PoorProcessPote工序潛力与工序表現a)Cp=2Cpk=2b)Cp=2Cpk=1c)Cp=2Cpk<145BPTLConfidential工序潛力与工序表現a)Cp=2b)Cp=2c)Cp工序穩定性Aprocessisstableifthedistributionofmeasurementsmadeonthegivenfeatureisconsistentovertime.TimeStableProcessTimeUnstableProcessucllclucllcl46BPTLConfidential工序穩定性Aprocessisstableifth短期工序能力与長期工序能力短期工序能力(previouslycalledshort-termcapability)showstheinherentvariabilityofamachine/processoperatingwithinabriefperiodoftime.長期工序能力(previouslycalledlong-termcapability)showsthevariabilityofamachine/processoperatingoveraperiodoftime.Itincludessourcesofvariationinadditiontotheshort-termvariability.47BPTLConfidential短期工序能力与長期工序能力短期工序能力(previously Within OverallSampleSize 30–50units 100unitsNumberofLots singlelot severallotsPeriodofTime hoursordays weeksormonthsNumberofOperators singleoperator differentoperatorsProcessPotential Cp Pp

ProcessPerformance Cpk Ppk

短期工序能力与長期工序能力48BPTLConfidential Within Overall短期工序能力与長期工實戰演練Thelengthofacamshaftforanautomobileengineisspecifiedat600±2mm.Controlofthelengthofthecamshaftiscriticaltoavoidscrap/rework.Thecamshaftisprovidedbyexternalsuppliers.Assesstheprocesscapabilityforthissupplier.ThedataisavailableinCamshaft.MTW.Dataarecollectedinsubgroupsof5each.49BPTLConfidential實戰演練ThelengthofacamshaftfExample4Minitab:StatQualityToolsCapabilityAnalysis(Normal)50BPTLConfidentialExample4Minitab:50BPTLConfidExample451BPTLConfidentialExample451BPTLConfidentialExample5Histogramofthecamshaftlengthsuggestsmixedpopulations.Furtherinvestigationrevealedthattherearetwosuppliersforthecamshaft.Datawerenowcollectedoncamshaftsfromeachsourcewithoutcombiningboth.Subgroupsizeis5foreachsupplier.Arethetwosupplierssimilarinperformance?Ifnot,whatareyourrecommendations?52BPTLConfidentialExample5HistogramofthecamsExample5MiniTab:StatQualityToolsCapabilitySixpack(Normal)53BPTLConfidentialExample5MiniTab:53BPTLConfidExample554BPTLConfidentialExample554BPTLConfidentialExample555BPTLConfidentialExample555BPTLConfidential用Box-Cox轉化后的工序能力分析Whentheprocessdataarenotnormal,theCpkorPpkindicesarenotaccurateorreliable,becausetheseindicesarecomputedonthebasisthatthedataarenormallydistributed.Dppmvaluesassociatedwiththeindiceswillnotbeneartotheactualperformancewhenthenormalcurvedoesnotmodeltheactualdatawell.56BPTLConfidential用Box-Cox轉化后的工序能力分析WhentheprIftheprocessdataaresomewhatbell-shapedbutskewed,Box-Coxtransformationcanbeusedtomakethedatanormalbeforeweassesstheprocesscapability.RemembertotransformthespecificationlimitstoobeforewecomputeCpkorPpk!用Box-Cox轉化后的工序能力分析57BPTLConfidentialIftheprocessdataaresomewhMinitab:StatQualityToolsCapabilityAnalysis(Normal)用Box-Cox轉化后的工序能力分析58BPTLConfidentialMinitab:用Box-Cox轉化后的工序能力分析58BExample6OpenthefilenamedDimension.MTWintheDay-2folderagain.Computetheprocesscapabilitywiththespecificationlimits:LSL:0.1 USL:10Arethedatanormallydistributed?ComputetheprocesscapabilityagainwithBox-Coxtransformation.用Box-Cox轉化后的工序能力分析59BPTLConfidentialExample6OpenthefilenamedDCpkof0.41isreportedintheSSATpackage.Thisvalueisnotreliableoraccurateifthedataarenotnormal.DataisnotnormalExample6用Box-Cox轉化后的工序能力分析60BPTLConfidentialCpkof0.41isreportedintheExample6Cpkhasincreasedfrom0.41to0.81用Box-Cox轉化后的工序能力分析61BPTLConfidentialExample6CpkhasincreasedfroWhat’s“6”Quality—ThenOriginalDefinitionbyMotorola:Intheshortterm,thespecificationlimitsareatleast±6awayfromtheprocessmean,i.e.Cp2,Inthelongrun,theprocesswillshiftbylessthan1.5,i.e.Ppk1.5,Theprocesswillyieldlessthan3.4dppmrejectedparts.66Shift1.54.5“SigmaLevel”Capability62BPTLConfidentialWhat’s“6”Quality—ThenOrWhat’sSixSigmaQuality—NowMikelJHarryclaimsthattheprocessmeanbetweenlotswillvary,withanaverageprocessshiftof1.5.k=z+1.5

