MeasurementSystemsAnalysis(测量系统分析)

MeasurementSystemsAnalysis

测量系统分析1WarmupExercise热身练习TheNecessityofTrainingFarmHandsforFirstClassFarmsintheFatherlyHandlingofFarmLiveStockisForemostintheEyesofFarmOwners.SincetheForefathersoftheFarmOwnersTrainedtheFarmHandsforFirstClassFarmsintheFatherlyHandlingofFarmLiveStock,theFarmOwnersFeeltheyshouldcarryonwiththeFamilyTraditionofTrainingFarmHandsofFirstClassFarmersintheFatherlyHandlingofFarmLiveStockBecausetheyBelieveitistheBasisofGoodFundamentalFarmManagement.Task:Youhave60secondstocountthenumberoftimesthe6thletterofthealphabetappearsattherightparagraph.Areyouready?Go!给你60秒的时间数出右边段落中第六个字母的出现次数.WarmupExerciseDocumentyouransweronascrapnoteAswereadtheanswers,typethemintoaMinitabdatasheet.RunahistogramontheresultsWhatareyourobservations?ObservedVariationWhichprocessisbest?

Observed(Total)2TotalVariability(Observedvariability)ProcessAProcessBMeasurementVariationWhichprocessisbest?=

Meas.System2

Observed(Total)2MeasurementVariabilityTotalVariability(Observedvariability)ProcessAProcessBPartVariationWhichprocessisbest?+

Actual(Part)2=PartVariability

(Actualvariability)

Meas.System2

Observed(Total)2ProcessAProcessBTotalVariability(Observedvariability)MeasurementVariabilityLSLUSLGoodPartsRejected?MeasurementUncertaintyWhatIsAnMSA?Scientificandobjectivemethodofanalyzingthevalidityofameasurementsystem一种科学客观的方法，用于有效的分析测量系统A“tool”whichquantifies:一种工具，它量化：EquipmentVariation设备波动Appraiser(Operator)Variation评估者波动TheTotalVariationofaMeasurementSystem

测量系统总的波动MSAisNOTjustCalibration测量系统分析不仅仅是校准MeasurementSystemAnalysisisoftena“projectwithinaproject”测量系统分析经常是”项目中的项目”MainSourcesOfVariationMaterials材料Methods方法Machines机器People人员Environment环境Measures测量Measurementsystemsarethemostneglected测量系统经常被忽视

测量系统：是用来对被测特性定量测量或定性评价的仪器或量具、标准、操作、方法、夹具、软件、人员、环境和假设的集合；用来获得测量结果的整个过程。(MSA手册第三版定义)MeasurementSystemAsAProcessCleanlinessTemperatureDimensionWeightCorrosionHardnessConductivityDensitySequenceTimingPositioningLocationSet-upPreparationCleanlinessTemperatureDesignPrecisionCalibrationResolutionStabilityWearCleanlinessVibrationAtmosphericpressureLightingTemperatureHumidityCompliance-procedureFatigueAttentionCalculationerrorInterpretationSpeedCoordinationVisionKnowledge-instrumentDexterityPeopleEnvironmentMeasurementErrorMethodMaterialMachineComponentsOfMeasurementErrorResolution/Discrimination分辨率Accuracy(biaseffects)准确度（偏离）Linearity线性Stability(consistency)稳定性（一致性）Repeatability(Precision)重复性（精度）Reproducibility(Precision)再现性（精度）Eachcomponentofmeasurementerrorcancontributetovariation,causingwrongdecisionstobemade测量误差的每一项都可能对变差造成影响而使我们做出错误的决策CategoriesOfMeasurementErrorWhichAffectLocation影响位置的测量误差Accuracy/BiasLinearityStabilityCategoriesOfMeasurementErrorWhichAffectSpread影响分布的测量误差RepeatabilityReproducibilityPrecisionResolution/Discrimination分辨率Canchangebedetected?能侦测到改变吗？Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKResolutionDefinitions分辨率定义Resolution/Discrimination分辨率Capabilitytodetectthesmallesttolerablechanges

可以侦测最小变化的能力InadequateMeasurementUnits不充分的度量单位Measurementunitstoolargetodetectvariationpresent度量单位过大而不能侦测到变化Guideline:“10BucketRule”

