MeasurementSystemsAnalysis(測量系統(tǒng)分析)課件

Presentation1MeasurementSystemsAnalysis

測量系統(tǒng)分析Presentation1MeasurementSysteWarmupExercise熱身練習(xí)TheNecessityofTrainingFarmHandsforFirstClassFarmsintheFatherlyHandlingofFarmLiveStockisForemostintheEyesofFarmOwners.SincetheForefathersoftheFarmOwnersTrainedtheFarmHandsforFirstClassFarmsintheFatherlyHandlingofFarmLiveStock,theFarmOwnersFeeltheyshouldcarryonwiththeFamilyTraditionofTrainingFarmHandsofFirstClassFarmersintheFatherlyHandlingofFarmLiveStockBecausetheyBelieveitistheBasisofGoodFundamentalFarmManagement.Task:Youhave60secondstocountthenumberoftimesthe6thletterofthealphabetappearsattherightparagraph.Areyouready?Go!給你60秒的時間數(shù)出右邊段落中第六個字母的出現(xiàn)次數(shù).WarmupExercise熱身練習(xí)TheNecesWarmupExerciseDocumentyouransweronascrapnoteAswereadtheanswers,typethemintoaMinitabdatasheet.RunahistogramontheresultsWhatareyourobservations?WarmupExerciseDocumentyourObservedVariationWhichprocessisbest?Observed(Total)2TotalVariability(Observedvariability)ProcessAProcessBObservedVariationWhichprocesMeasurementVariationWhichprocessisbest?=Meas.System2Observed(Total)2MeasurementVariabilityTotalVariability(Observedvariability)ProcessAProcessBMeasurementVariationWhichproPartVariationWhichprocessisbest?+Actual(Part)2=PartVariability

(Actualvariability)Meas.System2Observed(Total)2ProcessAProcessBTotalVariability(Observedvariability)MeasurementVariabilityPartVariationWhichprocessisLSLUSLGoodPartsRejected?MeasurementUncertaintyLSLUSLGoodPartsRejected?MeasWhatIsAnMSA?Scientificandobjectivemethodofanalyzingthevalidityofameasurementsystem一種科學(xué)客觀的方法，用于有效的分析測量系統(tǒng)A“tool”whichquantifies:一種工具，它量化：EquipmentVariation設(shè)備波動Appraiser(Operator)Variation評估者波動TheTotalVariationofaMeasurementSystem

測量系統(tǒng)總的波動MSAisNOTjustCalibration測量系統(tǒng)分析不僅僅是校準(zhǔn)MeasurementSystemAnalysisisoftena“projectwithinaproject”測量系統(tǒng)分析經(jīng)常是”項目中的項目”WhatIsAnMSA?ScientificandMainSourcesOfVariationMaterials材料Methods方法Machines機(jī)器People人員Environment環(huán)境Measures測量Measurementsystemsarethemostneglected測量系統(tǒng)經(jīng)常被忽視

測量系統(tǒng)：是用來對被測特性定量測量或定性評價的儀器或量具、標(biāo)準(zhǔn)、操作、方法、夾具、軟件、人員、環(huán)境和假設(shè)的集合；用來獲得測量結(jié)果的整個過程。(MSA手冊第三版定義)MainSourcesOfVariationMateMeasurementSystemAsAProcessCleanlinessTemperatureDimensionWeightCorrosionHardnessConductivityDensitySequenceTimingPositioningLocationSet-upPreparationCleanlinessTemperatureDesignPrecisionCalibrationResolutionStabilityWearCleanlinessVibrationAtmosphericpressureLightingTemperatureHumidityCompliance-procedureFatigueAttentionCalculationerrorInterpretationSpeedCoordinationVisionKnowledge-instrumentDexterityPeopleEnvironmentMeasurementErrorMethodMaterialMachineMeasurementSystemAsAProcesComponentsOfMeasurementErrorResolution/Discrimination分辨率Accuracy(biaseffects)準(zhǔn)確度（偏離）Linearity線性Stability(consistency)穩(wěn)定性（一致性）Repeatability(Precision)重復(fù)性（精度）Reproducibility(Precision)再現(xiàn)性（精度）Eachcomponentofmeasurementerrorcancontributetovariation,causingwrongdecisionstobemade測量誤差的每一項都可能對變差造成影響而使我們做出錯誤的決策ComponentsOfMeasurementErroCategoriesOfMeasurementErrorWhichAffectLocation影響位置的測量誤差A(yù)ccuracy/BiasLinearityStabilityCategoriesOfMeasurementErroCategoriesOfMeasurementErrorWhichAffectSpread影響分布的測量誤差RepeatabilityReproducibilityPrecisionCategoriesOfMeasurementErroResolution/Discrimination分辨率Canchangebedetected?能偵測到改變嗎？Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKResolution/Discrimination分辨率C

