Upload
others
View
10
Download
0
Embed Size (px)
Citation preview
LeanSixSigma:Training/CertificationBooksandResources
Page 1 of 15
Samples from: MINITAB BOOK
Quality and Six Sigma Tools using MINITAB Statistical Software: A complete Guide to Six Sigma DMAIC Tools using MINITAB®
Prof. Amar Sahay, Ph.D. One of the major objectives of this text is to teach quality, data analysis andstatisticaltoolsusedintheSixSigmaDMAIC(Define,Measure,Analyze,Improve,andControl)process.Thechaptersinthisbookprovideconcepts,understanding,andcomputerapplicationsofSixSigmaDMAICtools.ThestatisticaltoolsusedintheDMAICprocessarediscussedwithstep‐wiseMINITABcomputerapplications.The following are samples from the book randomly selected from differentchapters:
CHAPTER 4: Quality Tools: The Basic Tools and Seven New Tools of Quality
[Pareto Charts, Cause-and-effect Diagrams, Multi-vari Charts, Process maps, Check sheets, Run charts, control charts, Tree Diagrams, Prioritization matrix, Activity Network Diagrams and others)]
Note: The graphical tools described in this chapter are not all available in MINITAB. The tools available in MINITAB are indicated after their names.
ChapterHighlights
ThischapterdealswiththequalitytoolswidelyusedinSixSigmaandqualityimprovementprograms. The chapter includes the seven basic tools of quality, the seven new tools ofquality,andanothersetofusefultoolsinLeanSixSigmathatwereferto–“beyondthebasicandnewtoolsofquality.”TheobjectiveofthischapteristoenableyoutomasterthesetoolsofqualityandusethesetoolsindetectingandsolvingqualityproblemsinSixSigmaprojects.YouwillfindthesetoolstobeextremelyusefulindifferentphasesofSixSigma.Theyareeasyto learnandveryuseful indrawingmeaningfulconclusionsfromdata.Inthischapter,youwill learn the concepts, various applications, and computer instructions for these qualitytoolsofSixSigma.Thischapterwillenableyouto:1. Learnthesevengraphicaltools‐consideredthebasictoolsofquality.Theseare:
(i) ProcessMaps(ii) Checksheets(iii) Histograms(iv) ScatterDiagrams(v) RunCharts/ControlCharts(vi) Cause‐and‐Effect(Ishikawa)/FishboneDiagrams(vii) ParetoCharts/ParetoAnalysis
LeanSixSigma:Training/CertificationBooksandResources
Page 2 of 15
2. ConstructtheabovechartsusingMINITAB3. ApplythesequalitytoolsinSixSigmaprojects4. Learnthesevennewtoolsofqualityandtheirapplications:
(i) AffinityDiagram (ii) InterrelationshipDigraph(iii) TreeDiagram(iv) PrioritizingMatrices(v) MatrixDiagram(vi) ProcessDecisionProgramChart(vii) ActivityNetworkDiagram
5. Learn the construction and applications of some other quality tools including thestem‐and‐leafandboxplot.
6. Learna setofpowerful toolsbeyond thebasicandnew toolsofquality that includemulti‐varicharts,symmetryplots,andvariationsofscatterplots.
