六西格瑪工序控制與工序能力教材課件

Six-SigmaTrainingBook

Six-SigmaDec18,20011BPTLConfidentialSix-SigmaSix-Sigma1BPTLCon

數(shù)據(jù)分布2BPTLConfidential

NormalExponentialWeibullLognormaltc2fContinuousDistributionsSamplingDistributions數(shù)據(jù)分布3BPTLConfidential

Themostwidelyusedmodelforthedistributionofcontinuousrandomvariable.Arisesinthestudyofnumerousphysicalphenomena,suchasthevelocityofmolecules.正態(tài)分布PlotisknownasProbabilityDensityFunctionofX4BPTLConfidentialThemostwidelyusedmodelforManynaturalphenomenaandman-madeprocessesareobservedtohavenormaldistributions,orcanbecloselyrepresentedasnormallydistributed.Forexample,thelengthofamachinedpartisobservedtovaryaboutitsmeandueto:temperaturedrift,humiditychange,vibrations,cuttinganglevariations,cuttingtoolwear,bearingwear,rotationalspeedvariations,fixturingvariations,rawmaterialchangesandcontaminationlevelchangesIfthesesourcesofvariationaresmall,independentandequallylikelytobepositiveornegative,thelengthwillcloselyapproximateanormaldistribution.正態(tài)分布5BPTLConfidentialManynaturalphenomenaandmanFirstintroducedbyFrenchmathematicianAbrahamDeMoivrein1733.Madefamousin1809byGermanmathematicianK.F.Gausswhenhealsodevelopedanormaldistributionindependentlyanduseditinhisstudyofastronomy.Asaresult,itisalsoknownastheGaussiandistribution.Duringmidtolatenineteenthcentury,manystatisticiansbelievedthatitwas“normal”formostwell-behaveddatatofollowthiscurve.正態(tài)分布-歷程表KarlFriedrichGauss6BPTLConfidentialFirstintroducedbyFrenchmat正態(tài)分布易于理解,具有特性,統(tǒng)計學(xué)提供了許多基于正態(tài)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(tài)分布去近似模擬其它分布(如可能)或轉(zhuǎn)化數(shù)據(jù)以“使”它遵從正態(tài)分布.它是分析過程能力的首選分布形式.正態(tài)分布7BPTLConfidential正態(tài)分布易于理解,具有特性,統(tǒng)計學(xué)提供了許多基于正態(tài)分布Anormaldistributioncanbecompletelydescribedbyknowingonlythe:Mean(m)Variance(s2)正態(tài)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(tài)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(tài)分布的一些特性10BPTLConfidentialThemean,medianandmodeallTheareaundersectionsofthecurvecanbeusedtoestimatethecumulativeprobabilityofacertain“event”occurring:μPointofInflection1s+￥-￥68.27%95.45%99.73%m+/-3sisoftenreferredtoasthewidthofanormaldistribution3正態(tài)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(tài)分布的一些特性12BPTLConfidentialLet’scomputethecumulativepMiniTab:CalceProbabilityDistributionseNormal...EntermvalueEntersvalueEnterxvalue正態(tài)分布的一些特性13BPTLConfidentialMiniTab:EnterEnterEnter正態(tài)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(wù)上的生存競爭有賴于我們多大程度上讓我們的客戶滿意.客戶滿意才能體現(xiàn)品質(zhì),價格,和貨期的意義.品質(zhì),成本,準(zhǔn)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(xué)習(xí)目標(biāo)工序控制與工序能力工序能力:規(guī)格,工藝和控制的界限工序潛力與工序表現(xiàn)短期與長期工序能力“6σ”品質(zhì)28BPTLConfidential學(xué)習(xí)目標(biāo)工序控制與工序能力28BPTL工序控制與工序能力

1. 工序控制意即工序運作處于統(tǒng)計控制狀態(tài),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(shù)據(jù)來判定工序是處于受控狀態(tài).過程的跟蹤表現(xiàn)來証實它是否建立了長時間穩(wěn)定的數(shù)據(jù)分布表現(xiàn),典型地,用帶有“僅從工序中的數(shù)據(jù)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工序控制與工序能力