ResolutionDefinitions分辨率定義Resolution/Discrimination分辨率Capabilitytodetectthesmallesttolerablechanges

可以偵測最小變化的能力InadequateMeasurementUnits不充分的度量單位Measurementunitstoolargetodetectvariationpresent度量單位過大而不能偵測到變化Guideline:“10BucketRule”

1/10原則Incrementsinthemeasurementsystemshouldbeone-tenththeproductspecificationorprocessvariation

測量系統(tǒng)必須精確到產(chǎn)品范圍或過程變差的1/10ResolutionDefinitions分辨率定義RSameprocessoutputbeingmeasured12345BetterDiscrimination12345PoorDiscrimination1.31Resolution/Discrimination分辨率SameprocessoutputbeingmeasResolution分辨率OnHoldcomplaintsperhour每小時的投訴Complaint

NumberTransfers50Disputes 210Information 143Other 12 Total 415Whatisthecustomer’sbiggestcomplaint?Resolution分辨率OnHoldcomplainOnHoldcomplaintsperhourComplaint

NumberTransfers 50SetuporMaintenanceDisputes 70ServiceReceivedDisputes 60BillingAmountDisputes 80UpdateAccountInformation 115RequestInformation 28Other 12Total 415Whatisthecustomer’sbiggestcomplaint?ResolutionOnHoldcomplaintsperhourWhAccuracy/Bias準(zhǔn)確性/偏離Measurementsare“shifted”from“true”value測量值偏離真值Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKAccuracy/Bias準(zhǔn)確性/偏離MeasuremenDifferencebetweentheobservedaveragevalueofmeasurementsandthemastervalue測量平均值與基準(zhǔn)值之間的差異MasterValue(ReferenceStandard)AverageValueMastervalueisanaccepted,traceablereferencestandard基準(zhǔn)值是公認(rèn)的標(biāo)準(zhǔn)值A(chǔ)ccuracy/Bias準(zhǔn)確性/偏離DifferencebetweentheobservexxxxxxxxxxxxxxxxxxLessaccurateMoreaccurateAccuracy/Bias準(zhǔn)確性/偏離xxxxxxxxxxxxxxxxxxLessaccuratLinearity線性Measurementisnot“true”and/orconsistentacrosstherangeofthe“gage”測量系統(tǒng)在測量范圍內(nèi)與儀器范圍的不一致性Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKLinearity線性MeasurementisnotLinearityFullRangeofGageReferenceValueNoBiasObservedAverageValueBiasLinearityFullRangeofGageRefLinearity-AttributeExampleSurveyscoring:__ SuperOutstanding! 10__ Outstanding! 9__ Incredible 8__ Excellent 7__ Great 6__ VeryGood 5__ Good 4__ OK 3__ Fair 2__ Poor 1Isthisafairscale?Linearity-AttributeExampleSStability穩(wěn)定性Measurementdrifts測量系統(tǒng)偏移Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKStability穩(wěn)定性MeasurementdriftStability穩(wěn)定性Measurementsremainconstantandpredictableovertime