7. Learnhowtoconstructthesymmetryplots,andmulti‐varichartsusingMINITAB.
ChapterOutlineSevenBasicToolsofQuality
1. ProcessMaps2. CheckSheets3. Histograms (MINITAB)
UsingHistogramstoDetecttheShiftandtheVariationintheProcessEvaluatingProcessCapabilityUsingHistogram
4. ScatterPlots (MINITAB)5. RunChart/ControlCharts (MINITAB)
ConstructingaRunChartARunChartwithSubgroupSizeGreaterthan1ARunChartwithSubgroupSizeGreaterthan1RunChartShowingaStableProcess,aShift,andaTrend
6. Cause‐and‐EffectDiagramorFishboneDiagram (MINITAB)Cause‐and‐EffectDiagram(1)Cause‐and‐effectDiagram(2)CreatingotherTypesofCause‐and‐effectDiagram
7. ParetoChart (MINITAB)ASimpleParetoChartParetoChartwithCumulativePercentageParetoChartwithCumulativePercentagewhenDataareinOneColumnParetoChartbyVariable
LeanSixSigma:Training/CertificationBooksandResources
Page 3 of 15
SomeotherQualityTools:8. Stem‐and‐leafPlot (MINITAB)9. BoxPlot (MINITAB)
TheSevenNewToolsforQualityImprovement
(1) AffinityDiagram (2) InterrelationshipDigraph(3) TreeDiagram(4) PrioritizingMatrices(5) MatrixDiagram(6) ProcessDecisionProgramChart(7) ActivityNetworkDiagram
BeyondtheNewToolsofQuality
All the tools in this section are available in MINITAB.
1. BivariateData:MeasuringandDescribingTwoVariablesVariationsofScatterPlotsScatterplotswithHistogram,Box‐plotsandDotplotsScatterplotwithFittedLineorCurveScatterplotShowinganInverseRelationshipbetweenXandYScatterplotShowingaNonlinearRelationshipbetweenXandYScatterplotShowingaNonlinear(Cubic)RelationshipbetweenXandY
2. Multi‐VariCharts1. AMulti‐variChartforTwo‐factorDesign
MainEffectsandInteractionPlots2. AnotherMulti‐variChartforaTwo‐factorDesign
BoxPlots,MainEffectsPlot,andInteractionPlot3. Mult‐varichartforaThree‐factorDesign
Multi‐VariChart,BoxPlots,andMainEffectsPlot4. Multi‐variChartforaFour‐factorDesign
Multi‐VariChart,BoxPlots,MainEffectsandInteractionPlotsDetermineaMachine‐to‐Machine,Time‐to‐TimevariationPart‐to‐PartVariationinaProductionRunusingMulti‐variPlots
3. SymmetryPlotsChapterSummaryandApplications
LeanSixSigma:Training/CertificationBooksandResources
Page 4 of 15
SamplesandExamplesfromthisChapter
Figure5.1:ALogicalSequenceofSevenBasicToolsofQuality
Example5.1:ASIPOCProcessMapofOnlineOrderProcessing
Figure5.5:SymbolsandtheirMeaninginProcessMapping
LeanSixSigma:Training/CertificationBooksandResources
Page 5 of 15
Figure5.6(a):ACurrentStateValueStreamMapofaProductionandDistributionSystem
Figure5.6(a):ACurrentStateValueStreamMapofaProductionandDistributionSystem
HISTOGRAMOpentheworksheetPROCESSHIST.MTW
Fromthemainmenu,selectGraph&HistogramClickonWithOutlineandGroupsthenclickOKForGraph………RingDia:Run1ClickonScalethenclicktheReferenceLinestab::type4.955.05.05(withaspacebetweeneachvalue)ClickOKinalldialogboxes.
