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6
OverviewSix
Sigma:A
DefinitionApplied
to
GEGE
Quality
InitiativeWhy
This
Approach?Origin
of
Six
SigmaThe
“Breakthrough
Strategy”Arriving
at
SigmaSix
Sigma
StructureKey
Concepts
&
ToolsA
Practical
ExampleAn
OverviewNot
a
lot
of
Details!!6
Overview“Six
Sigma”If
we
can’t
express
what
we
know
in
the
form
of
numbers,we
really
don’t
know
much
about
it.If
we
don’t
know
much
about
it,
we
can’t
control
it.If
we
can’t
control
it,
we
are
at
the
mercy
ofchance.Mikel
J.
HarryPresident
&CEOSix
Sigma
Academy,
Inc.“...will
bring
GE
to
a
whole
new
level
of
quality
in
a
fraction
of
thetime
it
would
have
taken
to
climb
the
learning
curve
on
our
own.”John
F.
Welch,
Jr.1995
GE
Annual
ReportA
Rigorous
Method
for
Measuring
&
Controlling
Our
Quality6
OverviewWhat
Does
“Sigma”
Mean?Sigma
is
a
Measure
of
the
Consistency
of
a
ProcessIt
(
is
Also
the
18th
Letter
in
the
Greek
Alphabet!Why
Does
GE
Need
A
Quality
Initiative?GE
Raising
The
BarNew
Goal
to
be
“Best
in
the
World”
vs.
#1
or
#2Customers
are
Expecting
More,
we
Must
Deliver“Ship-and-fix”
Approach
no
Longer
Tolerated
in
theMarketAim
to
Speed
Past
Traditional
Competitors
in
5
YearsGoal
Consistent
with
Reduced
Total
CostsWe
Must
Acknowledge
Our
VulnerabilitiesPoor
Quality
That
Impacts
CustomersProblems
withNPIToo
High
Internal
CostsWe
Need
a
Major
Initiative
to
Move
FromWhere
we
Are
to
Where
we
Want
to
be6
Overview6
OverviewWhy
Does
GE
Need
A
Quality
Initiative?Cost
of
Failure
(%
of
Sales)40%35%30%25%20%15%10%5%Defects
per
Million3.4233621066,807308,537500,000Sigma654321Estimated
Cost
of
Failure
in
US
Industry
is
15%
of
Sales;
TakingGE
From
a
3
to
a
6
Company
Will
Save
~
$10.5
Billion
perYear!Why
“Six
Sigma”?
Proven
Successful
in
“Quality-Demanding”
Industries
e.g.,Motorola,
Texas
Instruments
(many
process
steps
in
series)Proven
Method
to
ReduceCostsHighly
Quantitative
Method
–
Science
and
Logic
Instead
of
GutFeelIncludes
Manufacturing
&
Service
(close
to
customer)
and
Provides
Bridgeto
Design
for
Quality
ConceptsHas
Support
and
Commitment
of
Top
ManagementItWorks!!!6
OverviewSigma3
Spelling1.5
Misspelled
Wordsper
Page
in
a
BookMoney$2.7
Million
Indebtednessper
$1
Billion
in
AssetsTime3
1/2
Monthsper
Century4
1
MisspelledWordper
30
Pagesin
a
Book$63,000
Indebtednessper
$1
Billion
in
Assets2
1/2
Daysper
Century5
1
Misspelled
Word
ina
set
ofEncyclopedias$570
Indebtednessper
$1
Billion
in
Assets30
Minutesper
Century6
1
Misspelled
Word
in
allof
the
Books
in
a
SmallLibrary$2
Indebtednessper
$1
Billion
in
Assets6Secondsper
Century6
is
Several
Orders
of
Magnitude
Better
Than
3
!!!Sigma:
A
Measure
of
Quality6
OverviewWhere
Does
“Six
Sigma”
Come
From?Mikel
J.