1. 工序控制29BPTLConfi工序控制與工序能力2. 工序能力“好處”是工序能力可被度量比較“工序的現(xiàn)狀”與“客戶的要求

”,均須以規(guī)格為依據(jù)度量一個穩(wěn)定的工序狀態(tài)(受控制)在多大程度上能滿足客戶的規(guī)格.30BPTLConfidential工序控制與工序能力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?qū)е碌睦鄯e效果只有微小的機會導(dǎo)致變化的運作工序稱為“統(tǒng)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(diào)機 b)操作者錯誤 c)有缺陷的原材料一個工序如果出現(xiàn)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(guī)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(guī)格極限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(guī)格極限a)b)c)34BPTLConfiden三種極限類型規(guī)格極限(LSLandUSL)

createdbydesignengineeringinresponsetocustomerrequirementstospecifythetoleranceforaproduct’scharacteristic工序極限(LPLandUPL)measuresthevariationofaprocessthenatural6limitsofthemeasuredcharacteristic控制極限(LCLandUCL)measuresthevariationofasamplestatistic(mean,variance,proportion,etc)35BPTLConfidential三種極限類型規(guī)格極限(LSLandUSL)工序能力指數(shù)工序能力的兩種度量:工序潛力Cp

工序表現(xiàn)Cpu

Cpl

Cpk

36BPTLConfidential工序能力指數(shù)工序能力的兩種度量:36BPTLConfide工序潛力

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

Cp指標(biāo)顯示實際工差(6)是否超出規(guī)格.公工序潛力傳統(tǒng)上,Cp有1.0時顯示工序能力被判為“有能力考核成績”.若數(shù)據(jù)集中于工程工差內(nèi),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(tǒng)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(xiàn)TheCpkindexrelatesthescaleddistancebetweentheprocessmeanandthenearestspecificationlimit.41BPTLConfidential工序表現(xiàn)TheCpkindexrelatesthe工序表現(xiàn) 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(xiàn) Cpk 不良率42BPTLConfi工序表現(xiàn)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(xiàn)a)Cp=2b)Cp=2c)Cp=243工序潛力與工序表現(xiàn)(a)PoorProcessPotential (b)PoorProcessPerformanceLSLUSLLSLUSLExperimentalDesigntoreducevariationExperimentalDesigntocentermeantoreducevariation44BPTLConfidential工序潛力與工序表現(xiàn)(a)PoorProcessPote工序潛力與工序表現(xiàn)a)Cp=2Cpk=2b)Cp=2Cpk=1c)Cp=2Cpk<145BPTLConfidential工序潛力與工序表現(xiàn)a)Cp=2b)Cp=2c)Cp工序穩(wěn)定性Aprocessisstableifthedistributionofmeasurementsmadeonthegivenfeatureisconsistentovertime.TimeStableProcessTimeUnstableProcessucllclucllcl46BPTLConfidential工序穩(wěn)定性Aprocessisstableifth短期工序能力與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短期工序能力與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