1/10原则Incrementsinthemeasurementsystemshouldbeone-tenththeproductspecificationorprocessvariation

测量系统必须精确到产品范围或过程变差的1/10Sameprocessoutputbeingmeasured12345BetterDiscrimination12345PoorDiscrimination1.31Resolution/Discrimination分辨率Resolution分辨率OnHoldcomplaintsperhour每小时的投诉Complaint

NumberTransfers50Disputes 210Information 143Other 12 Total 415Whatisthecustomer’sbiggestcomplaint?OnHoldcomplaintsperhourComplaint

NumberTransfers 50SetuporMaintenanceDisputes 70ServiceReceivedDisputes 60BillingAmountDisputes 80UpdateAccountInformation 115RequestInformation 28Other 12Total 415Whatisthecustomer’sbiggestcomplaint?ResolutionAccuracy/Bias准确性/偏离Measurementsare“shifted”from“true”value测量值偏离真值Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKDifferencebetweentheobservedaveragevalueofmeasurementsandthemastervalue测量平均值与基准值之间的差异MasterValue(ReferenceStandard)AverageValueMastervalueisanaccepted,traceablereferencestandard基准值是公认的标准值Accuracy/Bias准确性/偏离xxxxxxxxxxxxxxxxxxLessaccurateMoreaccurateAccuracy/Bias准确性/偏离Linearity线性Measurementisnot“true”and/orconsistentacrosstherangeofthe“gage”测量系统在测量范围内与仪器范围的不一致性Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKLinearityFullRangeofGageReferenceValueNoBiasObservedAverageValueBiasLinearity-AttributeExampleSurveyscoring:__ SuperOutstanding! 10__ Outstanding! 9__ Incredible 8__ Excellent 7__ Great 6__ VeryGood 5__ Good 4__ OK 3__ Fair 2__ Poor 1Isthisafairscale?Stability稳定性Measurementdrifts测量系统偏移Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKStability稳定性Measurementsremainconstantandpredictableovertime

测量系统随时间保持一致性与可预见性Forbothmeanandstandarddeviation

含均值与标准偏差Evaluatedusingcontrolcharts

可用控制图来检查Time2Time1MasterValue(ReferenceStandard)Precision精确性RepeatabilityandReproducibility重复性与再现性Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKPrecision精确性

2total=

2product/process+

2repeatability+

2reproducibility

GoodPrecisionPoorPrecisionMasterValueABAlsoknownasGageR&RRepeatability重复性VariationthatoccurswhenrepeatedmeasurementsaremadeofthesameitemunderabsolutelyidenticalconditionsSame:OperatorSet-upUnitsEnvironmentalconditions重复性：同一个人使用同样的设备、同样的仪器在同样的条件下测量同一个样品的差异Repeatability重复性MasterValuemeanmeanGoodRepeatabilityBadRepeatabilityMasterValueReproducibility再现性VariationthatoccurswhendifferentoperatorsmakethemeasurementsunderabsolutelyidenticalconditionsSame:Set-upsTestunitsEnvironmentalconditionsLocationsCompanies

再现性：不同的人使用同样的仪器，在同样的条件下测量同一个样本之间的差异Reproducibility再现性评价者

A评价者B评价者

C评价者

C评价者

A评价者

BGoodReproducibilityBadReproducibilityMasterValueABCMasterValueABCR&R重复性与再现性TheBigPicture:LinkingThemAllTogether

2Total=

2R&R +

2Processoutput

2Total=

2Repeat+

2Reproducibility+

2Processoutput

2Total=

2Repeat+

2Oper+

2Oper•Processoutput+

2ProcessoutputMeasurementErrorMatchingExerciseMatchthemeasurementelementtothepicturethatbestdescribesit12345A.AccuracyB.StabilityC.LinearityD.ResolutionE.PrecisionTime2Time11.2.3.4.5.ReferenceValueObservedAverageValue

Type1GageStudy

类型1量具分析35PurposeOfType1GageStudyTodeterminehowmuchofyourobservedprocessvariationisduetomeasurementsystemvariation.

确定观测到的过程变异有多少是由于测量系统本身的变异Tocombinedeffectsofbiasandrepeatabilitybasedonmultiplemeasurementsfromasinglepart.