Harry
one
of
the
Original
ArchitectsPreviously
Headed
Quality
Function
at
ABB
and
MotorolaNow
President/CEO
of
Six
Sigma
Academy
in
Phoenix,
ArizonaHas
Consulted
for
Texas
Instruments,
Allied
Signal
(and
others)Currently
Retained
by
GE
to
Teach
the
Implementation, Deployment
and
Application
of
Six
Sigma
Concepts
&
ToolsLearning
from
Those
Who
Have
had
SuccessWith
6
Will
Accelerate
its
Implementation
atGE6
OverviewSo...What
is
Six
Sigma?A
Measurement
SystemAProblem-SolvingApproachA
Disciplined
Change
Process“THE
SIX
SIGMA
BREAKTHROUGH
STRATEGY”MeasureAnalyzeImproveControl6
OverviewMeasurement
SystemHowDo
WeArrive
atSigma?Measuring&
Eliminating
Defects
isthe
“Core”of
SixIdentify
theCTQs“Critical
to
Quality”CharacteristicsortheCustomerRequirements
for
aProduct
orServiceLookforDefects
inProducts
or
ServicesCountDefects
or
failures
tomeetCTQrequirements
inall
process
stepsDefineDefect
OpportunitiesAny
step
in
theprocess
where
aDefectcouldoccurin
aCTQArrive
atDPMOConvertDPMOtoDefects
Per
MillionOpportunities
2PPM308,537SigmaUse
theSIGMATABLE366,80746,210523363.4Defects
perMillion
ofOpportunitySigmaLevel6
Overview2345308,53766,8076,210233PPMSIGMALEVELMILLIONOPPORTUNITYMeasurement
SystemSomeSigma
“Benchmarks”DEFECTSper
6
3.4AverageCompanyin3
toIRSTaxAdviceBestCompaniesAirlineSafetyGEAverageCompanyRestaurant
BillsAirline
BaggageDoctor’s
Prescription6
OverviewMeasurementSystemA
Graphic/Quantitative
Perspective
on
VariationManyData
Sets
Havea
NormalorBellShapeNumber
ofPeopleArrivingat
CRDTime7:007:15
7:30
7:45
8:00
8:15
8:30
8:45
9:00AverageValue9:156
OverviewProblemSolvingApproachOff-TargetCenterProcessReduceSpreadXXXXXXXXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXX
XXXXUnpredictableXOn-Target6
Helps
usIdentify
and
ReduceVARIATIONdueto:Insufficient
Process
CapabilityUnstable
Parts&
Materials-
InadequateDesignMarginTargetUSLLSLTargetUSLLSLTarget“Lower
SpecificationLimit”
LSL
USL
“Upper
SpecificationLimit”LessVariation
MeansFewer
Defects&Higher
ProcessCenterProcessReduceSpreadOff-TargetUnpredictableOn-TargetDefects6
OverviewProblemSolvingApproach6
OverviewProblemSolvingApproachKeyComponents
of“BREAKTHROUGH
STRATEGY”A
Mix
ofConcepts
and
ToolsMeasureAnalyzeImproveControlIdentifyCTQ&CTP(Critical
toProcess)VariablesDoProcessMappingDevelopandValidateMeasurementSystemsBenchmark
andBaselineProcessesCalculateYieldandSigmaTargetOpportunitiesandEstablishImprovementGoalsUseofPareto
Chart&
Fishbone
DiagramsUseDesign
ofExperimentsIsolatethe“Vital
Few”fromthe“TrivialMany”Sourcesof
VariationTestforImprovementinCenteringUseofBrainstormingandAction
WorkoutsSetupControlMechanismsMonitorProcessVariationMaintain“InControl”ProcessesUseofControlChartsandProceduresWillAlso
IntegratewithNPIProcess6
OverviewDisciplinedChange
ProcessA
New
SetofQUALITYMEASURESCustomerSatisfactionCostofPoorQualitySupplierQualityInternalPerformanceDesign
forManufacturabilityWillApplyto
Manufacturing
&Non-ManufacturingProcessesand
be
Tracked&
Reportedby
Each
Busin6
OverviewStructureQuality
CouncilMembers:
Labs
&
Functions“Pipeline”
&
BB
Project
PrioritiesTraining
&
CertificationMeasurements
&
RewardsCommunicationsChampionsLeadership:
Overall
InitiativeProject
FundingHR:
Training
&
RewardsBlack
BeltsLead
6
Project
Teams“Measure/Analyze”“Improve/Control”O(jiān)ut
with
BusinessesHere
at
CRDMaster
Black
BeltsTeach6
Mentor
Black
BeltsMonitor
BB
ProjectsWork
“Pipeline”
ProjectsA
ResourcePoolTeam
MembersLearn/Use
6
ToolsWork
on
BBProjectsPart
of
The
JobOut
with
Businesses6
Projects
with
the
GEBusinesses
Tabulationof
GE
SixSigmaResultsBenefit
Target&
UpdateCurrent
benefits
level
@10.865
MMQPIDloading
:Carryoverfrom1999:CompletedProjects
2000
:3.313Active
Projects2000:3.285Total:10.865
MM4.059Key
Concepts
&Tools6
Overview6
OverviewChanging
FocusFromOutput
toProcessYDependentOutputEffectSymptomMonitorX1.
