TUV德国莱茵六西格码黑带培训资料MSA.ppt

Chapter3.2MeasurementSystemsAnalysis测量系统分析,测量是科学的基础,“Ioftensaythatwhenyoumeasurewhatyouarespeakingaboutandexpressitinnumbers,youknowsomethingaboutit.”LORDKELVIN,TheScienceofMeasurement,EffectsofMeasurementError,Averages,Variability,MeasurementSystemBias,MeasurementSystemVariability,Accuracy,Precision,s2total=s2product+s2meassystem,测量误差,平均值,变差,测量系统的偏差,测量系统的变差,准确度,精确度,s2total=s2产品+s2测量系统,SourcesofMeasurementVariation,测量误差的原因,M,e,a,s,u,r,e,m,e,n,t,V,a,r,i,a,t,i,o,n,H,u,m,i,d,i,t,y,C,l,e,a,n,l,i,n,e,s,s,V,i,b,r,a,t,i,o,n,L,i,n,e,V,o,l,t,a,g,e,V,a,r,i,a,t,ion,T,e,m,p,e,r,a,t,u,r,e,F,l,u,c,t,u,a,tion,O,p,e,r,a,t,o,r,T,e,c,h,n,i,q,u,e,S,t,a,n,d,a,r,d,P,r,o,c,e,d,u,r,e,s,S,u,f,f,i,c,i,e,n,t,W,o,r,k,T,i,m,e,M,a,i,n,t,e,n,a,n,c,e,S,t,a,n,d,a,r,d,C,a,l,i,b,r,a,t,i,o,n,F,r,e,q,u,e,n,cy,O,p,e,r,a,t,o,r,T,r,a,i,n,i,n,g,E,a,s,e,o,f,D,a,t,a,E,n,t,r,y,电性能不稳定,磨损,机械不稳定性,量具,环境,测量方法,计算不稳定,取得数据的难易,操作员培训,校准频率,量具维护标准,足够的工作时间,标准操作规程,操作员技术,湿度,清洁程度,震动,线电压波动,温度波动,看到的不一定真实,PossibleSourcesofProcessVariation,Long-term,ProcessVariation,Short-term,ProcessVariation,Variation,w/isample,ActualProcessVariation,Stability,Linearity,Repeatability,Accuracy,Variationdue,togage,Variationdue,tooperators,MeasurementVariation,ObservedProcessVariation,Wewilllookat“repeatability”and“reproducibility”asthesearetheprimarycontributorstomeasurementerror.,Reproducibility,过程变差剖析,长期,过程变差,短期,抽样产生的变差,实际过程变差,稳定性,线性,重复性,准确度,量具变差,操作员造成的变差,测量误差,过程变差观测值,“重复性”和“再现性”是测量误差的主要来源,再现性,过程变差,Accuracy,AccuracyDoestheaverageofthemeasurementsdeviatefromthetruevalue?Truevalue:TheoreticallycorrectvalueNISTstandardsBiasDistancebetweenaveragevalueofallmeasurementsandtruevalueAmountgageisconsistentlyofftargetSystematicerrororoffset,准确度(Accuracy),准确度(Accuracy)测量的平均值是否与真值吻合?真值(TrueValue):理论上正确的值国际度量衡标准偏倚（Bias)测量值的均值与真值的距离测量系统持续地偏离目标系统错误,BIASIsthedifferencebetweentheobservedaverageofthemeasurementandthereferencevalue.Thereference-valueisthevaluethatservesasanagreed-uponreference.Thereferencevaluecanbedeterminedbyaveragingseveralmeasurementswithahigherlevel(e.g.,metrologylab)ofmeasuringequipment.,ObservedAverageValue,ReferenceValue,BIASDefinition,BIAS测量结果的平均值与参考值的差异.参考值（reference-value）是一个预先认定的参考标准.该标准可用更高一级测量系统测量的平均值来确定(例如：高一级计量室),观测平均值,参考值,偏倚BIAS,X1=0.75mmX6=0.8mmX2=0.75mmX7=0.75mmX3=0.8mmX8=0.75mmX4=0.8mmX9=0.75mmX5=0.65mmX10=0.7mm,OnePartMeasuredTenTimesbyOneAppraiser,WhatelsedoyouneedtodetermineBIAS?,ThereferenceValuedeterminedbythelayoutinspectionequipment(ensurethisequipmentwentthroughaGageR&R)is0.80mm.Theprocessvariationforthepartis0.70mm.,=0.75,Bias=0.75-0.8=-0.05,%Bias=1000.05/0.70=7.1%,Thismeans7.1%oftheprocessvariationisBIAS,BIASEXAMPLE:,X1=0.75mmX6=0.8mmX2=0.75mmX7=0.75mmX3=0.8mmX8=0.75mmX4=0.8mmX9=0.75mmX5=0.65mmX10=0.7mm,同一操作者对同一工件测量10次,如果参考标准是0.80mm.