通过对单个产品的多次测量来计算偏倚和重复性的影响Type1GageStudyshouldbedonepriortoconductingothergagerepeatabilityandreproducibilitystudies.Todetermineifcalibrationisneed量具的分析应该在做重复性和再现性之前做,来确定是否量具需要校准。SampleRuleOnemastersample(knownreferencevalue)取一个已知标准值的标准样品Referencevaluescanbedeterminedinmanyways,dependingonindustrystandardsandcompanyandcustomerexpectations.Someofthebasesforreferencevaluesare:标准值可以通过多种方法获得，根据行业和公司标准及客户的期望。

1)averageofrepeatedmeasurementsfrommoreaccuratemeasuringequipment用更准确的测量设备测量多次取平均值2)valuesendorsedbyaprofessionalgroup专业机构认可的值3)valuesagreeduponbytheaffectedparties客户认可的值4)valuesdefinedbylaw法律规定的值Tomeasurethemastersample25timesinsameconditionatleast,recordthemeasurements.

在相同条件下重复测量标准样品至少25次，记录每次测量数据StudyMethod在此处输入测量数据在此处输入标准值在此处输入测量值的公差规格ExampleofType1GageStudy1OpentheworksheetSHAFT.MTW.2ChooseStat>QualityTools>GageStudy>Type1GageStudy.3InMeasurementdata,enterDiameter.4InReference,type12.305.5UnderTolerance,chooseUpperspec-lowerspecandtype0.05.ClickOK.ExampleofType1GageStudy1）分析结果显示偏倚量是-0.00231，P值等于0说明测量系统的偏倚是统计显著的

同样从图上可以看出大部分的测量数据都低于标准值。2）Cg是公差和测量变异进行比较，CgK是公差和测量变异及偏倚量两者进行比较

Cg和CgK越大，表示测量系统的变异相对公差来说越小。通常Cg和CgK要求大于1.333）%Var(repeatability)由于Cg来确定，%Var(repeatabilityandbias)由Cgk来确定.%Var值小表示测量值变异相对公差而言小.能力指标1.33相当于%Var＝15%.AttributeMeasurementSystemStudies

离散型数据

测量系统研究41PurposeOfAttributeMSAAssessstandardsagainstcustomers’requirements

对顾客要求的标准进行评定Determineifallappraisersusethesamecriteria

确定所有的检验者使用相同的标准Quantifyrepeatabilityandreproducibilityofoperators

量化操作者的重复性与再现性Identifyhowwellmeasurementsystemconformstoa“knownmaster”

确定测量系统对已知标准的符合程度Discoverareaswhere:发现一些领域：

Trainingisneeded需要培训Proceduresarelacking缺少规程Standardsarenotdefined标准定义不清晰SampleRule30samplesatleast,

3appraisersandtwicetests

需要3个测量者，最少30个样本与每个样本2次测试40%~45%forpasssamples

40%~45%的好样本40%~45%forfailsamples

40%~45%的坏样本10%forequivocalsamples(ifpossible)

10%的边缘样本Thecriteriaforsamplesshouldbedeterminedinadvance.样本的好坏标准需提前确定下来Makesuretherandomizationforthetest