短期工序能力與長期工序能力48BPTLConfidential Within Overall短期工序能力與長期工實戰(zhàn)演練Thelengthofacamshaftforanautomobileengineisspecifiedat600±2mm.Controlofthelengthofthecamshaftiscriticaltoavoidscrap/rework.Thecamshaftisprovidedbyexternalsuppliers.Assesstheprocesscapabilityforthissupplier.ThedataisavailableinCamshaft.MTW.Dataarecollectedinsubgroupsof5each.49BPTLConfidential實戰(zhàn)演練ThelengthofacamshaftfExample4Minitab:StatQualityToolsCapabilityAnalysis(Normal)50BPTLConfidentialExample4Minitab:50BPTLConfidExample451BPTLConfidentialExample451BPTLConfidentialExample5Histogramofthecamshaftlengthsuggestsmixedpopulations.Furtherinvestigationrevealedthattherearetwosuppliersforthecamshaft.Datawerenowcollectedoncamshaftsfromeachsourcewithoutcombiningboth.Subgroupsizeis5foreachsupplier.Arethetwosupplierssimilarinperformance?Ifnot,whatareyourrecommendations?52BPTLConfidentialExample5HistogramofthecamsExample5MiniTab:StatQualityToolsCapabilitySixpack(Normal)53BPTLConfidentialExample5MiniTab:53BPTLConfidExample554BPTLConfidentialExample554BPTLConfidentialExample555BPTLConfidentialExample555BPTLConfidential用Box-Cox轉(zhuǎn)化后的工序能力分析Whentheprocessdataarenotnormal,theCpkorPpkindicesarenotaccurateorreliable,becausetheseindicesarecomputedonthebasisthatthedataarenormallydistributed.Dppmvaluesassociatedwiththeindiceswillnotbeneartotheactualperformancewhenthenormalcurvedoesnotmodeltheactualdatawell.56BPTLConfidential用Box-Cox轉(zhuǎn)化后的工序能力分析WhentheprIftheprocessdataaresomewhatbell-shapedbutskewed,Box-Coxtransformationcanbeusedtomakethedatanormalbeforeweassesstheprocesscapability.RemembertotransformthespecificationlimitstoobeforewecomputeCpkorPpk!用Box-Cox轉(zhuǎn)化后的工序能力分析57BPTLConfidentialIftheprocessdataaresomewhMinitab:StatQualityToolsCapabilityAnalysis(Normal)用Box-Cox轉(zhuǎn)化后的工序能力分析58BPTLConfidentialMinitab:用Box-Cox轉(zhuǎn)化后的工序能力分析58BExample6OpenthefilenamedDimension.MTWintheDay-2folderagain.Computetheprocesscapabilitywiththespecificationlimits:LSL:0.1 USL:10Arethedatanormallydistributed?ComputetheprocesscapabilityagainwithBox-Coxtransformation.用Box-Cox轉(zhuǎn)化后的工序能力分析59BPTLConfidentialExample6OpenthefilenamedDCpkof0.41isreportedintheSSATpackage.Thisvalueisnotreliableoraccurateifthedataarenotnormal.DataisnotnormalExample6用Box-Cox轉(zhuǎn)化后的工序能力分析60BPTLConfidentialCpkof0.41isreportedintheExample6Cpkhasincreasedfrom0.41to0.81用Box-Cox轉(zhuǎn)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=?(dpmo)?(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(shù)據(jù)分布68BPTLConfidential

NormalExponentialWeibullLognormaltc2fContinuousDistributionsSamplingDistributions數(shù)據(jù)分布69BPTLConfidential

Themostwidelyusedmodelforthedistributionofcontinuousrandomvariable.Arisesinthestudyofnumerousphysicalphenomena,suchasthevelocityofmolecules.正態(tài)分布PlotisknownasProbabilityDensityFunctionofX70BPTLConfidentialThemostwidelyusedmodelforManynaturalphenomenaandman-madeprocessesareobservedtohavenormaldistributions,orcanbecloselyrepresentedasnormallydistributed.Forexample,thelengthofamachinedpartisobservedtovaryaboutitsmeandueto:temperaturedrift,humiditychange,vibrations,cuttinganglevariations,cuttingtoolwear,bearingwear,rotationalspeedvariations,fixturingvariations,rawmaterialchangesandcontaminationlevelchangesIfthesesourcesofvariationaresmall,independentandequallylikelytobepositiveornegative,thelengthwillcloselyapproximateanormaldistribution.正態(tài)分布71BPTLConfidentialManynaturalphenomenaandmanFirstintroducedbyFrenchmathematicianAbrahamDeMoivrein1733.Madefamousin1809byGermanmathematicianK.F.Gausswhenhealsodevelopedanormaldistributionindependentlyanduseditinhisstudyofastronomy.Asaresult,itisalsoknownastheGaussiandistribution.Duringmidtolatenineteenthcentury,manystatisticiansbelievedthatitwas“normal”formostwell-behaveddatatofollowthiscurve.正態(tài)分布-歷程表KarlFriedrichGauss72BPTLConfidentialFirstintroducedbyFrenchmat正態(tài)分布易于理解,具有特性,統(tǒng)計學(xué)提供了許多基于正態(tài)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(tài)分布去近似模擬其它分布(如可能)或轉(zhuǎn)化數(shù)據(jù)以“使”它遵從正態(tài)分布.它是分析過程能力的首選分布形式.正態(tài)分布73BPTLConfidential正態(tài)分布易于理解,具有特性,統(tǒng)計學(xué)提供了許多基于正態(tài)分布Anormaldistributioncanbecompletelydescribedbyknowingonlythe:Mean(m)Variance(s2)正態(tài)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(tài)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(tài)分布的一些特性76BPTLConfidentialThemean,medianandmodeallTheareaundersectionsofthecurvecanbeusedtoestimatethecumulativeprobabilityofacertain“event”occurring:μPointofInflection1s+￥-￥68.27%95.45%99.73%m+/-3sisoftenreferredtoasthewidthofanormaldistribution3正態(tài)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(tài)分布的一些特性78BPTLConfidentialLet’scomputethecumulativepMiniTab:CalceProbabilityDistributionseNormal...EntermvalueEntersvalueEnterxvalue正態(tài)分布的一些特性79BPTLConfidentialMiniTab:EnterEnterEnter正態(tài)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(wù)上的生存競爭有賴于我們多大程度上讓我們的客戶滿意.客戶滿意才能體現(xiàn)品質(zhì),價格,和貨期的意義.品質(zhì),成本,準(zhǔn)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(xué)習(xí)目標(biāo)工序控制與工序能力工序能力:規(guī)格,工藝和控制的界限工序潛力與工序表現(xiàn)短期與長期工序能力“6σ”品質(zhì)94BPTLConfidential學(xué)習(xí)目標(biāo)工序控制與工序能力28BPTL工序控制與工序能力