过程变差为0.70mm,=0.75,Bias=0.75-0.8=-0.05,%Bias=1000.05/0.70=7.1%,表明7.1%的过程变差是偏倚BIAS,偏倚BIAS实例:,Precision,TotalvariationinthemeasurementsystemMeasureofnaturalvariationofrepeatedmeasurementsTerms:RandomError,Spread,Test/RetesterrorRepeatabilityandReproducibility,s,s,s,MS,G,O,2,2,2,=,+,测量系统总变差通过重复测量的方法测量到的过程自然变差代表名词：重复性（Repeatability）和再现性（Reproducibility）,s,s,s,MS,G,O,2,2,2,=,+,精确度（Precision),Precision:Repeatability,TheinherentvariabilityofthemeasurementsystemVariationinmeasurementsobtainedwithagagewhenusedseveraltimesbyoneoperatorwhilemeasuringacharacteristicononepart.EstimatedbythepooledstandarddeviationofthedistributionofrepeatedmeasurementsRepeatabilityislessthanthetotalvariationofthemeasurementsystem,测量系统内在的变异性基于重复测量的数据，用分组后组内的标准偏差来估算小于测量系统的总变差,精确度：重复性,Precision:Reproducibility,OperatorvariabilityofthemeasurementsystemVariationintheaverageofthemeasurementsmadebydifferentoperatorsusingthesamegagewhenmeasuringacharacteristicononepartEstimatedbythestandarddeviationofthedifferenceinaverages,basedonmeasurementstakenbydifferentoperatorsMustbeadjustedforgagevariationReproducibilityislessthanthetotalvariationofthemeasurementsystem,精确度：再现性,测量系统中操作员产生的变异基于不同操作者的测量数据，按操作员分组，通过组平均值的差来估。应扣除量具的因素（组内变差）比测量系统总变差小,Linearity,Differenceintheaccuracyvaluesofagagethroughtheexpectedoperatingrangeofthegage,GoodLinearity,BadLinearity,线性（Linearity）,量具在不同测量范围的准确度和精确度的变化，当测量范围较宽时尤为要关注,好的线性,差的线性,Stability,ThedistributionofmeasurementsremainsconstantandpredictableovertimeforbothmeanandstandarddeviationTotalvariationinthemeasurementsobtainedwithagage,onthesamemasterormasterparts,whenmeasuringasinglecharacteristicoveranextendedtimeperiod.Evaluatedusingatrendchartormultiplemeasurementanalysisstudiesovertime,Time-1,Time-2,time,Magnitude,Stability,在一段时间内，测量结果的分布无论是均值还是标准偏差都保持不变和可预测的通过较长时间内，用被监视的量具对相同的标准或标准件的同一特性进行测量的总变异来监视可用时间走势图进行分析,稳定性（Stability）,量值,Discrimination,Thetechnologicalabilityofthemeasurementsystemtoadequatelydifferentiatebetweenvaluesofameasuredparameter.,测量系统的分辨率（discrimination）,要求不低于过程变差或允许偏差（tolerance）的十分之一零件之间的差异必须大于最小测量刻度极差控制图可显示分辨率是否足够看控制限内有多少个数据阶级不同数据等级的计算为零件的标准偏差/总的量具偏差*1.41.,GenerallytwoorthreeoperatorsGenerally10unitstomeasureEachunitismeasured2-3timesbyeachoperator,GageR&Rstudy,Determineifreproducibilityisanissue.Ifitis,selectthenumberofoperatorstoparticipate.Operatorsselectedshouldnormallyusethemeasurementsystem.Selectsamplesthatrepresenttheentireoperatingrange.Gagemusthavegraduationsthatallowatleastone-tenthoftheexpectedprocessvariation.Insuredefinedgagingproceduresarefollowed.Measurementsshouldbemadeinrandomorder.Studymustbeobservedbysomeonewhorecognizestheimportanceofconductingareliablestudy.,计量型数据的GR&R研究,均值-极差（X-R）法是确定测量系统的重复性和再现性的数学方法，步骤如下：1选择三个测量人（A,B,C）和10个测量样品。