k=z+1.5Shift1.5zNote: SigmaCapability=ƒ(dpmo)ƒ(dppm)“SigmaLevel”Capability63BPTLConfidentialWhat’sSixSigmaQuality—NTypesofVariation1. PositionalVariation

Sameprocess,variationatdifferinglocationssimultaneously:TemperaturevariationsinsideathermalchamberCavity-to-cavityvariationsinaninjectionmold2. CyclicalVariation

Sequentialrepetitionsofaprocessoverfairlyshorttime,say,lessthan15mins:VariationsbetweenconsecutivebatchesofaprocessDifferencesfromlottolotofrawmaterials64BPTLConfidentialTypesofVariation1. PositionTypesofVariation3.TemporalVariation Variationsoverlongerperiodsoftime,suchaseveralhours,daysorweeks.65BPTLConfidentialTypesofVariation3.TemporalMeasurementSystemAnalysisApproachTherearetwotypesofmeasurementspossible:VariableDatacanbedescribedonacontinuousscaleAttributeDatacannotbeadequatelydescribedonacontinuousscalePass/Fail,verylowcounts

Eachmustbeapproacheddifferently.66BPTLConfidentialMeasurementSystemAnalysisAp

Six-SigmaTrainingBook

Six-SigmaDec18,200167BPTLConfidentialSix-SigmaSix-Sigma1BPTLCon

數据分布68BPTLConfidential

NormalExponentialWeibullLognormaltc2fContinuousDistributionsSamplingDistributions數据分布69BPTLConfidential