保证样本测试的随机性

AttributeMSA-ExcelMethodAllowsforR&Ranalysiswithinandbetweenappraisers

可以分析评估者之间的R&RTestforeffectivenessagainststandard

对标准判断的有效性Limitedtonominaldataattwolevels

只能用于两个水平的名义性数据DATE:1/4/2001AttributeLegend5(usedincomputations)NAME:AcmeEmployee1PassPRODUCT:Widgets2FailBUSINESS:EarthProductsKnownPopulationSample#AttributeTry#1Try#2Try#1Try#2Try#1Try#21PassPassPassPassPassPassPass2PassPassPassPassPassPassPass3PassPassPassPassPassPassPass4PassPassPassPassPassFailPass5FailFailFailFailFailPassFail6FailPassPassPassPassPassPass7PassPassPassPassPassPassPass8PassPassPassPassPassPassPass9FailFailFailFailFailFailFail10PassPassPassPassPassPassPass11PassPassPassPassPassPassPass12PassPassPassPassPassPassPass13PassPassPassPassPassPassPass14PassPassPassPassPassFailPass15FailFailFailFailFailPassFail16PassPassPassPassPassPassPass17PassPassPassPassPassPassPass18PassPassPassPassPassPassPass19FailFailFailFailFailFailFail20PassPassPassPassPassPassPass21PassPassPassPassPassPassPass22PassFailFailPassPassPassPass23PassPassPassPassPassPassPass24PassPassPassPassPassFailPass25FailFailFailFailFailFailFail26PassPassPassPassPassPassPass27PassPassPassPassPassPassPass28PassPassPassPassPassPassPass29FailFailFailFailFailFailFail30PassPassPassPassPassPassPassOperator#1Operator#2Operator#3AttributeMSAExampleOpenScoringExample100%istargetforallscores<100%indicatestrainingrequired%Appraiserscore=repeatabilityScreen%EffectivenessScore=reproducibility%Scorevs.AttributeindividualerroragainstaknownpopulationScreen%Effectivevs.AttributeTotalerroragainstaknownpopulation100.00%100.00%83.33%93.33%96.67%80.00%SCREEN%EFFECTIVESCORE->80.00%SCREEN%EFFECTIVESCOREvs.ATTRIBUTE->76.67%%APPRAISERSCORE->%SCOREVS.ATTRIBUTE->StatisticalReportStatisticalReportStatisticalReport-ContMINITABMethod-DataEntrySamedataasExcelexample

与Excel例中相同的数据Arrangedinmultiplecolumns

数据存放在多栏中Datacanalsobestackedinsinglecolumn

数据也可以堆叠在单独一栏中AttributeStudy-MINITABAnalysisAttributeStudy-MINITABAnalysis1.Select“MultipleColumns”ifdataisun-stacked2.Enternumberofappraisersandtrials3.Enternameofcolumnwith“Known”4.SelectOK1.Select“SingleColumn”ifdataisstackedMINITABGraphicalOutputLowervariationwithinappraiserHighervariationwithinappraiserLowervariationappraiservs.standardHighervariationappraiservs.standardNotincludedifno“Known”MINITABSessionWindowResultsEachAppraiservs.StandardAssessmentAgreementAppraiser#Inspected#MatchedPercent(%)95.0%CIBob302893.3(77.9,99.2)Sue302996.7(82.8,99.9)Tom302480.0(61.4,92.3)#Matched:Appraiser'sassessmentacrosstrialsagreeswithstandard.AssessmentDisagreementAppraiser#Pass/FailPercent(%)#Fail/PassPercent(%)#MixedPercent(%)Bob114.2914.3500.0Sue114.2900.000.0Tom114.2900.0516.7#Pass/Fail:Assessmentsacrosstrials=Pass/standard=Fail.#Fail/Pass:Assessmentsacrosstrials=Fail/standard=Pass.#Mixed:Assessmentsacrosstrialsarenotidentical.BetweenAppraisersAssessmentAgreement#Inspected#MatchedPercent(%)95.0%CI302480.0(61.4,92.3)#Matched:Allappraisers'assessmentsagreewitheachother.AllAppraisersvs.StandardAssessmentAgreement#Inspected#MatchedPercent(%)95.0%CI302376.7(57.7,90.1)#Matched:Allappraisers'assessmentsagreewithstandard.Individualvs.StandardDisagreementassessment(repeatability)Betweenappraisers(reproducibility)Totalagreement(againstknown)AttributeMSAExercise5人一组,选3人为检查员,一人为记时员,一人为数据录入员。发给每组3份AttributeGageR&R样本。每份样本包含20个方盒，每个方盒包含25个字母或数字.如果方盒包含任何数字即被认为是有缺陷的（FAIL）。让3个检查员独立地评估手中的第一份样本并判断每一个方盒是否有缺陷每个方盒只给5秒的时间做判断。当3位检查员完成第1份样本后，将被提供第2份样本并重复以上步骤。数据录入员将小组答案录入AttributeR&R.xls全部完成后，老师将提供标准答案。小组将标准答案录入，得到R&R的最终分数.每组展示自己的AttributeGageR&Rscore。VariablesMeasurementSystemStudies