测量人应有代表性，代表经常从事此项测量工作的QC人员或生产线人员10个样品应在过程中随机抽取，可代表整个过程的变差，否则会严重影响研究结果。2校准量具3测量，让三个测量人对10个样品的某项特性进行测试，每个样品每人测量三次，将数据填入表中。试验时遵循以下原则：盲测原则1：对10个样品编号，每个人测完第一轮后，由其他人对这10个样品进行随机的重新编号后再测，避免主观偏向。盲测原则2：三个人之间都互相不知道其他人的测量结果。4计算,计算A测的所有样品的总平均值XA。,同样方法计算RB,XB,RC,Xc,对每个样品由三个人所测得的9个测试值求平均值，计算这些均值的极差Rp,计算A对每个样品三次测试结果的极差，然后计算10个样品的极差的均值RA,测量系统分析,R=(RA+RB+RC)/3XDIFF=MaxXA,XB,XC-MinXA,XB,XC重复性-设备变差EV=RK1再现性-测验人变差AV=(XDIFFK2)2-(EV2/nr)过程变差PV=RPK3R&R=(EV2+AV2)总变差TV=(R&R2+PV2)%EV=EV/TV%AV=AV/TV%R&R=R&R/TV%PV=PV/TVP/T=R&R/Tolerance,n=样品个数r=每个人对每个样品的试验次数,r,K1,23,4.453.05,K2,23,3.652.70,测试人数,n,K3,78910,1.821.741.671.62,K1=5.15/d2,*AV计算中，如根号下出现负值，AV取值0,EV=EquipmentVariation(Repeatability)仪器变差(重复性)AV=AppraiserVariation(Reproducibility)测量人变差(再现性)R&R=Repeatability&Reproducibility重复性与再现性PV=PartVariation零件变差TV=TotalVariationofR&RandPV总变差K1-Trial,K2-Operator,&K3-PartConstants,GR&R研究中的名词,卡尺的R&R研究Excel运算,R&R对过程能力计算的影响,70%,60%,50%,40%,30%,10%,R&REffectonCapability,Guidelines,%R&RResultsStatQualityToolsGageStudyGageR&RStudy(Crossed)在MethodofAnalysis中选择XbarandR,Minitab计算GR&R,图解数据,%ContributionSourceVarComp(ofVarComp)TotalGageR&R0.0004594.53Repeatability0.0002312.28Reproducibility0.0002282.25Operator0.0001171.16Operator*PartNo0.0001111.09Part-To-Part0.00967095.47TotalVariation0.010129100.00StdDevStudyVar%StudyVar%ToleranceSource(SD)(5.15*SD)(%SV)(SV/Toler)TotalGageR&R0.0214300.11036621.2922.07Repeatability0.0152020.07829215.1115.66Reproducibility0.0151050.07778915.0115.56Operator0.0108340.05579310.7611.16Operator*PartNo0.0105250.05420510.4610.84Part-To-Part0.0983360.50643097.71101.29TotalVariation0.1006440.518317100.00103.66NumberofDistinctCategories=6,Minitab计算GR&R-ANOVA法,在MethodofAnalysis中选择ANOVA,MeasurementVariationVs.Tolerance,PrecisiontoToleranceRatioAddresseswhatpercentoftheToleranceistakenupbymeasurementerror.Bestcase:10%Acceptable:30%IncludesbothrepeatabilityandreproducibilityOperatorxUnitxTrialexperimentP/TRatiosarerequiredbycertaincustomers,Note:5.15standarddeviationsaccountsfor99%ofMSvariation.Theuseof5.15isanindustrystandard.,MeasurementVariationVs.Process(Analytical),PercentRepeatability&Reproducibility(%R&R)AddresseswhatpercentoftheTotalVariationistakenupbymeasurementerror.Bestcase:10%Acceptable:30%IncludesbothrepeatabilityandreproducibilityOperatorxUnitxTrialexperimentAgain,thestabilityintherepeatedmeasurementsaswellasthedegreeofdiscriminationcouldaffectthevalidityofthecalculation.%R&Risrequiredbycertaincustomers,P/T与%R&R,将测量系统的变差与产品容差比较是最常用的方法:P/T可以表达与产品规范比较时的好坏程度.产品规范的制订有时会太紧，有时又太松。一般来说，当测量系统只是用来检验生产线样品是否合格时，P/T是很有效的。