LeanSixSigma:Training/CertificationBooksandResources
Page 6 of 15
(i)Figure5.9(e)Theprocesshasshiftedtotheleft;productsoutofspecification,Figure5.9(f)Processshifttotheleft;morevariationcomparedto(e),Figure5.9(g)Processoutofcontrolandhaslargevariation,Figure5.9(h)Processwithincontrolbuthaslargevariation,Figure5.9(i)Processstableandclosetothetarget(desirable)
SCATTERPLOTWITHBOXPLOTSOpentheworksheetSALES&AD.MTW
SelectGraph&…..IntheMarginalPlotsdialogbox,selectWithBoxPlotsIntheMarginalPlot–WithBoxplotsdialogbox,selectthefollowing:DonotusetheHistogramsLabelstab.ClickOKinalldialogboxes
Repeatthestepsintheabovetabletoconstructascatterplotwithdotsplotsofxand
5.0405.0255.0104.9954.9804.9654.950
24
18
12
6
0
Ring Dia: Run 5 (e)
Fre
qu
ency
5.0554.95
5.0405.0225.0044.9864.9684.9504.932
30
20
10
0
Ring Dia: Run 6 (f)
Fre
qu
ency
5.0554.95
5.085.065.045.025.004.984.96
20
15
10
5
0
Ring Dia: Run 7 (g)
Fre
qu
ency
5.0554.95
5.0437E+005.0254E+005.0072E+004.9889E+004.9707E+004.9525E+00
16
12
8
4
0
Ring Dia: Run 8 (h)
Fre
qu
ency
5.0554.95
Histogram of Ring Dia: Run 5 Histogram of Ring Dia: Run 6
Histogram of Ring Dia: Run 7 Histogram of Ring Dia: Run 8
5.0445.0315.0185.0054.9924.9794.9664.953
14
12
10
8
6
4
2
0
Ring Dia: Run 9
Fre
quen
cy
5.0554.95
Histogram of Ring Dia: Run 9
LeanSixSigma:Training/CertificationBooksandResources
Page 7 of 15
yvariables.TheplotswillbesimilartoFigures5.16and5.17.
100908070605040
120
100
80
60
40
Sales ($)
Prof
it (
$)Scatter Plot with Box Plot of X and Y Variables
Figure5.16:ScatterplotwithBoxPlotsofxandyVariables
100908070605040
120
100
80
60
40
Sales ($)
Prof
it (
$)
Scatter Plot with Dotplots of X and Y Variables
Figure5.17:ScatterplotwithDotPlotsofxandy
VariablesTable5.15RUNCHARTOpentheworksheet RUNCHART2.MTW
Fromthemainmenu,selectStat&QualityTools&….UnderDataarearrangedasclickthecirclenexttoSinglecolumnand::ClicktheOptionstabandtypeatitleforyourplotClickOK
Observ at ion
Proc
ess
2
65605550454035302520151051
10
9
8
7
6
5
4
3
N umber o f ru n s abo u t med ian :
0.99996
18E xp ec ted n u mb er o f ru n s: 33.96970Lo n g est ru n ab o u t med ian : 12A pp ro x P -Valu e fo r C lu ster in g : 0.00004A pp ro x P -Valu e fo r M ixtu res:
N u mb er o f ru n s u p o r d o w n :
0.57822
43E xp ec ted n u mber o f ru n s: 43.66667Lo n gest run u p o r d o w n : 4A p p ro x P -Valu e fo r T ren d s: 0.42178A p p ro x P -Valu e fo r O sc illatio n :
A R un Chart S how ing a Trend
Example5.18:AnalyzingaControlChart‐ControllingtheShaftDiameter
Table5.20:TestsforAssignableCauses
TestResultsforXbarChartofn1,...,n5TEST 1. One point more than 3.00 standard deviations from center line. Test Failed at points: 14, 38, 39 TEST 5. 2 out of 3 points more than 2 standard deviations from center
LeanSixSigma:Training/CertificationBooksandResources
Page 8 of 15
line (on one side of CL).Test Failed at points: 37, 38, 39, 40 TEST 6. 4 out of 5 points more than 1 standard deviation from center line (on one side of CL). Test Failed at points: 14, 38, 39, 40 * WARNING * If graph is updated with new data, the results above may no longer be correct.