測量系統(tǒng)隨時間保持一致性與可預(yù)見性Forbothmeanandstandarddeviation

含均值與標(biāo)準(zhǔn)偏差Evaluatedusingcontrolcharts

可用控制圖來檢查Time2Time1MasterValue(ReferenceStandard)Stability穩(wěn)定性MeasurementsremaPrecision精確性RepeatabilityandReproducibility重復(fù)性與再現(xiàn)性Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKPrecision精確性Repeatabilityand

Precision精確性2total=2product/process+2repeatability+2reproducibility

GoodPrecisionPoorPrecisionMasterValueABAlsoknownasGageR&RPrecision精確性2total=2prodRepeatability重復(fù)性VariationthatoccurswhenrepeatedmeasurementsaremadeofthesameitemunderabsolutelyidenticalconditionsSame:OperatorSet-upUnitsEnvironmentalconditions重復(fù)性：同一個人使用同樣的設(shè)備、同樣的儀器在同樣的條件下測量同一個樣品的差異Repeatability重復(fù)性VariationthaRepeatability重復(fù)性MasterValuemeanmeanGoodRepeatabilityBadRepeatabilityMasterValueRepeatability重復(fù)性MasterValuemReproducibility再現(xiàn)性VariationthatoccurswhendifferentoperatorsmakethemeasurementsunderabsolutelyidenticalconditionsSame:Set-upsTestunitsEnvironmentalconditionsLocationsCompanies

再現(xiàn)性：不同的人使用同樣的儀器，在同樣的條件下測量同一個樣本之間的差異Reproducibility再現(xiàn)性VariationthReproducibility再現(xiàn)性評價者

A評價者B評價者

C評價者

C評價者

A評價者

BGoodReproducibilityBadReproducibilityMasterValueABCMasterValueABCReproducibility再現(xiàn)性評價者A評價者B評R&R重復(fù)性與再現(xiàn)性TheBigPicture:LinkingThemAllTogether2Total=2R&R +2Processoutput2Total=2Repeat+2Reproducibility+2Processoutput2Total=2Repeat+2Oper+2Oper?Processoutput+2ProcessoutputR&R重復(fù)性與再現(xiàn)性TheBigPicture:LiMeasurementErrorMatchingExerciseMatchthemeasurementelementtothepicturethatbestdescribesit12345A.AccuracyB.StabilityC.LinearityD.ResolutionE.PrecisionTime2Time11.2.3.4.5.ReferenceValueObservedAverageValueMeasurementErrorMatchingExePresentation35

Type1GageStudy

類型1量具分析Presentation35

Type1GageStuPurposeOfType1GageStudyTodeterminehowmuchofyourobservedprocessvariationisduetomeasurementsystemvariation.

確定觀測到的過程變異有多少是由于測量系統(tǒng)本身的變異Tocombinedeffectsofbiasandrepeatabilitybasedonmultiplemeasurementsfromasinglepart.

通過對單個產(chǎn)品的多次測量來計算偏倚和重復(fù)性的影響Type1GageStudyshouldbedonepriortoconductingothergagerepeatabilityandreproducibilitystudies.Todetermineifcalibrationisneed量具的分析應(yīng)該在做重復(fù)性和再現(xiàn)性之前做,來確定是否量具需要校準(zhǔn)。PurposeOfType1GageStudySampleRuleOnemastersample(knownreferencevalue)取一個已知標(biāo)準(zhǔn)值的標(biāo)準(zhǔn)樣品Referencevaluescanbedeterminedinmanyways,dependingonindustrystandardsandcompanyandcustomerexpectations.Someofthebasesforreferencevaluesare:標(biāo)準(zhǔn)值可以通過多種方法獲得，根據(jù)行業(yè)和公司標(biāo)準(zhǔn)及客戶的期望。

1)averageofrepeatedmeasurementsfrommoreaccuratemeasuringequipment用更準(zhǔn)確的測量設(shè)備測量多次取平均值2)valuesendorsedbyaprofessionalgroup專業(yè)機(jī)構(gòu)認(rèn)可的值3)valuesagreeduponbytheaffectedparties客戶認(rèn)可的值4)valuesdefinedbylaw法律規(guī)定的值Tomeasurethemastersample25timesinsameconditionatleast,recordthemeasurements.