因为这时候，即使过程能力(Cpk)不足，P/T也可以给你足够的信心来判断产品的好坏测量系统变差与过程变差的比较（%R&R）更适合于研究过程的能力与过程改进。,%R&R=20%,%R&R=50%,%R&R=100%,测量系统变差,P/T=20%,P/T=50%,P/T=100%,%R&R=25%,%R&R=50%,%R&R=100%,测量系统变差,P/T=50%,P/T=100%,P/T=200%,%R&R=20%,%R&R=40%,%R&R=100%,测量系统变差,P/T=10%,P/T=20%,P/T=50%,过程实际变差,平均范围=(2+1+1+2+1)/5=7/5=1.4量具误差=5.15*/d=5.15/1.19*=4.33*=4.33*1.4=6.1%GageR&R=量具误差GageError/允差Tolerance=6.1/20*100%=30.5%,快速GR&R（短期模式）,d常数表,允差Tolerance=20,=最大值-最小值,短期模式练习,Averagerange=R=(+)/_=_/_GageError=5.15/d*R=5.15/_*R=_*R=_*_=_%GageR&R=GageError/Tolerance=_/_*100%)=_%,Specrange=185-215,短期与长期方法的比较,短期模式用生产设备用生产操作员快速-只需几个样品(5)无反复（replicates）估计总的变差(TotalGageR&R)不能区分AV和EV不能指导改进的方向可用于破坏性测试,长期模式用生产设备用生产操作员较多样品(5)要求反复Replicates(3)估计总的变差(TotalGageR&R)可以区分AV和EV为测量系统的改进提供指导,正常标准方法,Part,A,B,Test1Test2,Operator,对同样的样品进行重复测量(称之为交叉设计CrossedDesigned),巢式设计NestedDesign,C,Test1Test2,Test1Test2,OperatorI,OperatorII,OperatorIII,样品来自同一总体,PartTest,I,II,III,破坏性测量和不可重复的测量,破坏性测量和不可重复的测量,与可重复测量的测量系统比较样品的个数不是几个(例如10个),而是几组(例如10组),每组内样品的个数等于对该组要进行的破坏性测试的次数每组样品来自过程中连续的产出,默认该组内各样品之间是没有差异的MinitabStatQualityToolsGageStudyGageR&RStudy(Nested)结果中只能看到测量系统的重复性,GageR&R%ContributionSourceVarComp(ofVarComp)TotalGageR&R0.00023112.31Repeatability0.00023112.31Reproducibility0.00000000.00Part-To-Part0.009780797.69TotalVariation0.0100119100.00StudyVar%StudyVarSourceStdDev(SD)(6*SD)(%SV)TotalGageR&R0.0152020.09121415.19Repeatability0.0152020.09121415.19Reproducibility0.0000000.0000000.00Part-To-Part0.0988980.59338698.84TotalVariation0.1000590.600355100.00NumberofDistinctCategories=9,使用前面一样的数据,NO-GO,GO,定性数据(AttributeData)的测量系统,定性数据(AttributeData)的测量系统的可靠性,Go-NoGo数据模式人为因素主导，情况复杂统计模型多种多样统计学上各家争鸣，尚无定论实践中采用何种形式，取决于实例与统计模型的接近程度,对于以“是”和“不是”为计数基础的定性数据，其GR&R考察的概念是与定量数据一样的。但方法上完全不同.定性数据测量系统的能力取决于操作员判断的有效性，即将“合格”判断成合格，将“不合格”判断成不合格的程度.,计数型测量系统能力分析方法示例,以下为判断所用的指标有效性Effectiveness(E)-即判断“合格”与“不合格”的准确性E=实际判断正确的次数/可能判断正确的机会次数.漏判的几率Probabilityofmiss(P-miss)-将“不合格”判为合格的机会P(miss)=实际漏判的次数/漏判的总机会数.误判的几率Probabilityoffalsealarm(P-FA)-将“合格”判为不合格的机会.P(falsealarm)=实际误判次数/误判的总机会数.偏倚Bias(B)-指漏判或误判的偏向.B=P(falsealarm)/P(miss)B=1,无偏倚B1,偏向误判BQualityToolsAttributeAgreementAnalysis,BetweenAppraisersAssessmentAgreement#Inspected#MatchedPercent95%CI121191.67(61.52,99.79)#Matched:Allappraisersassessmentsagreewitheachother.FleissKappaStatisticsResponseKappaSEKappaZP(vs0)F0.7983190.2886752.765460.0028P0.7983190.2886752.765460.0028,ICC等级关联系数IntraclassCorrelationCoefficient,当产品的质量判定不仅仅是合格与不合格两种性质，而是进行多个等级的区分时ICC针对不同情行下的测量系统进行评估ICC使用平方和SumsofSquare来进行评估工作,实例：某公司建立评估系统来测量采购订单(PO)完成的质量水平，选了三个高级采购员对个订单的完成好坏进行打分评估，分代表很差，分代表很好，结果如下,定义如下平方和项BMS=BetweenmeansquareEMS=ErrormeansquareJMS=JudgemeansquareWMS=WithinmeansquareTMS=Totalmeansquare,Sumofallsquared:1