37332925211713951
75.04
75.03
75.02
75.01
Sam ple
Sam
ple
Mea
n
__X=75.01861
UCL=75.03195
LCL=75.00528
37332925211713951
0.048
0.036
0.024
0.012
0.000
Sample
Sam
ple
Ran
ge
_R=0.02312
UCL=0.04890
LCL=0
5
1
1
5
1
Variab les Contro l Chart w ith Additional Sam ples
Figure5.31:ControlChartsshowingOutofControlConditions
Figure5.34:ACause‐and‐EffectDiagramofProductionProblemsusingMINITAB
P roblem
Environment
M easurement
M ethods
M ateria l
M achines
P ersonnel
S tress and fatigueHealth
P ersonal problem sLack of com m unication
Lack of m otivationP oor tools
P oor work instructionsIm proper work
Lack of experienceInadequate education
Hydraulic problem sP rev m aintenance
Exessive downtim eP oor m aintenance
Aautom ationP oor tooling
T echnologyIncapable M achines
W orn out m achines
C entralizedQuality check
External flawsInternal flawsVvariation in
S upplier relationshipM any suppliers
S upplier problemP oor quality m aterial
Im prove m ethods
W ork design problem
T echnology
No autom ation
P oor skills
Instructions
P rocess planing
W ork m ethods
F atigue
Lack of training
Observer errors
W rong gaging
Gage problem
Equipm ent
C alibration
W ork conditions
Distractions
Noise
Heat
Dirt
Dust
Hum idity
T em perature
Majo r Causes o f P roduction Problem
LeanSixSigma:Training/CertificationBooksandResources
Page 9 of 15
Figure 5.36: A Cause-and-Effect Diagram of Cost of Poor Quality
COPQ
Apprais al
Pre ve ntion
Exte rnal
Inte rnal
Dow ngrading products
Cost of y ie ld losses
Dow ntime
Failure analysis
Retest
Repair
Rew ork
Scrap
Loss of future businessLoss of m arket share
Custom erLoss of goodw ill
Paperw ork processingCorrective action
Settlem ent costsLegal serv ices and
Cost of testingRecalls
Custom er com pla insReturned
Warranty charges
Cost of sk illed qualityVariability analyses
Building supplier re lationsSpecial equipm ents to control
Cost of qulity tra iningCost of quality planning
Im roving designIm prove Manufacturing eng
Im prove Quality eng
Cost of fie ld audits
Cost of product audits
Cost of m ainta ining test and
Cost of inspection and testing
Cost of maintaining test
Cost of m ainta ing m aterials
Inspection Supervisors
Costs of Poor Q uality (CO PQ )
Table5.23ASIMPLEPARETOOpentheworksheetPARETOCHART.MTWCHARTFromthemainmenu,selectStat&QualityTools&ParetoChart
Defectorattributedatain:selectC1orFailureCauseFrequenciesin:C2orCountIntheCombineremainingdefectsintoonecategoryafterthis::ChecktheboxDonotchartcumulativepercentageNext,typeatitleforyourplotandclickOKinalltheboxes
TheParetochartasshowninfigureswillbedisplayedinthegraphics
LeanSixSigma:Training/CertificationBooksandResources
Page 10 of 15
Count 1284 55 40 33 25 21 17 15Percent 4.027.8 18.2 13.2 10.9 8.3 7.0 5.6 5.0Cum % 100.027.8 46.0 59.3 70.2 78.5 85.4 91.1 96.0
Causes of Failure
Drawing
Erro
rs
Surfa
ce Fi
nish E
rrors
In-u
se Fa
ilures
Mechan
ical E
rrors
Measu
remen
t Erro
rs
Inter
nal F
laws
Mach ini
ng E
rrors
Damag
ed P
arts
Inco
rrect
Dimen
sions
90
80
70
60
50
40
30
20
10
0
Coun
t
Pareto Chart of Defects in Machined Parts
