WCM精华之QC Workshop.ppt

1,QCWorkshop,Dr.H.YamashinaProfessorEmeritus,KyotoUniversityFellowofRCA(TheU.K.)MemberofRoyalSwedishAcademyofEngineeringSciences,19thJuly,2007,2,Contents1.JapansQCHistory2.WhatIstheQCProblemSolvingApproach?3.TheQCViewpointVitalforQC-TypeProblemSolving4.QualitySpecificationandProcessCapability5.HowtoImproveProcessCapability6.QualityAssuranceofEveryQualityItem7.TheQCSevenStepFormulaSolvingProblemstheQCWay8.TheFourMajorFactorsInfluencingProcessCapability9.ProcessingPointAnalysis10.DiagnosticTabletoCheckQualityControlKeyQuestions,3,CHAPTER1,JapansQCHistory,4,TheDevelopmentofJapansQualityControl:aLongJourney,Vision,strategySatisfactionsofstakeholdersManagementRstandardizethebestworkingmethods,teachthestandards,andseethattheseareobserved.Qualityisbuiltinviatheprocess,notthroughinspection.Thisiswhatmakesitsoimportanttocontrolprocessesproperly.Lookbeyondtheresults,reflectontheprocessthatproducedthem,improveworkingmethods,andraisethequalityofwork.Analyzethereasonsforanyshortfallsbetweentargetsandresultsandcontrolthecause-and-effectsystem.,84,3.9DispersionControlPayattentiontodispersionandidentifyitscauses3.9.1WhatIsDispersionControl?Datawillalwaysbedispersedaroundacertainvalue.Wemusttakenoteofthemeanandthedispersion,searchoutthecauseofthedispersion,reducethedispersionandkeepitwithinacceptablelimits,andmaintaintheprocessinastablestate.Thisisdispersioncontrol.,85,TheKeyPointsofDispersionControlEliminatedeviationfromstandards.Sincedataaredispersedaboutacertaincentralvalue,wemustidentifythefollowingfactors:,Ifthereisanydeviationfromthestandard,weinvestigatethecausesandtakecountermeasures.Onetoolwecanuseforcomparingresultswithstandardsisthehistogram.,Therearetwokeypointsindispersioncontrol,asdescribedbelow:,86,2.Keeptheprocessinastablestate.Everyprocesscontainsalargenumberoffactorsthatcreatedispersioninthequalityoftheproduct.Thesefactorsorcausescanbeclassifiedintothefollowingtwotypes:,Chancecauses:dispersionduetochancecausesisunavoidable.Itarisesevenwhenthematerials,workingmethods,andotherconditionsallconformtostandards.Assignablecauses:dispersionduetoassignablecausesmustnotbeignored.Itarisesforvariousreasons,suchasbecausetheworkstandardsarenotbeingobservedorbecausethestandardsareinadequate.,Tomaintainaprocessinthestablestate,wecanignorethechancecausesbutwemusteliminateanyassignablecausesandtakeappropriateactiontoensurethatthesamecausesdonotariseagaininthefuture.Controlchartsareusedtoanalyzeandcontrolprocessesbyclassifyingdispersionintothekindduetochancecausesandthekindduetoassignablecauses.,87,3.10RecurrencePreventionInstituteradicalcountermeasurestoensurethatthesamemistakeisnotrepeated,3.10.1Whatisrecurrenceprevention?Recurrencepreventionmeansidentifyingthecausesoftroubleandtakingcountermeasuresagainstthosecausestoensurethattheyneverrecur.Toachievethis,thefollowingthreetypesofcountermeasuremustbetaken(seeTable3.3).,88,Table3.3Countermeasuretypes,89,Fig.3.17Recurrence-PreventionSystem,Primarycountermeasure,Secondarycountermeasure,Tertiarycountermeasure,AnythingwhichadverselyaffectssubsequentprocessesAnythingwhichcausesactualharmAnythingwhichappearslikelytocauseharmifithappensagain,Whydiditoccur?Whywasitnotdetectedinadvanceinupstreamprocesses?Delvedowntothreesuccessivelevelstofindtherootcause,Emergencyimprovementproposalforproblematicproduct,processorwork,PermanentimprovementplansforprocessorworkcontainingtroublePlansforimprovingdetectionmethodsinprocessorphasewhereproblemshouldreallyhavebeendetected,Plansforimprovingworkingmethodsorsystemswhichledtotrouble,Stopgapcountermeasure,Individualrecurrence-preventioncountermeasure,Clarificationofcauses,Systematicrecurrence-preventioncountermeasure,Identificationoftrouble(problem),90,3.11StandardizationFormulate,observe,andutilizestandards3.11.1Whatisstandardization?Standardizationmeanssettingstandardsformaterialsandworkingmethodsandputtingthemintoeffect.Whenpreparingworkstandards,itisimportanttoensure:,Thattheworkproceduresareappropriate.Thatthestandardsareexpressedinspecific,concreteterms.Thattheprioritiesareclear.Thatthestandardsareeasilyunderstoodandmakeplentifuluseofdiagramsandcharts.,Weshouldstrivetoavoidthe“Isetstandards,youobeythem”dichotomyandtrytogeteverybodyworkingtogethertoformulateandobservestandards.,91,Operationalstandards,Ifoperationalstandardsarenotwellmanaged,Willnotmatchtheexistingsituations,Willnotmatchtheimprovement,Yieldswilldecrease,defectiveswillincrease,Therewillbeaproblemforthedeliverytime,Willlosecustomerscredibility,Therewillbeproblemsofsafety,Ifoperationalstandardsdonotexist,Operatorscarryouttheirjobsintheirownways,Operationalconditionswillfluctuate,Therewillbechangesinquality,Variationwillincrease,Yieldswilldecrease,defectiveswillincrease,Therewillbechangeinqualitycharacteristics,Dispersionwillbecomebigger,Ifstandardsarenotkept,Ifstandardsareignored,Basedontheoperationalstandards,Operationalmanagement,Trainingandeducation,Improvetheyields.Reducethenumberofdefectives,Improveskilllevel,Operationalstandardsareignoredandbecomemerelyanexistence,Regulationsbecomemerelyaname,Problemsoncost,process,quality,Therearisemoreoperationalmanagementproblems,Fig.3.9Influencesofoperationalstandards,92,Inaworkplace,activitiesforformulating,revising,andobservingstandardscanbedevelopedinaccordancewiththeschemeshowninFig.3.10.,93,Fig.3.10Standardizationflowchartshowingkeypoints,Teachstandards,Giveworkerstechnicaltrainingorreallocatetodifferentjobs,Instructandguideworkerstofollowstandards,Considerstationingofworkersinimprovedworkingenvironment,Improveworkingmethodsbyintroducingerror-proofingdevices,Workersdonotunderstandormisunderstandstandard,Workerslackabilitytofollowstandard,Workersdonotappreciatenecessityforfollowingstandard,Workingconditionsareinadequate,Easily-mistakenprocedureorcomplicatedequipment,Wasthestandardbeingfollowed?,Trouble(nonconformingproducts,defects,etc.)occurs,Planandimplementemergencycountermeasures,Investigatethecauseofthetrouble,Isthereaworkstandard?,Istheworkstandardappropriate?,Prepareaworkstandardandensurethatallworkersfollow.,Decidewheretokeepitandrewriteittosuitpresentworkmethods,Rewriteitintheformofaspecificprocedure.Usediagramstomakeiteasytounderstand,Reviewitfromthetechnicalviewpoint,Notinusableform,Hardforworkerstounderstand,Impracticalordoesnotleadtogoodresults,:Recurrence-preventioncountermeasure,No,No,No,Yes,Yes,Yes,1,2,3,4,5,6,7,8,9,94,WorkStandardsSpecifyingKeyPoints,Themodelstowhichtheyapplyareclearlyspecified.Theyusesketchestofacilitateunderstanding.Theyitemizethekeyworkpointsconcisely.Theyrecordthevaluesofimportantcharacteristicsclearly.Theyspecifycauses,notresults.,95,96,97,98,CHAPTER4,QualitySpecificationsandProcessCapability,4.1QualitySpecificationsandTolerances4.2ProcessCapability,99,4.1QualitySpecificationsandTolerancesThequalitywewanttoimproveandcontrolisconcretelyrepresentedbyfiguresshowinglength,hardness,percentageofdefectives,etc.Theycanbecalledqualitycharacteristics.Therearevariousfactorssuchaschemicalcomposition,diameters,workers,etc.whichcancausethedispersionofthefigures.Thus,therequirementofaqualitycharacteristicisgiven,byaspecificvaluewithitstolerance.Therearetwocategoriesofvalues:*Indiscrete(orcontinuous)valuesbasedonmeasurementseg.1yieldsofachemicalprocess2boardweight*Discrete(orenumerated)valuesbasedoncountingeg.1defectivearticlesorthenumberofdefects2blisters3cocklings,100,4.2ProcessCapability,Ifthequalitycharacteristicisassumedtofollowanormaldistribution,where3includes99.73percentofthepopulation,processcapabilityisdefinedinthefollowingway:Processcapability=3or6,Fig.4.1Normaldistribution,Processcapability,101,Fig.4.2Relationshipbetweencharacteristicdistributionsandtolerances,102,103,Incasewherexdeviatesfromthetargetvalue,thefollowingCpk,Fig.4.3CpkandCmk,104,Fig.4.4Theruleofdesignengineersandoperators,6m,105,RememberthatIfCp1,theprocessisnotcapabletoproduceproductsproperly.IfCp=1,27itemsoutof10,000itemsareoutoftolerances.IfCpAbout64itemsoutof1,000,000itemsareoutoftole-rances.Withthislowlevelofdefectiveproduction,theprocesscanbemanaged.,4,106,Fig.4.5JudgmentontheprocessbasedonthevalueofCp,107,CHAPTER5,HowtoImproveProcessCapability5.1DetectionofProblemsandtheSevenQCTools5.2HowtoCalculateProcessCapability:Histogram5.34MAnalysisofProcessCapability5.4HowtoImproveProcessCapability:CauseandEffectDiagram5.5CausesofDefectiveProductionandCountermeasures5.6HowtoDetectChangesofaCondition:ControlChart,108,Tab.5.1DetectionofProblemsand7QCTools,Paretodiagram,checksheet,graphHistogram,controlchart,checksheetcauseandeffectdiagram,stratification,checksheetScatterdiagramStratification,1.Findoutimportantpoints(problems)2.Graspthecurrentsituations3.Analyzecurrentsituations4.Checkthecorrelation5.Narrowtheproblems,7QCtools,Stepsofproblemdetection,5.1DetectionofProblemsandtheSevenQCTools,109,5.2.1DatahavedispersionWeliveinaworldofdispersion.Toknowthequalityofagivenamountofproducts,wemustuseaveragesanddispersion.Letsassumethatwetakefoursamplesofacertainpartfromaproductionlinedailyforonemonthandtakemeasurements.Therearetwowaysoflookingatthedataforthe100samples:1)Overallappearanceofthepartsasagroup.2)Changesinthedailymeasurementsoveronemonth.For(1),wecanconstructafrequencytableshowingthenumberofpartsforeachdimension.Then,ifwemakeahistogram,itwillbeeasytofindtheshape,thecentralvalue,andthemannerofdispersionofthesizemeasurement.For(2),inordertoseethechangesinthedatachronologically,controlchartsorgraphsgivingthedateverticallyandthedimensionshorizontallyareoftenused.,5.2HowtoCalculateProcessCapability:Histogram,110,5.2.2HowtoprepareahistogramThedatainTable5.2representthethickness(inmillimeters)of100metalblocksthatarepartsofopticalinstruments.Whenthereisasmuchdataasthe100sampleshere,itisdifficulttodeterminethedistributionofdatajustbylookingatthefigures.Inasituationsuchasthis,ifwearrangethedatainsequenceordersandshowhowmanyfiguresarealike(seeTab.5.2andthendrawupagraph,wecanperceivetheoveralltendency.Therearemanykindsofgraphs,butoneofthemostcommonisthehistogram(Fig.5.1).Letsexaminethemethodformakingahistogram.,111,(1)Countthedata.N=100(2)AsshowninTab.5.2,dividethedataroughlyintotengroups.RecordthelargestvaluesineachgroupasXLandthesmallestvaluesasXS(thisiscomparabletoalocalelection).Next,recordthelargestXLandthesmallestXSonthewhole(comparabletoanationalelection).XL=3.68,XS=3.30.,112,Table5.2Metalblockthickness(inmm),113,Fig.5.1Metalblockthickness,114,(3)Therange(R)ofallthedatais:R=XL-XS=0.38.Thisrangecanbedividedintoclassesandthenumberofdatabelongingtoeachclasscanbeinvestigated.Thenumberofclasses(thenumberofhistogrambars)canbedeterminedonthebasisofTable5.3.However,togettheroughnumberofclasses,takeK=10,anddivideitintotherange(R),(4)Thisclassinterval,h,whichwillbeusedasthehorizontalgraduationunitforthehistogram,shouldbeexpressedasamultipleofaninteger(thedatahavevaluesof,forexample,3.56,sotheunitsofmeasurementare0.01).Herehcouldbeconsideredequalto0.04,buttomakeclassdivisioneasierwewillputitat0.05.,h=0.038,K,XL-XS,10,0.38,115,Table5.3NumberofDataandnumberofclasses,116,(5)Classboundary,whichwemustdetermineinordertomakeabargraph,isdemarcatedstartingatoneendoftherange.Itistroublesomewhenactualsfallontheclassboundary.Toavoidthis,theboundaryunitistakenashalftheactualmeasurementunit.Inthiscaseitis0.005.Inotherwords,theboundariesthewidthofbarswillbe3.2753.325,3.3253.375,etc.Withcheckmarkssuchas/,/,/,/,/，/,etc,thedatawhichbelongtoeachclassareenumeratedasshowninTable5.4andafrequencytableismade.ThetotalshouldcorrespondtoNasoutlinedinstep(1)above.(Mistakesoftenoccurhere,sobecareful.),117,Table5.4Frequencytable,118,(6)Afterexaminingthefrequencytable,youcangetanideaoftheoverallpicture,butifitisindicatedonagraphitbecomesmuchclearer.Ongraphpaper,marktheclassboundarieshorizontallyandthefrequencyverticallylikethehistograminFig.5.1.IntheblankareaswritethebackgroundofthedataN,averagevalues,standarddeviation,etc.Ifthereisacompanyorindustrialstandarditisgoodtoshowthisalso.Inthisexample,thespecificationlimitsonthemetalblocksare3.283.60mm,sothishasbeenrecordedonthegraph.,119,5.2.3Howtouseahistogram,(1)Whatistheshapeofthedistribution?Example1.,Fig.5.2Comparisonofhistograms,120,Example2.Thishistogramhasacliff-likeappearanceontheleftedgeandthereforeseemsunusual.,Fig.5.3Cliff-likehistogram,121,Example3.Thishistogramlookedabnormal.,Fig.5.4Comb-likehistogram,122,Example4.Alloftheexamplessofarhavebeenforhistogramsshowingcontinuousdatavalues.However,figuresfornumbersofdefectiveparts,absentees,defects,etc(whatwecalldiscretevalues)canbeusedasdataforhistogramsinthesamewaythatcontinuousdataare.Fig.5.5showsthenumberofdailymachinefailuresinahistogrammadetoassistinpreventivemaintenance.Thedistributionisskewedtotheright.Withthiskindofdiscretevaluenumberofdefectiveparts,percentageofdefectiveparts,numberofaccidents,andnumberofdefectsthedistributionofthesedatawilloftenbefoundtoassumeanasymmetricalform.,Fig.5.5Failureoccurrencedistribution,123,(2)Whatistherelationshipwithspecifications?,Whatisthepercentageofout-of-specificationproducts?Doproductsfullymeetthespecifications?Istheaveragevalueattheexactcentreofthespecificationlimits?Letscompareahistogramwiththespecifications.InFig.5.1,wherethethicknessofmetalblocksisshown,weseethattheaveragevalueisroughlyinthecentreofthespecificationlimits,butthedispersionisgreaterthanthewidthofthespecificationlimits.Sothisdispersionmusteitherbereducedorthespecificationmustbere-examined.,124,Example5.AhistogramshowingtheloadcharacteristicsofamicroswitchisgiveninFig.5.6.Therearemanydefectivemicroswitches,andonthechartoverhalfofthedefectsareduetoloadcharacteristics.Forthisreason,thedataonloadcharacteristicstakenduringthemanufacturingprocesswerestudiedbyusingahistogram.Ascanbeseenclearly,theaveragevalueinclinestowardtheupperspecificationlimitandthedispersionisbroad.Theseproblemswereanalyzedthroughcontrolchartsandvariousstatisticalmethods;theresultwasareductioninthenumberofdefectives.Thisisagoodexampleforshowinghowahistogramcanbeusedtoperceivethestateofthemanufacturingprocess,tohelppeoplelearnwhattheproblemsare,andthustoimproveprocesscapabilityandreducedefects.Aprocesscapabilityindexisusedtodeterminewhetherthedispersionissufficientlysmallincomparisonwiththespecificationlimits.,125,Fig.5.6Histogramofloadcharacteristics,126,(3)Isthereaneedtochangethehistogram?,Whenthedataarestratifiedinaccordancewiththematerials,machines,shifts,workers,months,etc,thedistributionisprobablydifferentforeach.Inextremesituations