Themostwidelyusedmodelforthedistributionofcontinuousrandomvariable.Arisesinthestudyofnumerousphysicalphenomena,suchasthevelocityofmolecules.正態分布PlotisknownasProbabilityDensityFunctionofX70BPTLConfidentialThemostwidelyusedmodelforManynaturalphenomenaandman-madeprocessesareobservedtohavenormaldistributions,orcanbecloselyrepresentedasnormallydistributed.Forexample,thelengthofamachinedpartisobservedtovaryaboutitsmeandueto:temperaturedrift,humiditychange,vibrations,cuttinganglevariations,cuttingtoolwear,bearingwear,rotationalspeedvariations,fixturingvariations,rawmaterialchangesandcontaminationlevelchangesIfthesesourcesofvariationaresmall,independentandequallylikelytobepositiveornegative,thelengthwillcloselyapproximateanormaldistribution.正態分布71BPTLConfidentialManynaturalphenomenaandmanFirstintroducedbyFrenchmathematicianAbrahamDeMoivrein1733.Madefamousin1809byGermanmathematicianK.F.Gausswhenhealsodevelopedanormaldistributionindependentlyanduseditinhisstudyofastronomy.Asaresult,itisalsoknownastheGaussiandistribution.Duringmidtolatenineteenthcentury,manystatisticiansbelievedthatitwas“normal”formostwell-behaveddatatofollowthiscurve.正態分布-歷程表KarlFriedrichGauss72BPTLConfidentialFirstintroducedbyFrenchmat正態分布易于理解,具有特性,統計學提供了許多基于正態分布的強有力的分析方法來幫助人們做決定.因此,我們通常會試圖用正態分布去近似模擬其它分布(如可能)或轉化數据以“使”它遵從正態分布.它是分析過程能力的首選分布形式.正態分布73BPTLConfidential正態分布易于理解,具有特性,統計學提供了許多基于正態分布Anormaldistributioncanbecompletelydescribedbyknowingonlythe:Mean(m)Variance(s2)正態分布的一些特性DistributionOneDistributionTwoDistributionThreeWhatisthedifferencebetweenthe3normaldistributions?X~N(m,s2)174BPTLConfidentialAnormaldistributioncanbecA~Normal(A,A²)B~Normal(B,B²)A~Normal(A,A²)B~Normal(B,B²)A~Normal(A,A²)B~Normal(B,B²)WhatisthedifferencebetweenprocessA&Bforeachcase?正態分布的一些特性75BPTLConfidentialA~Normal(A,A²)B~Normal(B,BThemean,medianandmodeallcoincideatthesamevalue-m.Thereisperfectsymmetry.µ+¥-¥MeanMedianMode2Themeanrepresentsthearithmeticaverageofallobservationsinadataset. Ifasetofobservationsisarrangedinanincreasingorderofmagnitude(rankeddata),themiddlevalueiscalledthemedian.Ifthenumberofobservationsisodd,themedianisthevalueofthemiddlenumber.Ifthenumberofobservationsiseven,thereare2middlenumbers,andthemedianistheaverageofthe2values.Themodeistheobservationthatoccursmostfrequentlyinthesample.正態分布的一些特性76BPTLConfidentialThemean,medianandmodeallTheareaundersectionsofthecurvecanbeusedtoestimatethecumulativeprobabilityofacertain“event”occurring:µPointofInflection1s+¥-¥68.27%95.45%99.73%m+/-3sisoftenreferredtoasthewidthofanormaldistribution3正態分布的一些特性77BPTLConfidentialTheareaundersectionsoftheLet’scomputethecumulativeprobabilitiesofthefollowingdistributions:+¥-¥m=3.5s=0.61.8+¥-¥20.0m=16.6s=2.8+¥-¥m=-1.5s=0.9-2.80.5正態分布的一些特性78BPTLConfidentialLet’scomputethecumulativepMiniTab:CalcðProbabilityDistributionsðNormal...EntermvalueEntersvalueEnterxvalue正態分布的一些特性79BPTLConfidentialMiniTab:EnterEnterEnter正態分布什么是6σ???80BPTLConfidential什么是6σ???14BPTLConfidential6σ簡介81BPTLConfidential6σ簡介15BPTLConfidentialTheFocusofSixSigmaIdentifyingcritical