Figure5.37:ParetoChartofDefectDatawithNoCumulativePointsPlotted
Count 1284 55 40 33 25 21 17 15Percent 4.027.8 18.2 13.2 10.9 8.3 7.0 5.6 5.0Cum % 100.027.8 46.0 59.3 70.2 78.5 85.4 91.1 96.0
Causes of Failure
Draw
ing Erro
rs
Surfa
ce Fi
nish E
rrors
In-u
se Fa
ilure
s
Mecha
nica l
Erro
rs
Measu
remen
t Erro
rs
Inte
rnal
Flaws
Machin
ing E
rrors
Damag
ed Pa
rts
Inco
rrect
Dimen
sions
300
250
200
150
100
50
0
100
80
60
40
20
0
Coun
t
Perc
ent
Pareto Chart of Defects in Machined Parts
Figure5.38:ParetoChartofDefectDatawithCumulativePointsPlotted
Ty p e s o f Fa ilu r e
Coun
t
Dr aw in g
E rror s
I n- us
e F ai l
u res
S urfa
ce F
in is h E
rrors
I nter
n al F l aw
s
D amag
e d P a rts
Me as
ur em
ent E
rr ors
I nco
rrec t
D imen
si on
Ma ch
in in g Erro
rs
1 2 09 06 03 00
D r awin g E
rror s
I n-u s e
Fail
ures
S urfa c e
Fin is h
Erro
rs
Inte
rna l F
la ws
D a ma g ed P
ar ts
M e asu rem
ent E
r rors
I nc o
r rec t
D ime ns
i on
Mac
h in in g Erro
rs
1 2 09 06 03 0
0
S h if t = D a y S h if t = M o rn in g
S h if t = N ig h t
T y p es o f F a ilu r e
I n ter n a l F law sS u r fac e F in ish E r r o r sI n - u se F a ilu r esD r aw in g E r r o r s
M ac h in in g E r r o r sI n c o r r ec t D im en sio nM easu r em en t E r r o r sD am ag ed P ar ts
P a r e to C ha r t o f D e fe c ts in M a c hine d P a r ts
L
Summa
TypChart/
ProcessM
Checkshe
Histogram
ScatterD
RunChar
eanSixS
aryandAp
peof/GraphMaps
s
eets
m
iagrams
b
rt
Sigma:Tr
pplications
Process maservice procoperationth
Check sheetchecksheets
Detemeasdetecthep
Scatter dibetweentw
……………
raining/C
Pag
sofBasicT
Descript
pping is flocess. The chatfacilitates
s are data gsisto……
rmining thesured on oncting procesprocesseithe
agrams ino…….
Certificati
ge 11 of 15
ToolsofQ
ion/Applicat
ow chartinghart providcommunica
gathering too
e shape andne characteris problemsertothelefto
nvestigate
tionBook
5
Quality
tion
g a productes a modeltionaboutth
ols. The pur
d location oistic. Also uincluding aorright….
the relati
ksandRes
Va
tion orl of anhe….
pose of
of dataused forshift in
ionship birel
Co
OnploUn
sources
NumberofariablesPlot
ivariatelationship
ontinued…
nevariableotted:nivariatedata
ftted
a
L
Cause‐an(IshikawaboneDiag
ParetoCh
Stem‐and
Box‐plot
Stem-and-leaf of No1000) N = 65Leaf Unit = 1.0
3 1 0248 2 0567817 3 00445727 4 012445(13) 5 2344425 6 02345616 7 13566910 8 1223684 9 352 10 35
7570
Boxplot of Box Plot
eanSixS
nd‐Effecta)/Fish‐grams
A
hart
T
d‐leafPlot
Ap
All theadescribe
o. of Defects (out of
788956669
445567889668898
908580
Sigma:Tr
A cause‐anestablishing
Thechartshofthevitalfe
A simplepresentingd
Plotoffivem
abovegrapheonecharact
raining/C
Pag
nd‐Effect diatherelations
hows(indescewversusth
and usefuldata.Thestem
measures:the
sexcept theteristicatat
Certificati
ge 12 of 15
agram isship……
cendingordeetrivialman
way form‐and‐leafp
eminimum,
eCause‐and‐time,andthe
tionBook
5
a useful t
er)thecontrny.…..
summarizinlotdisplays
…..
Effectdiagraerefore,descr
ksandRes
tool in
ribution On
ng and…..
