S標(biāo)準(zhǔn)培訓(xùn)教材

6

Overview

SixSigma:-ADefinition-AppliedtoGE-GEQualityInitiative-WhyThisApproach?-OriginofSixSigma-The“BreakthroughStrategy”-ArrivingatSigmaSixSigmaStructureKeyConcepts&ToolsAPracticalExampleAnOverviewNotalotofDetails!!6OverviewSixSigma:AnOver6

Overview

“SixSigma”

Ifwecan’texpresswhatweknowintheformofnumbers,wereallydon’tknowmuchaboutit.Ifwedon’tknowmuchaboutit,wecan’tcontrolit.Ifwecan’tcontrolit,weareatthemercyofchance.MikelJ.HarryPresident&CEOSixSigmaAcademy,Inc.ARigorousMethodforMeasuring&ControllingOurQuality“...willbringGEtoawholenewlevelofqualityinafractionofthe

timeitwouldhavetakentoclimbthelearningcurveonourown.”JohnF.Welch,Jr.1995GEAnnualReport6Overview “SixSigma”6

Overview

WhatDoes“Sigma”Mean?

SigmaisaMeasureoftheConsistencyofaProcessIt(

isAlsothe18thLetterintheGreekAlphabet!6Overview WhatDoes“WhyDoesGENeedAQualityInitiative?GERaisingTheBarNewGoaltobe“BestintheWorld”vs.#1or#2CustomersareExpectingMore,weMustDeliver“Ship-and-fix”ApproachnoLongerToleratedintheMarketAimtoSpeedPastTraditionalCompetitorsin5YearsGoalConsistentwithReducedTotalCostsWeMustAcknowledgeOurVulnerabilitiesPoorQualityThatImpactsCustomersProblemswithNPITooHighInternalCosts6

Overview

WeNeedaMajorInitiativetoMoveFromWhereweAretoWhereweWanttobeWhyDoesGENeedAQualityIni6

Overview

WhyDoesGENeedAQualityInitiative?40%35%30%25%20%10%15%5%CostofFailure(%ofSales)DefectsperMillion3.4233621066,807308,537500,000Sigma654321

EstimatedCostofFailureinUSIndustryis15%ofSales;TakingGEFroma3

toa6

CompanyWillSave~$10.5BillionperYear!6Overview WhyDoesGEWhy“SixSigma”?ProvenSuccessfulin“Quality-Demanding”Industriese.g.,Motorola,TexasInstruments(manyprocessstepsinseries)ProvenMethodtoReduceCostsHighlyQuantitativeMethod–ScienceandLogicInsteadofGutFeelIncludesManufacturing&Service(closetocustomer)andProvidesBridgetoDesignforQualityConceptsHasSupportandCommitmentofTopManagementItWorks!!!Why“SixSigma”?ProvenSuccess6

Overview

Sigma3

4

5

6

SpellingMoneyTime1.5

MisspelledWordsperPageinaBook1

MisspelledWordper30PagesinaBook1

MisspelledWordinasetofEncyclopedias1

MisspelledWordinalloftheBooksinaSmallLibrary$2.7MillionIndebtednessper$1BillioninAssets$570

Indebtednessper$1BillioninAssets$63,000

Indebtednessper$1BillioninAssets$2

Indebtednessper$1BillioninAssets31/2MonthsperCentury21/2DaysperCentury30MinutesperCentury6SecondsperCentury6

isSeveralOrdersofMagnitudeBetterThan3

!!!Sigma:AMeasureofQuality6Overview Sigma3456

Overview

WhereDoes“SixSigma”ComeFrom?

MikelJ.HarryoneoftheOriginalArchitectsPreviouslyHeadedQualityFunctionatABBandMotorola

NowPresident/CEOofSixSigmaAcademyinPhoenix,ArizonaHasConsultedforTexasInstruments,AlliedSignal(andothers)CurrentlyRetainedbyGEtoTeachtheImplementation,DeploymentandApplicationofSixSigmaConcepts&Tools

LearningfromThoseWhoHavehadSuccessWith6

WillAccelerateitsImplementationatGE6Overview WhereDoes6

Overview

So...WhatisSixSigma?