,thehistogramdistributionmaytaketheshapeoftwopeaks(bi-modaldistribution).Inthecaseofbi-modaldistributionorbroaddispersion,thisdistributionoftenincludestwoormoredistributionswhichhavedifferentaverages.Example6.Asubcontractingcompanyprocessedsheetmetalpanelsforanelectricmachinemaker,withsheetmetalsuppliedbytheparentcompany.However,thepressedproductshadmanywrinklesandcracks,andtheywereoftennottherightsize.Therefore,hardnesstestswerecarriedoutonthesheets,andtheresultswereshowninahistogram.,127,Sincethedispersionwasbroad,investigationsweremade.Itwasdiscoveredthattheparentcompanyhadorderedsheetsfromtwosuppliers,AandB.Thesheetsfromthesesuppliersweretestedseparately,resultinginthestratifiedhistogramsinFig.5.7.Itisclearthatthereisadifferenceinthehardnessofthesheetsofthetwosuppliers.Whentwoseparategraphsaredrawnlikethis,suchdifferencestendtobecomeclear.,Fig.5.7HardnesshistogramsbycompaniesAandB,128,1)4M:Material,Machine,Man,Method2)5M:1)+Measurement3)5M+E:2)+Environment,5.34MAnalysisofProcessCapability,Man,Method,Material,Machine,Processcapability,129,5.4HowtoImproveProcessCapability:Cause-and-EffectDiagrams,5.4.1Whydoesqualitydispersionoccur?Itemsproducedinexactlythesamewaystillturnoutdifferently,asrevealedinhistograms.Whydoesthisdispersionoccur?Inalmosthalfofthecases,itisbecauseof:1)therawmaterials2)theworkmethods3)men4)machinesRawmaterialsdifferslightlyincompositionaccordingtothesourceofsupplyandtherearesizedifferenceswithinthepermittedlimits.Inthesamewayworkmethodsdifferslightlyalthoughtheyappeartobethesame.Menworkindifferentwaysunlesstheyfollowthestandardoperationprocedure.Machinesmayseemtobefunctioninginthesameway,butdispersioncanarisefromdifferencesintheaxlesleevefittingsorbecauseamachineisoperatingoptimallyonlypartofthetime.,130,Inthisway,whenthereisslightdispersioninrawmaterials,workmethodsandequipment,thesedifferencescanadduptoagreatdealofproductqualitydispersioninahistogram.Thecasualfactorsofdispersionaretherawmaterial,workmethodandequipment,etc;theseresultinthedispersionofquality.ThisrelationshipisshowninFig.5.8.Therelationshipbetweencauseandeffectisquiteclear.,131,Chemicalcomposition,diameters,workers,etc,whichcancausethedispersion,canbecalledfactors.Inordertoillustrateonadiagramtherelationshipbetweenthecauseandtheeffect,weneedtoknowthecausesandeffectsinconcreteforms.Therefore,theeffect=qualitycharacteristics,andcause=factors.Fig.5.8iscalleda“cause-and-effectdiagram”.Ingeneralpractice,thefactorsmustbewritteninmoredetailtomakethechartuseful.,Fig.5.8Cause-and-effectdiagram,Quality,Materials,Workmethods,Men,Equipment,Cause,Effect,132,5.4.2Makingcause-and-effectdiagrams(generalsteps)Thefactorsinvolvedinproblemswithqualityatfactoriesarealmostuncountable.Acause-and-effectdiagramisusefulinhelpingustosortoutthecausesofdispersionandorganizethemutualrelationships.Wewilloutlinethestepsformakingacause-and-effectdiagram.,133,Step1.Decidethequalitycharacteristic(wobbleduringmachinerotation).Thisissomethingwewouldwanttoimproveandcontrol.Inthiscaseitwasfoundthatmostofourfactorydefectiveswereduetowobbleduringrotating.Tostopthiswobblewemustfinditscauses.Step2.Writethequalitycharacteristicontherightside.Drawabroadarrowfromtheleftsidetotherightside(Fig.5.9),Wobble,Fig.5.9,134,Step3.Writethemainfactorswhichmaybecausingthewobble,directingabrancharrowtothemainarrow(seeFig.5.10).Itisrecommendedtogroupthemajorpossiblecausalfactorsofdispersionintosuchitemsasrawmaterials(materials),equipment(machinesortools),methodofwork(workers)andmeasuringmethod(inspection).Eachindividualgroupwillformabranch.,Wobble,Fig.5.10,Workers,Materials,Inspectio