在相同條件下重復(fù)測量標(biāo)準(zhǔn)樣品至少25次，記錄每次測量數(shù)據(jù)SampleRuleOnemastersample(StudyMethod在此處輸入測量數(shù)據(jù)在此處輸入標(biāo)準(zhǔn)值在此處輸入測量值的公差規(guī)格StudyMethod在此處輸入測量數(shù)據(jù)在此處輸入標(biāo)準(zhǔn)值在ExampleofType1GageStudy1OpentheworksheetSHAFT.MTW.2ChooseStat>QualityTools>GageStudy>Type1GageStudy.3InMeasurementdata,enterDiameter.4InReference,type12.305.5UnderTolerance,chooseUpperspec-lowerspecandtype0.05.ClickOK.ExampleofType1GageStudy1ExampleofType1GageStudy1）分析結(jié)果顯示偏倚量是-0.00231，P值等于0說明測量系統(tǒng)的偏倚是統(tǒng)計顯著的

同樣從圖上可以看出大部分的測量數(shù)據(jù)都低于標(biāo)準(zhǔn)值。2）Cg是公差和測量變異進(jìn)行比較，CgK是公差和測量變異及偏倚量兩者進(jìn)行比較

Cg和CgK越大，表示測量系統(tǒng)的變異相對公差來說越小。通常Cg和CgK要求大于1.333）%Var(repeatability)由于Cg來確定，%Var(repeatabilityandbias)由Cgk來確定.%Var值小表示測量值變異相對公差而言小.能力指標(biāo)1.33相當(dāng)于%Var＝15%.ExampleofType1GageStudy1）Presentation41AttributeMeasurementSystemStudies

離散型數(shù)據(jù)

測量系統(tǒng)研究Presentation41AttributeMeasurPurposeOfAttributeMSAAssessstandardsagainstcustomers’requirements

對顧客要求的標(biāo)準(zhǔn)進(jìn)行評定Determineifallappraisersusethesamecriteria

確定所有的檢驗者使用相同的標(biāo)準(zhǔn)Quantifyrepeatabilityandreproducibilityofoperators

量化操作者的重復(fù)性與再現(xiàn)性Identifyhowwellmeasurementsystemconformstoa“knownmaster”

確定測量系統(tǒng)對已知標(biāo)準(zhǔn)的符合程度Discoverareaswhere:發(fā)現(xiàn)一些領(lǐng)域：

Trainingisneeded需要培訓(xùn)Proceduresarelacking缺少規(guī)程Standardsarenotdefined標(biāo)準(zhǔn)定義不清晰PurposeOfAttributeMSAAssessSampleRule30samplesatleast,

3appraisersandtwicetests

需要3個測量者，最少30個樣本與每個樣本2次測試40%~45%forpasssamples

40%~45%的好樣本40%~45%forfailsamples

40%~45%的壞樣本10%forequivocalsamples(ifpossible)

10%的邊緣樣本Thecriteriaforsamplesshouldbedeterminedinadvance.樣本的好壞標(biāo)準(zhǔn)需提前確定下來Makesuretherandomizationforthetest

保證樣本測試的隨機(jī)性

SampleRule30samplesatleastAttributeMSA-ExcelMethodAllowsforR&Ranalysiswithinandbetweenappraisers