1. 工序控制意即工序運作處于統(tǒng)計控制狀態(tài),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(shù)據(jù)來判定工序是處于受控狀態(tài).過程的跟蹤表現(xiàn)來証實它是否建立了長時間穩(wěn)定的數(shù)據(jù)分布表現(xiàn),典型地,用帶有“僅從工序中的數(shù)據(jù)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工序控制與工序能力

1. 工序控制29BPTLConfi工序控制與工序能力2. 工序能力“好處”是工序能力可被度量比較“工序的現(xiàn)狀”與“客戶的要求

”,均須以規(guī)格為依據(jù)度量一個穩(wěn)定的工序狀態(tài)(受控制)在多大程度上能滿足客戶的規(guī)格.96BPTLConfidential工序控制與工序能力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?qū)е碌睦鄯e效果只有微小的機會導(dǎo)致變化的運作工序稱為“統(tǒng)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(diào)機 b)操作者錯誤 c)有缺陷的原材料一個工序如果出現(xiàn)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(guī)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(guī)格極限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(guī)格極限a)b)c)34BPTLConfiden三種極限類型規(guī)格極限(LSLandUSL)

createdbydesignengineeringinresponsetocustomerrequirementstospecifythetoleranceforaproduct’scharacteristic工序極限(LPLandUPL)measuresthevariationofaprocessthenatural6limitsofthemeasuredcharacteristic控制極限(LCLandUCL)measuresthevariationofasamplestatistic(mean,variance,proportion,etc)101BPTLConfidential三種極限類型規(guī)格極限(LSLandUSL)工序能力指數(shù)工序能力的兩種度量:工序潛力Cp

工序表現(xiàn)Cpu

Cpl

Cpk

102BPTLConfidential工序能力指數(shù)工序能力的兩種度量:36BPTLConfide工序潛力

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

Cp指標(biāo)顯示實際工差(6)是否超出規(guī)格.公工序潛力傳統(tǒng)上,Cp有1.0時顯示工序能力被判為“有能力考核成績”.若數(shù)據(jù)集中于工程工差內(nèi),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(tǒng)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(xiàn)TheCpkindexrelatesthescaleddistancebetweentheprocessmeanandthenearestspecificationlimit.107BPTLConfidential工序表現(xiàn)TheCpkindexrelatesthe工序表現(xiàn) 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(xiàn) Cpk 不良率42BPTLConfi工序表現(xiàn)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(xiàn)a)Cp=2b)Cp=2c)Cp=243工序潛力與工序表現(xiàn)(a)PoorProcessPotential (b)PoorProcessPerformanceLSLUSLLSLUSLExperimentalDesigntoreducevariationExperimentalDesigntocentermeantoreducevariation110BPTLConfidential工序潛力與工序表現(xiàn)(a)PoorProcessPote工序潛力與工序表現(xiàn)a)Cp=2Cpk=2b)Cp=2Cpk=1c)Cp=2Cpk<1111BPTLConfidential工序潛力與工序表現(xiàn)a)Cp=2b)Cp=2c)Cp工序穩(wěn)定性Aprocessisstableifthedistributionofmeasurementsmadeonthegivenfeatureisconsistentovertime.TimeStableProcessTimeUnstableProcessucllclucllcl112BPTLConfidential工序穩(wěn)定性Aprocessisstableifth短期工序能力與長期工序能力短期工序能力(previouslycalledshort-termcapability)showstheinherentvariabilityofamachine/processoperatingwithinabriefperiodoftime.長期工序能力(previouslycalledlo