.
.
XNIndependentInput-ProcessCauseProblemControlIdentifying
andFixing
Root
CausesWillHelpus
Obtainthe
Desired
OutputY
=f
(X)Process
Capability6
OverviewTime
1Time
2Time
3Time
4SustainedCapabilityof
theProcess(longterm)USLTInherent
Capabilityof
theProcess(short
term)LSLTargetOverTime,a
“Typical”
ProcessWillShift
andDrift
byApproximately
1.5
6
Overview“ShortTermCentered”versus
“Long
Term
ShifteLSLUSLTProcessCapabilitySHORTTERMSix
SigmaCentered.001ppm.001ppm+6
LSLUSLT3.4ppmLONGTERMSixSigmaShifted1.5
ProcessCapabilityHigherDefectYieldinLongTermProcessCapabilitythanShortTermProcessCapability-6
4.5
1.5
6
OverviewTyingitAllTogethershiftCDAB0.51.01.52.02.5
123456CONTROLPOORGOODPOOR
GOODTECHNOLOGYProblemCouldbeControl,TechnologyorBothABCDGood
Control/Poor
TechnologyPoor
Control/PoorTechnologyPoor
Control/Good
TechnologyWORLD
CLASS!!!shortterm6
OverviewShortTermCapability
(Cp)ShortTermCapabilityRatioCp=USL
-
LSL6
ExampleUSL
=
3.0
LSL
= -3.0
6
3.0
-(-3.0
Cp=Cp=
1LSLUSL2.5
0.5
3.0
T
TargetProcessMeanA3
ProcessThePotentialPerformanceofaProcess,ifitWereonTarg6
OverviewLongTermCapability(Cpk)Cpk
=
Cp
-LongTermCapabilityRatioExampleCp=Target
==
-0.5
1(previouschart)0
0
-
(-0.5
3
Cpk
=
1-Cpk
=
0.83Off-TargetPenalty
Target
-
μ3
ThePotentialPerformanceofaProcess,CorrectedforanOff-TargetMeanLSLUSL2.5
0.5
3.0
T
TargetProcessMeanA3
Process6
OverviewZ
=Z-ScaleofMeasureAUnitofMeasureEquivalenttotheNumberofStandardDeviationsthataValueisAwayfromtheTargetValue-3.0-0.5
03.0Z
-ValuesUSLLSL2.5
0.5
3.0
=Process
MeanZT
TargetA
3
ProcessTheDefinitionsofYieldFinal
TestProcess(Process
4)PassProcess
3Process
1Process
2100(Units
Tested)65708291Yield
1Yield
2Yield
3Loss
19Rejects5Loss
312Loss
29FirstTime
Yield(Yft)Yield
ExclusiveofRework=Units
PassedUnits
Tested=6570=
0.93= (Yield1)=(Yield2)(Yield
3).
..