AMeasurementSystem

AProblem-SolvingApproach

ADisciplinedChangeProcess“THESIXSIGMABREAKTHROUGHSTRATEGY”MeasureAnalyzeImproveControl6Overview So...Whati6

Overview

How

DoWeArriveatSigma?Measuring&EliminatingDefectsisthe“Core”ofSixSigmaMeasurementSystemIdentifytheCTQsLookforDefectsinProductsorServices

“CriticaltoQuality”CharacteristicsortheCustomerRequirementsforaProductorService

CountDefectsorfailurestomeetCTQ

requirementsinallprocessstepsDefineDefectOpportunities

AnystepintheprocesswhereaDefectcouldoccurinaCTQ

ArriveatDPMO

UsetheSIGMATABLEConvertDPMOtoSigma

DefectsPerMillionOpportunities23456308,53766,8076,2102333.4PPM

DefectsperMillionofOpportunity

SigmaLevel6Overview HowDoWeA6

Overview

MeasurementSystem23456308,53766,8076,2102333.4PPM

SIGMALEVEL

DEFECTSperMILLIONOPPORTUNITY

IRSTaxAdviceBestCompaniesAirlineSafetyAverageCompanyGEAirlineBaggageDoctor’sPrescriptionRestaurantBills

AverageCompanyin3

to4

RangeSomeSigma“Benchmarks”6Overview Measurement6

Overview

MeasurementSystemAGraphic/QuantitativePerspectiveonVariationAverageValueManyDataSetsHaveaNormalorBellShapeNumberofPeopleArrivingatCRDTime7:007:157:307:458:008:158:308:459:009:156Overview Measurement6

Overview

ProblemSolvingApproachCenterProcessReduceSpreadXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXOff-TargetUnpredictableOn-Target

6

HelpsusIdentifyandReduceVARIATIONdueto:-InsufficientProcessCapability-UnstableParts&Materials-InadequateDesignMargin6Overview ProblemSolTargetUSLLSLTargetUSLLSLTargetUSLLSLCenterProcessReduceSpreadOff-TargetUnpredictableOn-TargetDefects6

Overview

ProblemSolvingApproach“LowerSpecificationLimit”“UpperSpecificationLimit”LessVariationMeansFewerDefects&HigherProcessYields

TargetUSLLSLTargetUSLLSLTarget6

Overview

ProblemSolvingApproachKeyComponentsof“BREAKTHROUGHSTRATEGY”MeasureAnalyzeImproveControl

IdentifyCTQ&CTP(CriticaltoProcess)VariablesDoProcessMappingDevelopandValidateMeasurementSystems

BenchmarkandBaselineProcessesCalculateYieldandSigmaTargetOpportunitiesandEstablish

ImprovementGoalsUseofParetoChart&FishboneDiagrams

UseDesignofExperimentsIsolatethe“VitalFew”fromthe“TrivialMany”SourcesofVariationTestforImprovementinCenteringUseofBrainstorming

andActionWorkouts

SetupControlMechanismsMonitorProcessVariationMaintain“InControl”ProcessesUseofControlChartsand

ProceduresAMixofConceptsandToolsWillAlsoIntegratewithNPIProcess6Overview ProblemSol6

Overview

DisciplinedChangeProcessANewSetofQUALITYMEASURES

CustomerSatisfactionCostofPoorQualitySupplierQualityInternalPerformanceDesignforManufacturability

WillApplytoManufacturing&Non-ManufacturingProcessesandbeTracked&ReportedbyEachBusiness6Overview Disciplined6

Overview

StructureQualityCouncil

Members:Labs&Functions“Pipeline”&BBProjectPrioritiesTraining&CertificationMeasurements&RewardsCommunicationsChampions

Leadership:OverallInitiativeProjectFundingHR:Training&RewardsBlackBelts

Lead6

ProjectTeams“Measure/Analyze”“Improve/Control”O(jiān)utwithBusinessesHereatCRDMasterBlackBelts