可以分析評估者之間的R&RTestforeffectivenessagainststandard

對標(biāo)準(zhǔn)判斷的有效性Limitedtonominaldataattwolevels

只能用于兩個水平的名義性數(shù)據(jù)AttributeMSA-ExcelMethodAlDATE:1/4/2001AttributeLegend5

(usedincomputations)NAME:AcmeEmployee1PassPRODUCT:Widgets2FailBUSINESS:EarthProductsKnownPopulationSample#AttributeTry#1Try#2Try#1Try#2Try#1Try#21PassPassPassPassPassPassPass2PassPassPassPassPassPassPass3PassPassPassPassPassPassPass4PassPassPassPassPassFailPass5FailFailFailFailFailPassFail6FailPassPassPassPassPassPass7PassPassPassPassPassPassPass8PassPassPassPassPassPassPass9FailFailFailFailFailFailFail10PassPassPassPassPassPassPass11PassPassPassPassPassPassPass12PassPassPassPassPassPassPass13PassPassPassPassPassPassPass14PassPassPassPassPassFailPass15FailFailFailFailFailPassFail16PassPassPassPassPassPassPass17PassPassPassPassPassPassPass18PassPassPassPassPassPassPass19FailFailFailFailFailFailFail20PassPassPassPassPassPassPass21PassPassPassPassPassPassPass22PassFailFailPassPassPassPass23PassPassPassPassPassPassPass24PassPassPassPassPassFailPass25FailFailFailFailFailFailFail26PassPassPassPassPassPassPass27PassPassPassPassPassPassPass28PassPassPassPassPassPassPass29FailFailFailFailFailFailFail30PassPassPassPassPassPassPassOperator#1Operator#2Operator#3AttributeMSAExampleOpenfileMSA-Attribute.xlsDATE:1/4/2001AttributeLegend5ScoringExample100%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->ScoringExample100.00%100.00%8StatisticalReportStatisticalReportStatisticalReportStatisticalReportStatisticalReport-ContStatisticalReport-ContMINITABMethod-DataEntrySamedataasExcelexample

與Excel例中相同的數(shù)據(jù)Arrangedinmultiplecolumns

數(shù)據(jù)存放在多欄中Datacanalsobestackedinsinglecolumn

數(shù)據(jù)也可以堆疊在單獨一欄中MINITABMethod-DataEntrySamAttributeStudy-MINITABAnalysisAttributeStudy-MINITABAnalAttributeStudy-MINITABAnalysis1.Select“MultipleColumns”ifdataisun-stacked2.Enternumberofappraisersandtrials3.Enternameofcolumnwith“Known”4.SelectOK1.Select“SingleColumn”ifdataisstackedAttributeStudy-MINITABAnalMINITABGraphicalOutputLowervariationwithinappraiserHighervariationwithinappraiserLowervariationappraiservs.standardHighervariationappraiservs.standardNotincludedifno“Known”MINITABGraphicalOutputLowerMINITABSessionWindowResultsEachAppraiservs.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)MINITABSessionWindowResultsAttributeMSAExercise5人一組,選3人為檢查員,一人為記時員,一人為數(shù)據(jù)錄入員。發(fā)給每組3份AttributeGageR&R樣本。每份樣本包含20個方盒，每個方盒包含25個字母或數(shù)字.如果方盒包含任何數(shù)字即被認(rèn)為是有缺陷的（FAIL）。讓3個檢查員獨立地評估手中的第一份樣本并判斷每一個方盒是否有缺陷每個方盒只給5秒的時間做判斷。當(dāng)3位檢查員完成第1份樣本后，將被提供第2份樣本并重復(fù)以上步驟。數(shù)據(jù)錄入員將小組答案錄入AttributeR&R.xls全部完成后，老師將提供標(biāo)準(zhǔn)答案。小組將標(biāo)準(zhǔn)答案錄入，得到R&R的最終分?jǐn)?shù).每組展示自己的AttributeGageR&Rscore。AttributeMSAExercise5人一組,選3Presentation56VariablesMeasurementSystemStudies

連續(xù)型數(shù)據(jù)

