制程能力控制过程-英文版.pptx
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制程能力控制过程-英文版.pptx
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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,e.g.millimetres,volts,amps,decibelandseconds.,Inthistrainingwedealwithvariablesonly,TheSourcesofProcess/SystemVariation,Methods,Operators,CustomerSatisfaction,Material,Environment,Equipment,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,Thispartiswithinspec.Thetoolwouldbeapprovedifonlythispartwasmeasured,Thesepartsareoutofspecandcouldbeapprovedifonlyonegoodpartwasmeasured,Aprocesscapabilitystudywouldrevealthatthetoolshouldnotbeaccepted,Whenadimensionneedstobekeptproperlywithinspec,wemuststudytheprocesscapability.butstillthisisnoguaranteefortheactualperformanceoftheprocessasitisonlyaninitialcapabilitystudy,TheNokiaProcessVerificationProcess,10parts/cavitymeasuredformeasurementreport,Capabilitystudy:
Requirement:
CpandCpk1.67byE3.Quantitiestobeagreedwithsupplier.Minimum5partspr1/2hourin10hoursmeasuredforeachcavity=100parts.Canvarydependingontoolcapacity,e.g.stampedparts(seeDMY00019-EN),Section2.Population,SampleandNormalDistribution,TheBellShaped(Normal)Distribution,Symmetricalshapewithapeakinthemiddleoftherangeofthedata.Indicatesthattheinputvariables(Xs)totheprocessarerandomlyinfluenced.,“PopulationParameters”=Populationmean=Populationstandarddeviation,PopulationversusSample,PopulationAnentiregroupofobjectsthathavebeenmadeorwillbemadecontainingacharacteristicofinterest,SampleThegroupofobjectsactuallymeasuredinastatisticalstudyAsampleisusuallyasubsetofthepopulationofinterest,Population,Sample,“SampleStatistics”x=Samplemeans=Samplestandarddeviation,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,Typical:
N=20&n=5,Example:
WhatMeasurementsCanBeUsedtoDescribeProcessvariation?
TheDifferenceBetweenSSTandsLT!
mean,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,Meanvalue=NominalvalueorTarget,RequirementforCpandCpkis1.67min.1.67isaratioof=5/3or10/6.,6*standarddeviation,10*standarddeviation,2*standarddeviation,2*standarddeviation,Cpk1.67theprocessNOTCAPABLE,AcceptabilityofCpkIndex,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
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