Teach6

MentorBlackBeltsMonitorBBProjectsWork“Pipeline”ProjectsAResourcePoolTeamMembers

Learn/Use6

ToolsWorkonBBProjectsPartofTheJobOutwithBusinesses6

ProjectswiththeGEBusinesses

6Overview StructureQuS標(biāo)準(zhǔn)培訓(xùn)教材S標(biāo)準(zhǔn)培訓(xùn)教材

TabulationofGESixSigmaResultsTabulationofGESixSigmaResBenefitTarget&UpdateCurrentbenefitslevel@10.865MMQPIDloading:

Carryoverfrom1999: 4.059CompletedProjects2000: 3.313ActiveProjects2000:

3.285Total: 10.865MMBenefitTarget&UpdateCurrentS標(biāo)準(zhǔn)培訓(xùn)教材

KeyConcepts&Tools6

Overview

KeyConcepts&Tools6Overv6

Overview

ChangingFocusFromOutputtoProcess

Y

Dependent

Output

Effect

Symptom

Monitor

X1...XN

Independent

Input-Process

Cause

Problem

Control

IdentifyingandFixingRootCausesWillHelpusObtaintheDesiredOutputf(X)Y=6Overview ChangingFoProcessCapability6

Overview

SustainedCapabilityoftheProcess(longterm)USLTTime1Time2Time3Time4InherentCapabilityoftheProcess(shortterm)LSLTargetOverTime,a“Typical”ProcessWillShiftandDriftbyApproximately1.5

ProcessCapability6Overview 6

Overview

“ShortTermCentered”versus“LongTermShifted”SixSigmaCenteredLSLUSLT

ProcessCapabilitySHORTTERM.001ppm.001ppm+6

LONGTERMLSLUSLT3.4ppmSixSigmaShifted1.5

ProcessCapabilityHigherDefectYieldinLongTermProcessCapabilitythanShortTermProcessCapability-6

4.5

1.5

6Overview “ShortTerm6

Overview

TyingitAllTogethershiftCDAB0.51.01.52.02.5123456CONTROLPOORGOODTECHNOLOGYPOORGOODABCD

GoodControl/PoorTechnologyPoorControl/PoorTechnologyPoorControl/GoodTechnology

WORLDCLASS!!!

shortterm

ProblemCouldbeControl,TechnologyorBoth6Overview TyingitAl6

Overview

ShortTermCapabilityShortTermCapabilityRatio(Cp)Cp=

LSL-6

USL

ExampleUSLLSL3.0

==-3.0

6

3.0

-(-3.0

Cp=Cp=1LSLUSL2.5

0.5

3.0

ProcessMean

TTargetA3

Process

ThePotentialPerformanceofaProcess,ifitWereonTarget6Overview ShortTerm6

Overview

LongTermCapability

(Cpk)CpCpk=LongTermCapabilityRatioExampleCp=1(previouschart)Target=-0.5

=0

Cpk1-(-0.5

-0

3

=Cpk=0.83-Off-TargetPenalty

Target-3

ThePotentialPerformanceofaProcess,CorrectedforanOff-TargetMeanLSLUSL2.5

0.5

3.0

ProcessMean

TTargetA3

Process6Overview LongTermC6

Overview

Z-ScaleofMeasureZ

=AUnitofMeasureEquivalenttotheNumberofStandardDeviationsthataValueisAwayfromtheTargetValue-3.0-0.53.0Z-Values

USLLSL2.5

0.5

3.0

=ProcessMean

Z

TTarget0A3

Process6Overview Z-ScaleoTheDefinitionsofYieldFinalTestProcess(Process4)PassProcess3Process1Process2100(UnitsTested)65708291Yield1Yield2Yield3

Loss1

Loss3Rejects

Loss299125

FirstTimeYield(Yft)=UnitsPassedUnitsTested=6570=0.93

RolledThruputYield(Yrt)=(Yield1)(Yield2)(Yield3)....=91826570(((())))=0.65100917082

NormalizedYield(Ynm)==1/n(Yrt)(0.65)1/4=0.89(n:TotalNumberofProcesses)6

Overview

YieldExclusiveofReworkProbabilityofZeroDefectsAverageYieldofAllProcessesTheDefinitionsofYieldFinal6