Un
amareusedribe……
sources
nevariable…
nivariatedata
tosummari
….
a
izeor
LeanSixSigma:Training/CertificationBooksandResources
Page 13 of 15
(1)Multi‐variPlot
Themulti‐vari plots of data in Table 5.40 are shown in Figures 5.67 and 5.68. Thedifferenceinappearancebetweenthetwoplotsisduetotheorderofselectionofthetwofactors.Whenyouselect thecommandsequenceStat&QualityTools&Multi‐VariChart,youmustselecttheresponsevariableandthenfactor1andfactor2.Forourexample,theresponsevariableisstrengthandthetwofactorsarealloytypeandthickness.Ifyouselectalloytypeforfactor1andthicknessforfactor2,….
Solidlinesconnectthemeansoffactor1levels(ateachleveloffactor2). Adottedlineconnectsthemeansoffactor2levels.
Both the plots above show that alloy type 2 and thickness 2 has the maximumstrength.….
Thickness
Stre
ngth
4321
740
735
730
725
720
715
710
AlloyType
123
Multi-Vari Chart for Strength by Alloy Type - Thickness
Figure5.67:AMulti‐VariChartforStrengthbyAlloyTypeandThickness
Alloy Type
Stre
ngth
321
740
735
730
725
720
715
710
Thickness1234
Multi-Vari Chart for Strength by Thickness - Alloy Type
Figure5.68:AMulti‐VariChartforStrengthbyThicknessandAlloyType
Thickness
Alloy Type
321
740
730
720
710
4321
740
730
720
710
Thickness
34
12
Alloy
3
Type12
Interaction Plot (data means) for Strength
Figure5.72:InteractionPlotofStrengthbyThicknessandStrengthbyAlloyType
L
Summa
A
InD
M
T
eanSixS
aryofSeve
Thesevusedasthebasisimple vuseful itheseto
AffinityDiag
nterrelationDigraph
MatrixDiagr
TreeDiagram
Sigma:Tr
enNewTo
ennewtoolsdecisionmakicseventoolvisual toolsn solving unols.
gram
nship
ram
m
raining/C
Pag
oolsforQu
sforqualitykingtoolsfosofquality(to understanstructured
Affinitydiag
Theinterrelbetweendif::.
Thematrixthe relationrelationship::
The tree didifferentlev
:
:
:
Certificati
ge 14 of 15
uality
areapowerfrmanagingp(discussedeaand differentproblems. T
gramisavisu
lationshipdifferentissues
diagram isnship amongp
agram is usvelsofdetail.
tionBook
5
fulsetoftooprojectsthatarlierinthist processes.The table be
ualtoolthat
igraphisusesrelatingto
a tool usedg two or m
sed to break.Itstarts
ksandRes
olsthathavetinvolveteamschapter),thThese tools
elow provide
gatherslarg
edtoidentifyaproblem.…
to identify,more variable
k down broa
sources
beensuccesm.Combinedhesetoolsprs are particues a summa
eamounts…
ytherelation….
analyze, andes. It define
ad categories
sfullydwithovideularlyary of
….
nships
d rates the
s into
L
P
PP
AD
eanSixS
PrioritizingM
ProcessDeciProgramCha
ActivityNetwDiagram
Sigma:Tr
Matrix
isionart
work
raining/C
Pag
Aprioritizatcriteriaand
:
:
:
The Procescontingency:::
The Activit(ProgramEvtheCriticalP:::
Certificati
ge 15 of 15
tiongridisumultiplealte
ss Decisionyplanning.T
ty NetworkvaluationanPathMethod
tionBook
5
usedtomakeernatives.Th
Program CThistoolcan
Diagram isndReviewTed(CPM)
ksandRes
edecisionsihistoolprior
Chart (PDPCbeusedto
s also knowechnique)net
sources
nvolvingmuritizes
C) is a too
wn as thetwork,andC
ultiple
ol for
PERTCPM‐