測量系統(tǒng)研究Presentation56VariablesMeasurStepVariablesMSAStep1:Randomlyselect10samples.Inaddition,identifytheoperatorswhousethisinstrumentdaily.第一步:隨機(jī)選取10個能夠代表過程變異的樣品,指定常用該檢驗裝置的操作員來做檢查人員Step2:Calibratethegageorverifythelastcalibrationdateisvalid.第二步:檢驗儀器,確認(rèn)儀器在校準(zhǔn)合格期以內(nèi)Step3:SetuptheMinitabdatacollectionsheetfortheR&Rstudy.第三步:用Minitab設(shè)定做GR&R分析的數(shù)據(jù)收集表格Step4:Askthefirstoperatortomeasureallthesamplesonceinrandomorder.Blindsampling,inwhichtheoperatordoesnotknowtheidentityofeachpartshouldbeusedtoreducehumanbias.第四步:要求第一個操作員隨機(jī)測量所有樣品一次,注意不能讓操作員知道樣品的編號,以減少人為偏差.Step5:Havethesecondoperatormeasureallthesamplesonceinrandomorderandcontinueuntilalloperatorshavemeasuredthesamplesonce(thisistrial1)第五步:讓第二個操作員隨機(jī)測量所有樣品一次,繼續(xù)直到所有操作員都測量樣品一次.這算完成第一輪測量.StepVariablesMSAStep1:RanStepVariablesMSAStep6:Repeatsteps4&5fortherequirednumberoftrials.Itisbestifthesemeasurementscanbedoneoverseveraldays.第六步:重復(fù)第4和第5步直到完成需要的輪次.如果可能,測量最好是在跨時間段完成.Step7:EnterthedataandtoleranceinformationintoMinitab

第七步:把數(shù)據(jù)和公差信息輸入到Minitab中Step8:Analyzetheresultsbyassessingthequalityofthemeasurementsystembasedontheguidelinesonthefollowingpage.Determinefollow-upactions.第八步:根據(jù)后續(xù)的測量系統(tǒng)評估指標(biāo)的指導(dǎo)原則來分析測量系統(tǒng)是否可以接受,決定采取必要的行動.SAMPLESELECTIONOption1:ifprocessvariabilityisknown,thesamplesselectedshouldberepresentativeofthenormalprocess/productvariationOption2:ifprocessvariabilityisunknown,thesamplesselectedshoulduniformlyspanbeyondthewidthofthespecs樣品選擇的原則:1)如果過程變異已知,那么樣品要盡量展現(xiàn)正常過程/產(chǎn)品的變異范圍

2)如果過程變異未知,那么樣品要盡量在規(guī)格范圍內(nèi)均勻取樣.StepVariablesMSAStep6:Rep

TrialsAndDataCollectionGenerallytwotothreeoperators

一般選取2到3個操作者Generally5-10processoutputstomeasure

選取5到10個樣本進(jìn)行測量Eachprocessoutputismeasured2-3times(replicated)byeachoperator

每個操作者測量每個樣本2到3次RandomizationisCritical隨機(jī)很關(guān)鍵TrialsAndDataCollectionGenGR&REvaluateGuideline%Contribution=×100%%StudyVariation=×100%%Tolerance=×100%Numberofdistinctcategories=Round{×1.41}部品散布(σpart)測定散布(σMS)σ2MSσ2TotalσMSσTotal5.15×σMSTolerance

(*Tolerance=USL-LSL)區(qū)分%Contribution%StudyVariation或%Tolerance辨別范周良好<1%<10%>10費用/考慮重要性1~10%10~30%5~9不可使用>10%>30%<5GR&REvaluateGuideline%ContriAcceptabilitySummaryTabularMethod%Contribution1%10%Process

Control

%StudyVariation10%30%Product

Control

%Tolerance10%30%Numberof

Distinct

Categories105DesirabletoHaveAll4IndicatorsSay“Go”AcceptabilitySummaryTabularMVariablesMSA-MINITABExampleOpenthefileVariableMSA.mtwUSL=1.0LSL=0.5Replicate1Replicate2(Randomizedorder)VariablesMSA-MINITABExamplMSAUsingMINITAB10ProcessOutputs3Operators2ReplicatesHaveOperator1measureallsamplesonce(asshownintheoutlinedblock)Then,haveOperator2measureallsamplesonceContinueuntilalloperatorshavemeasuredsamplesonce(thisisReplicate1)RepeatthesestepsfortherequirednumberofReplicatesEnterdataintoMINITABin3columnsasshown