aspectsofthebusinesswithproblemsoropportunitiesforimprovement.TargetingthosecriticalareasanddesignatingimprovementeffortsasSixSigmaBlackBeltprojects.Selectingtoppeopletoworkontheprojects--fulltime.Ensuringthesepeoplehavethetime,tools,andresourcestheyneedtosucceed.82BPTLConfidentialTheFocusofSixSigmaIdentifyCustomerFocus:AModelForSuccessTechnologyTechnologyCapabilityCapabilityOrganizationOrganizationPeoplePeopleProcessesProcesses商務上的生存競爭有賴于我們多大程度上讓我們的客戶滿意.客戶滿意才能体現品質,价格,和貨期的意義.品質,成本,准時走貨無不依耐于工序能力.WhatpurposeisSix-sigma?83BPTLConfidentialCustomerFocus:AModelForSSixSigmaVisionTheVisionofSixSigmaistodelightcustomersbydeliveringworld-classqualityproductsthroughtheachievementofSixSigmalevelsofperformanceineverythingwedo.WhatpurposeisSix-sigma?SixSigmaPhilosophyThephilosophyofSixSigmaistoapplyastructured,systematicapproachtoachievebreakthroughimprovementacrossallareasofourbusiness.84BPTLConfidentialSixSigmaVisionTheVisionofPPMProcessCapabilityDefectsperMillionOpp.SixSigma-AggressiveGoalWhatpurposeisSix-sigma?85BPTLConfidentialPPMProcessDefectsperSixSigmStatisticalDefinitionofn-SigmaLSLLSLUSLUSLProcessWidthmoDesignWidthTTscaleLSLLSLUSLUSLscaleTT+nsscale-nsThisistheso-calledn-sigmaSigmaisastatisticalunitofmeasurethatreflectsprocesscapability.Thesigmascaleofmeasureisperfectlycorrelatedtosuchcharacteristicsasdefects-per-unit,parts-permilliondefective,andtheprobabilityofafailure/error.86BPTLConfidentialStatisticalDefinitionofn-SiStatisticalDefinitionof6σThisisthesix-sigmawesaidLSLLSLUSLUSLProcessWidthmoDesignWidth-3sst+3sstTT.001ppm>USL.001ppm<LSLscaleLSLLSLUSLUSLscaleTT+6sstscale-6sst87BPTLConfidentialStatisticalDefinitionof6σT3Sigma6Sigma5Sigma4Sigma93.32%99.379%99.9767%99.99966%HistoricalCurrentIntermediateLong-RunSigmaLong-TermYieldStandard6σ-PerformanceTarget88BPTLConfidential3Sigma6Sigma5Sigma4SCharacterizeOptimizeBreakthroughUSLTLSLUSLTLSLTUSLLSLUSL’LSL’TheStrategy89BPTLConfidentialCharacterizeUSLTLSLUSLTLSLTUSLBreakthroughStrategyCharacterizationPhase1:MeasurementPhase2:AnalysisOptimizationPhase3:ImprovementPhase4:ControlTheBreakthroughPhases90BPTLConfidentialBreakthroughStrategyCharacteriPhase2:AnalysisCapabilitystudy(Cpk)GR&RstudyCause&effectanalysisFishboneandC&EmatrixDotplot,Boxplot,Histogramchart,ParetochartTheBreakthroughPhases

Analysistoolandmethod91BPTLConfidentialPhase2:AnalysisCapabilitystImprovementAnalysisrolledthroughputyieldSetupprocessMapSetupFMEAandcontrol………….TheBreakthroughPhases

Improvementtoolandmethod92BPTLConfidentialImprovementAnalysisrolledSet工序能力分析Dec18,200193BPTLConfidential工序能力分析27BPTLConf學習目標工序控制与工序能力工序能力:規格,工藝和控制的界限工序潛力与工序表現短期与長期工序能力“6σ”品質94BPTLConfidential學習目標工序控制与工序能力28BPTL工序控制与工序能力

1. 工序控制意即工序運作處于統計控制狀態,換言之,普遍的原因是變化的僅有來源.鑒于“用事實說話”,即一個人僅需要用源于工序的數据來判定工序是處于受控狀態.過程的跟蹤表現來証實它是否建立了長時間穩定的數据分布表現,典型地,用帶有“僅從工序中的數据計算出的”控制圖表.

“而且一個工序在受控”并不一定意味著它是一個好工序.95BPTLConfidential工序控制与工序能力

1. 工序控制29BPTLConfi工序控制与工序能力2. 工序能力“好處”是工序能力可被度量比較“工序的現狀”与“客戶的要求

”,均須以規格為依据度量一個穩定的工序狀態(受控制)在多大程度上能滿足客戶的規格.96BPTLConfidential工序控制与工序能力2. 工序能力30BPTLConf變化的類型固有的或定值的變化許多微小又不可避免的原因導致的累積效果只有微小的机會導致變化的運作工序稱為“統計控制”97BPTLConfidential變化的類型固有的或定值的變化31BPTLConfident變化的類型特定或確定的變化可能由于a)不正確的調机 b)操作者錯誤 c)有缺陷的原材料一個工序如果出現上面的變化則稱為“失控”.98BPTLConfidential變化的類型特定或確定的變化32BPTLConfidenti工序能力工序能力研究能:

