MSA-7.ppt

ProcessCapability(Cp/Cpk/Pp/Ppk)GlobalTrainingMaterial,Creator:GlobalMechanicsProcessManagerFunction:MechanicsApprover:GaryBradley/GlobalProcessTeamDocumentID:DMT00018-ENVersion/Status:V.1.0/ApprovedLocation:Notes:NMPDOCMANR4PCPPCProcessLibraryDocManChangeHistory:IssueDateHandledByComments1.021stDec01JimChristy&SrenLundsfrydApprovedforGlobalUseNOTEAllcommentsandimprovementsshouldbeaddressedtothecreatorofthisdocument.,Contents,SectionHeading/DescriptionPage1Variation,TolerancesandDimensionalControl42Population,SampleandNormalDistribution153CpandCpkConcept284UseoftheNMPDataCollectionSpreadsheet445ConfidenceofCpk52,ProcessCapability-EvaluatingManufacturingVariation,AcknowledgementsBennyMatthiassen(NMPCMT,Copenhagen,Denmark)FrankAdler(NMPAlliance,Dallas,USA)JoniLaakso(NMPR&D,Salo,Finland)JimChristy(NMPSRC,Southwood,UK),Section1Variation,TolerancesandDimensionalControl,TwoTypesofProductCharacteristics,Variable:Acharacteristicmeasuredinphysicalunits,limetres,volts,amps,decibelandseconds.,Inthistrainingwedealwithvariablesonly,TheSourcesofProcess/SystemVariation,Process,TwoTypesofProcesses,Allprocesseshave:Natural(random)variability=duetocommoncauses,StableProcess:Aprocessinwhichvariationinoutcomesarisesonlyfromcommoncauses,UnstableProcess:Aprocessinwhichvariationisaresultofbothcommonandspecialcauses,Unnaturalvariability=duetospecialcauses,Shewhart(1931),TheTwoCausesofVariation,CommonCauses:Causesthatareimplementedintheprocessduetothedesignoftheprocess,andaffectalloutcomesoftheprocessIdentifyingthesetypesofcausesrequiresmethodssuchasDesignofExperiment(DOE),etc.SpecialCauses:Causesthatarenotpresentintheprocessallthetimeanddonotaffectalloutcomes,butarisebecauseofspecificcircumstancesSpecialcausescanbeidentifiedusingStatisticalProcessControl(SPC),Defect,USL,LSL,nominalvalue,Tolerances,LSL(lowerspecificationlimit)10,7,USL(upperspecificationlimit)10,9,Acceptablepart,RejectedPart,RejectedProduct,Nominal10,80,1,RejectedPart,Atoleranceisaallowedmaximumvariationofadimension.,MeasurementReport,Inmostcaseswemeasureonlyonepartpercavityformeasurementreport,ExampleofCapabilityAnalysisData,Forsomecriticaldimensionsweneedtomeasuremorethan1partForcapabilitydataweusuallymeasure5pcs2times/hour=100pcs(butsamplingplanneedstobemadeonthebasisofproductionquantity,rundurationandcycletime),ProcessCapability-Whatisit?,ProcessCapabilityisameasureoftheinherentcapabilityofamanufacturingprocesstobeabletoconsistentlyproducecomponentsthatmeettherequireddesignspecifications,ProcessCapabilityisdesignatedbyCpandCpk,ProcessPerformanceisameasureoftheperformanceofaprocesstobeabletoconsistentlyproducecomponentsthatmeettherequireddesignspecifications.ProcessPerformanceincludesspecialcausesofvariationnotpresentinProcessCapability,ProcessPerformanceisdesignatedPpandPpk,WhyMakeProcessCapabilityStudies,Aprocesscapabilitystudywouldrevealthatthetoolshouldnotbeaccepted,Whenadimensionneedstobekeptproperlywithinspec,wemuststudytheprocesscapability.butstillthisisnoguaranteefortheactualperformanceoftheprocessasitisonlyaninitialcapabilitystudy,TheNokiaProcessVerificationProcess,Section2.Population,SampleandNormalDistribution,TheBellShaped(Normal)Distribution,Symmetricalshapewithapeakinthemiddleoftherangeofthedata.Indicatesthattheinputvariables(Xs)totheprocessarerandomlyinfluenced.,“PopulationParameters”=Populationmean=Populationstandarddeviation,PopulationversusSample,PopulationAnentiregroupofobjectsthathavebeenmadeorwillbemadecontainingacharacteristicofinterest,SampleThegroupofobjectsactuallymeasuredinastatisticalstudyAsampleisusuallyasubsetofthepopulationofinterest,TheNormalDistribution,WhatMeasurementsCanBeUsedtoDescribeaProcessorSystem?,mean(average)ordescribesthelocationofthedistribution,(m),ameasureofcentraltendency,isthemeanoraverageofallvaluesinthepopulation.Whenonlyasampleofthepopulationisbeingdescribed,meanismoreproperlydenotedas(x-bar):,Themostsimplemeasureofvariabilityistherange.Therangeofasampleisdefinedbyasthedifferencebetweenthelargestandthesmallestobservationfromsamplesinasub-group,e.g.5consecutivepartsfromthemanufacturingprocess.,WhatMeasurementsCanBeUsedtoDescribeProcessvariation?,sST-oftennotatedasorsigma,isanothermeasureofdispersionorvariabilityandstandsfor“short-termstandarddeviation”,whichmeasuresthevariabilityofaprocessorsystemusing“rational”sub-grouping.,whereistherangeofsubgroupj,Nthenumberofsubgroups,andd2*dependsonthenumberNofsubgroupsandthesizenofasubgroup(seenextslide),WhatMeasurementsCanBeUsedtoDescribeProcessvariation?,d2*valuesforSST,Example:,WhatMeasurementsCanBeUsedtoDescribeProcessvariation?,TheDifferenceBetweenSSTandsLT!,ThedifferencebetweenthestandarddeviationssLTandsSTgivesanindicationofhowmuchbetteronecandowhenusingappropriateproductioncontrol,likeStatisticalProcessControl(SPC).,Short-termstandarddeviation:,Long-termstandarddeviation:,ThedifferencebetweensSTandsLT,ThedifferencebetweensSTandsLT,ThedifferencebetweensLTandsSTisonlyinthewaythatthestandarddeviationiscalculatedsLTisalwaysthesameorlargerthansSTIfsLTequalssST,thentheprocesscontroloverthelonger-termisthesameastheshort-term,andtheprocesswouldnotbenefitfromSPCIfsLTislargerthansST,thentheprocesshaslostcontroloverthelonger-term,andtheprocesswouldbenefitfromSPCThereliabilityofsLTisimprovedifthedataistakenoveralongerperiodoftime.AlternativelysLTcanbecalculatedonseveraloccasionsseparatedbytimeandtheresultscomparedtoseewhethersLTisstable,Exercise1:SampleDistributions,1.InExcelfileDataexercise1.xlsyoufind100measurementsbeingtheresultofacapabilitystudy.Thespecificationforthedimensionis15,16,012.Howwelldoesthesamplepopulationfitthespecification,e.g.shouldweexpectanypartsoutsidespec?3.Mentionpossibleconsequencesofhavingapartoutsidespec.4.Mentionpossiblecausesofvariationforparts.5.Calculatethesamplemeanandsamplestandarddeviationforthe100measurements.UsetheaverageandstdevfunctionsExcel.,Section3.CpandCpkConcept,DefiningCpandPp,Thetoleranceareadividedbythetotalprocessvariation,irrespectiveofprocesscentring.,DefiningCpkandPpk,CpkandPpkIndexesaccountalsoforprocesscentring.,WhatistheDifferenceBetweenCpandCpk?,TheCpindexonlyaccountsforprocessvariabilityTheCpkIndexaccountsforprocessvariabilityandcenteringoftheprocessmeantothedesignnominalTherefore,CpCpkNOTE:SameappliesalsoforPpandPpk,WhatDoTheseIndexesTellUs?,SimplenumericalvaluestodescribethequalityoftheprocessThehigherthenumberthebetter,RequirementforCpandCpkis1.67min.RecommendationforPpandPpkis1.33min.,Thisleavesussomespaceforthevariation,i.e.asafetymargin,AreweabletoimproveourprocessbyusingSPC?,Ifindexislow,followingthingsshouldbegivenathought:,IstheproductdesignOK?,Aretolerancelimitssetcorrectly?,Tootight?,Istheprocesscapableofproducinggoodqualityproducts?Processvariation?DOErequired?,Isthemeasuringsystemcapable?(SeeGageR&R),Cpk-Witha2-sigmasafetymargin,RequirementforCpandCpkis1.67min.1.67isaratioof=5/3or10/6.,2*standarddeviation,2*standarddeviation,Cpk=1.67theprocessisCAPABLE,Cpk=2.0theprocesshasreachedSixSigmalevel,WhatDoTheseIndexesTellUs?,IfCp=Cpk,IfPp=Ppk,IfCpkCp,IfPpkPp,IfCp=Pp,IfCpk=Ppk,IfPpCp,IfPpkCpk,thenprocessisaffectedbyspecialcauses.InvestigateX-bar/R-chartforout-of-controlconditions.SPCmaybeeffective,thenprocessisnotaffectedbyspecialcausesduringthestudyrun.SPCwouldnotbeeffectiveinthiscase,thenprocessperfectlycentred,thenprocessnotcentred(checkprocessmeanagainstdesignnominal),CpandCpkIndicesandDefects(bothtailsofthenormaldistribution),Pp=Ppk=1,3363ppmdefects=0,006%,Cp=Cpk=1,670,6ppmdefects=0,00006%,Note:PpmrejectratescalculatedfromCp&Cpkarebasedontheshorttermvariationwhichmaynotrepresentthelongtermrejectrate,TheEffectsofCpkandCponFFR,Exercise2:CpandCpk,CalculateCpandCpkforthe100measurementsinthefileDataexercise1.xlsDeterminetheapproximateCpandCpkforthe4samplepopulationsonthefollowingpageShouldactionsbemadetoimprovetheseprocesses.Ifyes,which?,EstimateCpandCpk?,Thewidthofthenormaldistributionsshowninclude3*s,EstimateCpandCpk?-A),LSL,USL,A),Meanandnominal,USL-LSL,6*s,USL-Mean,Mean-LSL,3*s,EstimateCpandCpk?-B),LSL,USL,B),Nominal,Mean,USL-LSL,6*s,USL-Mean,Mean-LSL,3*s,EstimateCpandCpk?-C),LSL,USL,C),Nominal,Mean,USL-LSL,6*s,USL-Mean,Mean-LSL,3*s,EstimateCpandCpk?-D,USL,LSL,D),Nominal,Mean,USL-LSL,6*s,USL-Mean,Mean-LSL,3*s,Section4.UseoftheNMPDataCollectionSpreadsheet,ExampleofhowtoCollectData,1.Runinandstabiliseprocess2.Notethemainparametersforreference3.Whentheprocessisstablerunthetoolfor10hours3.Take5partsoutfromeachcavityeveryhalfhourandmarkthemwithtime,dateandcavity.Total20setsof5partsfromeachcavitymustbemade,oraccordingtoagreement.,4.Afterthelastsamplelotnotethemainprocessparametersforreference5.Measureandrecordthemainfunctionalcharacteristics(whitediamonds)6.FilldataintotheNMPdatacollectionspreadsheet7.Analyse!,SeeDMY00019-ENClassificationandMarkingofFunctionalCharacteristics,DataCollectionSheet(DMM00024-EN-5.0),DataCollectionSheet(DMM00024-EN-5.0),GraphicalPresentation:Histogram,Whatkindofdistribution?LocationversustoleranceareaWidth(deviation)Example:Cp2.59Pp1.86Cpk0.88Ppk0.63,GraphicalPresentation:X-barandR-Chart,X-BarChart,R-Chart,GraphicalPresentation-TimeSeriesPlot,Exercise3:CpkDataSpreadsh