Overview

TheImpactofComplexityTheImpactofComplexityRolledRolled

Yield

YieldNumberofOperationsNumberofOperations1.001.000.900.900.800.800.700.700.600.600.500.500.400.400.300.300.200.200.100.100.000.001101001,00010,000100.0001,000,0001101001,00010,000100.0001,000,000ProcessMeanCenteredonEachOperationProcessMeanCenteredonEachOperation1101001,00010,000100.0001,000,0001101001,00010,000100.0001,000,000RolledRolled

Yield

YieldNumberofOperationsNumberofOperations1.001.000.900.900.800.800.700.700.600.600.500.500.400.400.300.300.200.200.100.100.000.00

AstheNumberofOperationsIncreases,aHighRolledYieldRequiresaHigh

forEachOperation5

4

3

6

6

5

4

3

ProcessMeanShifted1.5

atEachOperation6Overview TheImpact6

Overview

Baselining&BenchmarkinganExistingProcessp(x)DefectsBenchmarkBaseline

Entitlement

BenchmarkAWorld-ClassPerformance

EntitlementAchievablePerformanceGiventheInvestmentsAlreadyMade

BaselineTheCurrentLevelofPerformanceBaselining=CurrentProcess/Benchmarking=UltimateGoal6Overview BaseliningSomeBasic6

-RelatedTools6

Overview

ScatterDiagram

OverSlept

CarWouldNotStartWeather

FamilyProblemsOtherParetoDiagramFrequencyofOccurenceReasonsforBeingLateforWorkArrivalTimeatWorkTimeAlarmWentOffSomeBasic6-RelatedTools6MaterialsPeopleTheHistogramControlCharts6

Overview

SomeBasic6

-RelatedToolsTheFishboneDiagramMeasurementsMethodsTechnologyStatementCause&EffectBeingLateforWorkPlotofDailyArrivalTime9:157:007:157:307:458:008:158:308:459:00AverageValueNumberofPeopleArrivingatCRDTimeMaterialsPeopleTheHistogramCo6

Overview

LCLUCLRangeChartROutofControlConditionLCLXUCLXBarChartSomeBasic6

-RelatedToolsLCL=LowerControlLimitUCL=UpperControlLimitX=MeanR=AverageRangeMonitorsChangesinAverageorVariationOverTime6Overview LCLUCLRangeDesignofExperiments6

Overview

SCREENINGOPTIMIZATIONCHARACTERIZATION

ForExperimentsInvolvingaLarge

NumberofFactorsUsefulinIsolatingthe“VitalFew“fromthe“TrivialMany”

ForExperimentsInvolvingaRelatively

SmallNumberofFactorsUsefulWhenStudyingRelativelyUncomplicated

Effects&Interactions

ForExperimentsInvolvingOnly2or3FactorsUsefulWhenStudying

HighlyComplicatedEffects&RelationshipsDOEisMoreEffectiveThanTestingOneFactorataTimeDesignofExperiments6Overvi6

Overview

Usingthe“OneFactorataTime”Approach

ReduceCommutetoWorkto15Minutes(withoutworkinganabnormalworkschedule)

TheGoalTheVariables

TimeofDeparturefromHome&RouteTakentoWorkTheApproach

Try3PotentialRoutesatCurrentDepartureTime(7:45),SelecttheBest&VarytheDepartureTime‘tilwegetto15MinutesTimeofDeparture3217:157:307:458:008:15RouteCombinationSelectedTheResultUseRoute2andLeaveat7:15toReachGoal6Overview Usingthe“6

Overview

Using“DesignofExperiments”(DOE)TimeofDepartureDOE(i)BetterAccountsforInteractiveVariablesMissedby“OneFactorataTime”,and(ii)EfficientlySearchesfor“SweetSpot”inParameterSpaceTheVariables

TimeofDeparturefromHome&RouteTakentoWorkTheApproach

VarytimeofDepartureandRouteSimultaneously,inaSystematicFashionTheResultABetterCombinationAllowing15MoreMinutesofSleep!!!ActualCommutingTimeAverages

(minutes)3217:157:307:458:008:15Route172023211915182019161215212018

OriginalConclusion

BestCombination“SweetSpot”