顯示工序輸出的恒定性顯示輸出符合規格的程度用于和另一工序或競爭對手比較99BPTLConfidential工序能力工序能力研究能:33BPTLConfidenti工序能力與規格极限a)b)c)a)工序能力高b)工序能力能夠滿足c)工序能力不足夠100BPTLConfidential工序能力與規格极限a)b)c)34BPTLConfiden三種极限類型規格极限(LSLandUSL)

createdbydesignengineeringinresponsetocustomerrequirementstospecifythetoleranceforaproduct’scharacteristic工序极限(LPLandUPL)measuresthevariationofaprocessthenatural6limitsofthemeasuredcharacteristic控制极限(LCLandUCL)measuresthevariationofasamplestatistic(mean,variance,proportion,etc)101BPTLConfidential三種极限類型規格极限(LSLandUSL)工序能力指數工序能力的兩种度量:工序潛力Cp

工序表現Cpu

Cpl

Cpk

102BPTLConfidential工序能力指數工序能力的兩种度量:36BPTLConfide工序潛力

Cp指標顯示實際工差(6)是否超出規格.公式103BPTLConfidential工序潛力

Cp指標顯示實際工差(6)是否超出規格.公工序潛力傳統上,Cp有1.0時顯示工序能力被判為“有能力考核成績”.若數据集中于工程工差內,將僅有0.27%的工件會超差. Cp 拒貨率 1.00 0.270% 1.33 0.007% 1.50 6.8ppm 2.00 2.0ppb104BPTLConfidential工序潛力傳統上,Cp有1.0時顯示工序能力被判為“有工序潛力a)b)c)a)工序能力高(Cp>2)b)工序能力可(Cp=1to2)c)工序能力差(Cp<1)105BPTLConfidential工序潛力a)b)c)39BPTLConfidential工序潛力TheCpindexcomparestheallowablespread(USL-LSL)againsttheprocessspread(6).Itfailstotakeintoaccountiftheprocessiscenteredbetweenthespecificationlimits.ProcessiscenteredProcessisnotcentered106BPTLConfidential工序潛力TheCpindexcomparesthe工序表現TheCpkindexrelatesthescaleddistancebetweentheprocessmeanandthenearestspecificationlimit.107BPTLConfidential工序表現TheCpkindexrelatesthe工序表現 Cpk 不良率 1.0 0.13–0.27% 1.1 0.05–0.10% 1.2 0.02–0.03% 1.3 48.1–96.2ppm 1.4 13.4–26.7ppm 1.5 3.4–6.8ppm 1.6 794–1589ppb 1.7 170–340ppb 1.8 33–67ppb 1.9 6–12ppb 2.0 1–2ppb108BPTLConfidential工序表現 Cpk 不良率42BPTLConfi工序表現a)工序能力高(Cpk>1.5)b)工序能力可(Cpk=1to1.5)c)工序能力差(Cpk<1)a)Cp=2Cpk=2b)Cp=2Cpk=1c)Cp=2Cpk<1109BPTLConfidential工序表現a)Cp=2b)Cp=2c)Cp=243工序潛力与工序表現(a)PoorProcessPotential (b)PoorProcessPerformanceLSLUSLLSLUSLExperimentalDesigntoreducevariationExperimentalDesigntocentermeantoreducevariation110BPTLConfidential工序潛力与工序表現(a)PoorProcessPote工序潛力与工序表現a)Cp=2Cpk=2b)Cp=2Cpk=1c)Cp=2Cpk<1111BPTLConfidential工序潛力与工序表現a)Cp=2b)Cp=2c)Cp工序穩定性Aprocessisstableifthedistributionofmeasurementsmadeonthegivenfeatureisconsistentovertime.TimeStableProcessTimeUnstableProcessucllclucllcl112BPTLConfidential工序穩定性Aprocessisstableifth短期工序能力与長期工序能力短期工序能力(previouslycalledshort-termcapability)showstheinherentvariabilityofamachine/processoperatingwithinabriefperiodoftime.長期工序能力(previouslycalledlo