连续型数据

测量系统研究56StepVariablesMSAStep1:Randomlyselect10samples.Inaddition,identifytheoperatorswhousethisinstrumentdaily.第一步:随机选取10个能够代表过程变异的样品,指定常用该检验装置的操作员来做检查人员Step2:Calibratethegageorverifythelastcalibrationdateisvalid.第二步:检验仪器,确认仪器在校准合格期以内Step3:SetuptheMinitabdatacollectionsheetfortheR&Rstudy.第三步:用Minitab设定做GR&R分析的数据收集表格Step4:Askthefirstoperatortomeasureallthesamplesonceinrandomorder.Blindsampling,inwhichtheoperatordoesnotknowtheidentityofeachpartshouldbeusedtoreducehumanbias.第四步:要求第一个操作员随机测量所有样品一次,注意不能让操作员知道样品的编号,以减少人为偏差.Step5:Havethesecondoperatormeasureallthesamplesonceinrandomorderandcontinueuntilalloperatorshavemeasuredthesamplesonce(thisistrial1)第五步:让第二个操作员随机测量所有样品一次,继续直到所有操作员都测量样品一次.这算完成第一轮测量.StepVariablesMSAStep6:Repeatsteps4&5fortherequirednumberoftrials.Itisbestifthesemeasurementscanbedoneoverseveraldays.第六步:重复第4和第5步直到完成需要的轮次.如果可能,测量最好是在跨时间段完成.Step7:EnterthedataandtoleranceinformationintoMinitab

第七步:把数据和公差信息输入到Minitab中Step8:Analyzetheresultsbyassessingthequalityofthemeasurementsystembasedontheguidelinesonthefollowingpage.Determinefollow-upactions.第八步:根据后续的测量系统评估指标的指导原则来分析测量系统是否可以接受,决定采取必要的行动.SAMPLESELECTIONOption1:ifprocessvariabilityisknown,thesamplesselectedshouldberepresentativeofthenormalprocess/productvariationOption2:ifprocessvariabilityisunknown,thesamplesselectedshoulduniformlyspanbeyondthewidthofthespecs样品选择的原则:1)如果过程变异已知,那么样品要尽量展现正常过程/产品的变异范围

2)如果过程变异未知,那么样品要尽量在规格范围内均匀取样.TrialsAndDataCollectionGenerallytwotothreeoperators

一般选取2到3个操作者Generally5-10processoutputstomeasure

选取5到10个样本进行测量Eachprocessoutputismeasured2-3times(replicated)byeachoperator

每个操作者测量每个样本2到3次RandomizationisCritical随机很关键GR&REvaluateGuideline%Contribution=×100%%StudyVariation=×100%%Tolerance=×100%Numberofdistinctcategories=Round{×1.41}部品散布(σpart)测定散布(σMS)σ2MSσ2TotalσMSσTotal5.15×σMSTolerance

(*Tolerance=USL-LSL)区分%Contribution%StudyVariation或%Tolerance辨别范周良好<1%<10%>10费用/考虑重要性1~10%10~30%5~9不可使用>10%>30%<5AcceptabilitySummaryTabularMethod%Contribution1%10%Process

Control

%StudyVariation10%30%Product

Control

%Tolerance10%30%Numberof

Distinct

Categories105DesirabletoHaveAll4IndicatorsSay“Go”VariablesMSA-MINITABExampleOpenthefileVariableMSA.mtwUSL=1.0LSL=0.5Replicate1Replicate2(Randomizedorder)MSAUsingMINITAB10ProcessOutputs3Operators2ReplicatesHaveOperator1measureallsamplesonce(asshownintheoutlinedblock)Then,haveOperator2measureallsamplesonceContinueuntilalloperatorshavemeasuredsamplesonce(thisisReplicate1)RepeatthesestepsfortherequirednumberofReplicatesEnterdataintoMINITABin3columnsasshownUSL=1.5LSL=0.5Replicate1Replicate2(Randomizedorder)ManipulateTheDataYourdatainMINITABshouldinitiallylooklikethis.YouwillneedtoSTACKyourdatasothatalllikedataisinonecolumnonlyNowyouarereadytorunthemacrofordataanalysisUsethecommands >Data