.82917082(
)
(91100)
()
(
)6570=
0.65Rolled
Thruput
Yield(Yrt)Probabilityof1/n(Yrt)==
(0.65)1/4Normalized
Yield(Ynm)AverageYield=
0.89(n:Total
NumberofProcesses)6
OverviewZeroDefectsof
AllProcesses6
OverviewThe
Impact
of
ComplexityProcess
Mean
Centered
on
Each
Operation
ProcessMeanShifted1.5
RolledYield1.000.900.800.700.600.500.400.300.200.100.001
10
100
1,000 10,000
100.000
1,000,000Number
of
Operations1
10100
1,000 10,000
100.000
1,000,000Number
of
OperationsRolledYield1.000.900.800.700.600.500.400.300.200.100.00As
the
Number
ofOperationsIncreases,
aHighRolled
YieldRequires
aHigh
forEachOperation5
4
3
6
6
5
4
3
atEachOperation6
Overviewp
(x)Baselining
&Benchmarking
anExisting
ProcessBenchmarkDefectsBaselineEntitlementBenchmarkA
World-Class
PerformanceEntitlementAchievable
Performance
Giventhe
Investments
Already
MadeBaselineThe
Current
Level
of
PerformanceBaselining=CurrentProcess/Benchmarking=UltimateGSomeBasic
6
-RelatedTools6
OverviewScatterDiagramOverSlept
CarWouldNotStartWeatherFamilyProblemsOtherPareto
DiagramFrequencyofOccurenceReasonsforBeing
Late
for
WorkArrivalTimeat
WorkTimeAlarmWentOffMaterialsPeopleThe
HistogramControl
Charts-6
OverviewSomeBasic6
-Related
ToolsThe
Fishbone
DiagramMeasurements Methods
TechnologyStatementCause
&
EffectBeingLateforWorkPlotof
Daily
Arrival
Time7:00Average
Value7:15
7:30
7:45
8:00
8:15
8:30
8:45
9:00
9:15TimeNumberofPeopleArrivingat
CRD6
OverviewLCLUCL
=
Upper
Control
LimitUCLSomeBasic
6
-RelatedToolsX
Bar
Chart
Range
ChartROut
of
Control
ConditionLCLUCLXLCL
=
Lower
Control
LimitX
=
MeanR
=
Average
RangeMonitorsChangesinAverageor
VariationOver
TimeDesign
of
Experiments6
OverviewSCREENINGOPTIMIZATIONCHARACTERIZATIONForExperimentsInvolving
aLargeNumber
of
FactorsUseful
inIsolatingthe“Vital
Few
“fromthe“TrivialMany”ForExperimentsInvolving
aRelativelySmall
NumberofFactorsUseful
WhenStudyingRelativelyUncomplicatedEffects&
InteractionsForExperimentsInvolvingOnly2or3FactorsUseful
WhenStudyingHighly
ComplicatedEffects&
RelationshipsDOEis
MoreEffective
Than
Testing
One
Factor
ata
T6
OverviewUsing
the
“One
Factor
ata
Time”ApproachThe
GoalReduce
Commute
toWorkto
15
Minutes(withoutworking
an
abnormal
work
schedule)The
VariablesTime
of
Departure
fromHome
&
Route
Takento
WorkThe
ApproachTry
3
Potential
Routes
at
CurrentDeparture
Time
(7:45),
Selectthe
Best
&
Vary
theDepartureTime
‘til
we
get
to
15Minutes7:30
7:45
8:00
8:15TimeofDeparture3217:15RouteCombinationSelectedTheResultUseRoute2andLeaveat7:15
toReach
Goal6
OverviewUsing“D“
esign
ofExperiments”(DOE)DOE(i)
BetterAccountsforInteractiveVariables
Missedby““One
FactorataTime””,and(ii)EfficientlySearchesfo“r“Sweet
Spo”t”in
ParameterSpaceTheVariablesTime
of
DeparturefromHome
&RouteTakentoWorkThe
ApproachVary
time
of
Departure
andRoute
Simultaneously,
in
aSystematic
FashionTheResultABetterCombinationAllowing15MoreMinutesofSleep!!!ActualCommuting
TimeAverages(minutes)3217:15
7:30
7:45
8:00
8:15Time
of
DepartureRoute172023211915182019161215212018OriginalConclusionBestCombination“Sweet
Spot”Reduce
Commute
toWorkto
15