USL=1.5LSL=0.5Replicate1Replicate2(Randomizedorder)MSAUsingMINITAB10ProcessOuManipulateTheDataYourdatainMINITABshouldinitiallylooklikethis.YouwillneedtoSTACKyourdatasothatalllikedataisinonecolumnonlyNowyouarereadytorunthemacrofordataanalysisUsethecommands >Data >Stack >StackBlocksofColumns(StackallProcessOutputs,Operators,andResponsessothattheyareinonecolumnonly)ManipulateTheDataYourdataiNote:c8,c9,c10arethecolumnsinwhichtherespectivedataarefoundINOUREXAMPLE.YoumusthaveALLdataSTACKEDinthesecolumnsStackedAndReadyForAnalysisNote:StackedAndReadyForAnaAnalysisinMinitabANOVAmethodispreferredGivesmoreinformationEnterGageInfoandOptionsAnalysisinMinitabANOVAmethoUSL-LSL=0.50USL=1.0LSL=0.6USL=1.0LSL=0.5AddingTolerance(Optional)UpperSpecificationLimit(USL)MinusLowerSpecificationLimit(LSL)Forthisexample:USL-LSL=0.50USL=1.0LSL=0.6USTwo-WayANOVATableWithInteractionSourceDFSSMSFPPart92.058710.22874539.71780.00000Operator20.048000.0240004.16720.03256Operator*Part180.103670.0057594.45880.00016Repeatability300.038750.001292Total592.24912GageR&R%ContributionSourceVarComp(ofVarComp)TotalGageR&R0.00443710.67Repeatability0.0012923.10Reproducibility0.0031467.56Operator0.0009122.19Operator*Part0.0022345.37Part-To-Part0.03716489.33TotalVariation0.041602100.00StdDevStudyVar%StudyVar%ToleranceSource(SD)(5.15*SD)(%SV)(SV/Toler)TotalGageR&R0.0666150.3430632.6668.61Repeatability0.0359400.1850917.6237.02Reproducibility0.0560880.2888527.5057.77Operator0.0302000.1555314.8131.11Operator*Part0.0472630.2434023.1748.68Part-To-Part0.1927810.9928294.52198.56TotalVariation0.2039651.05042100.00210.08NumberofDistinctCategories=4MSAOutput:SessionWindowTwo-WayANOVATableWithInterGraphicalOutput-6GraphsInAllWhatdoesallthismean?GraphicalOutput-6GraphsInPresentation70MeasurementSystemsAnalysis

測量系統(tǒng)分析Presentation1MeasurementSysteWarmupExercise熱身練習(xí)TheNecessityofTrainingFarmHandsforFirstClassFarmsintheFatherlyHandlingofFarmLiveStockisForemostintheEyesofFarmOwners.SincetheForefathersoftheFarmOwnersTrainedtheFarmHandsforFirstClassFarmsintheFatherlyHandlingofFarmLiveStock,theFarmOwnersFeeltheyshouldcarryonwiththeFamilyTraditionofTrainingFarmHandsofFirstClassFarmersintheFatherlyHandlingofFarmLiveStockBecausetheyBelieveitistheBasisofGoodFundamentalFarmManagement.Task:Youhave60secondstocountthenumberoftimesthe6thletterofthealphabetappearsattherightparagraph.Areyouready?Go!給你60秒的時間數(shù)出右邊段落中第六個字母的出現(xiàn)次數(shù).WarmupExercise熱身練習(xí)TheNecesWarmupExerciseDocumentyouransweronascrapnoteAswereadtheanswers,typethemintoaMinitabdatasheet.RunahistogramontheresultsWhatareyourobservations?WarmupExerciseDocumentyourObservedVariationWhichprocessisbest?Observed(Total)2TotalVariability(Observedvariability)ProcessAProcessBObservedVariationWhichprocesMeasurementVariationWhichprocessisbest?=Meas.System2Observed(Total)2MeasurementVariabilityTotalVariability(Observedvariability)ProcessAProcessBMeasurementVariationWhichproPartVariationWhichprocessisbest?+Actual(Part)2=PartVariability