ReduceCommutetoWorkto15Minutes(withoutworkinganabnormalworkschedule)

TheGoal6Overview Using“Desi

APracticalExample

(The“Cookbook”)6

Overview

APracticalExample6Overvi6

andBakingBreadYEAST

FLOURUsinga12StepProcess6

Overview

The“BETTERBREAD”Company6andBakingBreadYEASTFStep1Selecting“CriticaltoQuality”(CTQsorY)WhatisImportanttotheCustomer?RiseTextureSmellFreshnessTasteY=Taste!!6

Overview

MeasureStep1Selecting“CriticalStep2DefiningPerformanceStandardsforCTQsorY6

Overview

HowCouldWeMeasureTaste(Y)?PanelofTastersRatingSystemof1to10Target:AverageRatingat8Desired:NoIndividualRatings(“defects”)Below7Y=12345678910TargetDefectsWorstBestButIsthistheRightSystem?MeasureStep2DefiningPerformanc6

Overview

Step3ValidatingtheMeasurementSystemforYHowCouldWeApproachThis?BlindfoldedPanelRatesSeveralLoafSamplesPut“Repeat”PiecesfromSameLoafinDifferentSamplesConsistentRatings*onPiecesfromSameLoaf=“Repeatability”ConsistentRatings*onSamplesAcrossthePanel=“Reproducibility”

“Repeatability”&“Reproducibility”SuggestValidMeasurementApproach

PanelMember

Loaf1

Loaf2

Loaf3

A5

8

9B 4

9

1C 4

9

2D 8

9

8E 4

8

2F 5

9

1G 8

9

2*Within

OneTasteUnitMeasure6Overview Step36

Overview

Step4EstablishProductCapabilityforY(Taste)Thisisa3

Process!7Defects(ratingsbelow7)24Ratings(fromourpanel)=.292292,000Defectsper1,ooo,oooLoavesOR765432112345678910#ofRatingsRating64321143Defects<7Target=8AnalyzeHowDoWeApproachThis?BakeSeveralLoavesUnder“Normal”ConditionsHaveTasterPanelAgainDotheRatingAverageRatingis7.4

ButVariationistooGreatfora6

Process3x10+4x9+6x8+4x7+3x6+2x5+1x4+1x31+1+2+3+4+6+4+36Overview Step46

Overview

Step5DefineImprovementObjectivesforY(Taste)HowdoweDefineImprovement?BenchmarktheCompetitionFocusonDefects(i.e.tasterating<7)DetermineWhatisan“AcceptableSigmaLevel”SetImprovementObjectivesAccordinglyMaybea5

ProcessWillSuffice!1,000,000-100,000-.............................10,000-.............................1,000-.............................100-.............................10-.............................1-234567“BETTERBREAD”

BakingProcess

BestCompetitor

RangeforImprovement

DefectsPerMillionSigmaScale

Freihofer

WONDER

PepperidgeFarm

SunbeamAnalyze6Overview Step56

Overview

Step6IdentifySourcesofVariationinY(Taste)HowdoweDeterminethePotentialSourcesofVariation(Xs)?HavetheChefsBrainstormSomeLikelyOnesMightbe:-AmountofSaltUsed-BrandofFlour-BakingTime-BakingTemperature-BrandofYeast

YEAST

FLOURMultipleSources:Chefs,Suppliers,ControlsAnalyze6Overview Step66

Overview

Step7ScreenPotentialCausesofVariation(Xs)HowdoweScreenforCausesofVariation(Xs)?DesignanExperimentUseDifferentSourcesofPotentialVariationHavePanelRatetheBreadUsedintheExperimentResultsLeadtothe“VitalFew”CausesYEAST

FLOURSourceConclusionNegligibleMajorCauseNegligibleMajorCauseNegligibleFocusonThe“VitalFew”Improve6Overview Step76

Overview

Step8DiscoverVariableRelationshipsBetween“VitalFew”(Xs)andYHowdoweFindtheRelationshipBetweenthe“VitalFew”(Xs)andTaste(Y)?ConductaMoreDetailedExperiment

Focus:OvenTemperaturefrom325to375and3BrandsofFlourRUN#TEMPBRAND1325A2325B3