Minutes(withoutworking
an
abnormal
work
schedule)The
GoalA
Practical
Example(The“C“
ookbook”)6
Overview6
and
BakingBreadFLOURYEASTUsinga
12StepProcess6
OverviewThe
“BETTER
BREAD”
CompanyStep
1Selecting
“Critical
to
Quality”
(CTQs
or
Y)Whatis
Important
totheCustomer?RiseTextureSmellFreshnessTasteY=
Taste!!6
OverviewMeasureStep
2Defining
Performance
Standards
for
CTQs
or
Y6
OverviewMeasureHow
CouldWe
MeasureTaste
(Y)?Panelof
TastersRating
Systemof
1to
10Target:
AverageRating
at8Desired:
NoIndividualRatings(“defects”)
Below
78910TargetDefectsWorstY=
12
34
567BestButIsthistheRightSystem?6
OverviewStep
3Validating
the
Measurement
System
for
YHow
CouldWe
Approach
This?Blindfolded
Panel
RatesSeveral
Loaf
SamplesPut
“Repeat”
PiecesfromSameLoafinDifferentSamplesConsistentRatings*onPieces
fromSameLoaf=
“Repeatability”ConsistentRatings*onSamples
AcrossthePanel=“R“
eproducibility”“Repeatability”
&“R“
eproducibility””Suggest
ValidMeasurementApproachPanelMemberLoaf1Loaf2Loaf3A589B491C492D898E482F591G892*Within
±OneTasteUnitMeasure6
OverviewAnalyzeStep
4Establish
Product
Capability
for
Y
(Taste)Thisisa3
Process!7Defects(ratingsbelow7)24Ratings(fromourpanel)=
.292292,000Defectsper1,ooo,oooLoavesOR76543217
8
9
101
2
3
4
5
6Rating#
ofRatings64321
143Defects
<7Target
=
8HowDoWeApproachThis?BakeSeveralLoavesUnde“r“Norma”l”
ConditionsHaveTasterPanelAgainDotheRatingAverageRatingis7.43
x
10
+
4
x
9
+
6
x
8
+
4
x
7
+
3
x
6
+
2
x
5
+
1
x
4
+
1
x
31
+
1
+
2
+
3
+
4
+
6
+
4
+
3ButVariationistooGreatfora6
Process6
OverviewAnalyzeStep
5Define
Improvement
Objectives
for
Y
(Taste)HowdoweDefineImprovement?BenchmarktheCompetitionFocusonDefects(i.e.tasterating<7)DetermineWhatisan“A“
cceptableSigmaLevel”SetImprovementObjectivesAccordinglyMaybea
5
Process
WillSuffice!1,000,000-100,000-...
...
...
...
...
...
...
...
...
..10,000-..
...
...
...
...
...
...
...
...
...1,000-.
...
...
...
...
...
...
...
...
...
.100-..
...
...
...
...
...
...
...
...
...1-23456710-.
...
...
...
...
.B..
e...s.t..
...
...
.“BETTERBREAD””BakingProcessCompetitorRangeforImprovementDefectsPerMillionSigmaScaleFreihoferWONDERPepperidge
FarmSunbeam6
OverviewStep
6Identify
Sources
of
Variation
in
Y
(Taste)HowdoweDetermine
thePotentialSourcesofVariation(Xs)?Have
theChefsBrainstormSome
LikelyOnes
Might
be:-AmountofSaltUsed-BrandofFlour-BakingTime-BakingTemperature-BrandofYeastYEASTFLOURMultipleSources:Chefs,Suppliers,ControlsAnalyze6
OverviewStep
7Screen
Potential
Causes
of
Variation
(Xs)HowdoweScreen
forCausesofVariation
(Xs)?DesignanExperimentUseDifferent
SourcesofPotentialVariationHave
PanelRatetheBreadUsedintheExperimentResults
Leadtothe“VitalFew”CausesYEASTFLOURSourceConclusionNegligibleMajorCauseNegligibleMajorCauseNegligibleFocusonThe““Vital
Few”Improve6
OverviewStep
8Discover
Variable
Relationships
Between
“Vital
Few”
(Xs)
and
YHowdoweFindtheRelationship
Betweenthe
“VitalFew””(Xs)and
Taste
(Y)?Conduct
aMoreDetailedExperimentFocus:OvenTemperaturefrom
325to375and3BrandsofFlourRUN#TEMPBRAND1325A2325B3325C4350A5350B6
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