(Actualvariability)Meas.System2Observed(Total)2ProcessAProcessBTotalVariability(Observedvariability)MeasurementVariabilityPartVariationWhichprocessisLSLUSLGoodPartsRejected?MeasurementUncertaintyLSLUSLGoodPartsRejected?MeasWhatIsAnMSA?Scientificandobjectivemethodofanalyzingthevalidityofameasurementsystem一種科學(xué)客觀的方法，用于有效的分析測量系統(tǒng)A“tool”whichquantifies:一種工具，它量化：EquipmentVariation設(shè)備波動Appraiser(Operator)Variation評估者波動TheTotalVariationofaMeasurementSystem

測量系統(tǒng)總的波動MSAisNOTjustCalibration測量系統(tǒng)分析不僅僅是校準(zhǔn)MeasurementSystemAnalysisisoftena“projectwithinaproject”測量系統(tǒng)分析經(jīng)常是”項目中的項目”WhatIsAnMSA?ScientificandMainSourcesOfVariationMaterials材料Methods方法Machines機(jī)器People人員Environment環(huán)境Measures測量Measurementsystemsarethemostneglected測量系統(tǒng)經(jīng)常被忽視

測量系統(tǒng)：是用來對被測特性定量測量或定性評價的儀器或量具、標(biāo)準(zhǔn)、操作、方法、夾具、軟件、人員、環(huán)境和假設(shè)的集合；用來獲得測量結(jié)果的整個過程。(MSA手冊第三版定義)MainSourcesOfVariationMateMeasurementSystemAsAProcessCleanlinessTemperatureDimensionWeightCorrosionHardnessConductivityDensitySequenceTimingPositioningLocationSet-upPreparationCleanlinessTemperatureDesignPrecisionCalibrationResolutionStabilityWearCleanlinessVibrationAtmosphericpressureLightingTemperatureHumidityCompliance-procedureFatigueAttentionCalculationerrorInterpretationSpeedCoordinationVisionKnowledge-instrumentDexterityPeopleEnvironmentMeasurementErrorMethodMaterialMachineMeasurementSystemAsAProcesComponentsOfMeasurementErrorResolution/Discrimination分辨率Accuracy(biaseffects)準(zhǔn)確度（偏離）Linearity線性Stability(consistency)穩(wěn)定性（一致性）Repeatability(Precision)重復(fù)性（精度）Reproducibility(Precision)再現(xiàn)性（精度）Eachcomponentofmeasurementerrorcancontributetovariation,causingwrongdecisionstobemade測量誤差的每一項都可能對變差造成影響而使我們做出錯誤的決策ComponentsOfMeasurementErroCategoriesOfMeasurementErrorWhichAffectLocation影響位置的測量誤差A(yù)ccuracy/BiasLinearityStabilityCategoriesOfMeasurementErroCategoriesOfMeasurementErrorWhichAffectSpread影響分布的測量誤差RepeatabilityReproducibilityPrecisionCategoriesOfMeasurementErroResolution/Discrimination分辨率Canchangebedetected?能偵測到改變嗎？Resolution?Accuracy/Bias?Linearity?Stability?Precision(R&R)?OKOKOKOKResolution/Discrimination分辨率C

ResolutionDefinitions分辨率定義Resolution/Discrimination分辨率Capabilitytodetectthesmallesttolerablechanges

可以偵測最小變化的能力InadequateMeasurementUnits不充分的度量單位Measurementunitstoolargetodetectvariationpresent度量單位過大