Download - Samples MINITAB Book Chapter 4 · [Pareto Charts, Cause-and-effect Diagrams, Multi-vari Charts, Process maps, Check sheets, Run charts, control charts, Tree Diagrams, Prioritization

LeanSixSigma:Training/CertificationBooksandResources

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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


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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


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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


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SamplesandExamplesfromthisChapter

Figure5.1:ALogicalSequenceofSevenBasicToolsofQuality

Example5.1:ASIPOCProcessMapofOnlineOrderProcessing

Figure5.5:SymbolsandtheirMeaninginProcessMapping


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Figure5.6(a):ACurrentStateValueStreamMapofaProductionandDistributionSystem

Figure5.6(a):ACurrentStateValueStreamMapofaProductionandDistributionSystem

HISTOGRAMOpentheworksheetPROCESSHIST.MTW

Fromthemainmenu,selectGraph&HistogramClickonWithOutlineandGroupsthenclickOKForGraph………RingDia:Run1ClickonScalethenclicktheReferenceLinestab::type4.955.05.05(withaspacebetweeneachvalue)ClickOKinalldialogboxes.


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(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

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Histogram of Ring Dia: Run 7 Histogram of Ring Dia: Run 8

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yvariables.TheplotswillbesimilartoFigures5.16and5.17.

100908070605040

120

100

80

60

40

Sales ($)

Prof

it (

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Figure5.16:ScatterplotwithBoxPlotsofxandyVariables

100908070605040

120

100

80

60

40

Sales ($)

Prof

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Scatter Plot with Dotplots of X and Y Variables

Figure5.17:ScatterplotwithDotPlotsofxandy

VariablesTable5.15RUNCHARTOpentheworksheet RUNCHART2.MTW

Fromthemainmenu,selectStat&QualityTools&….UnderDataarearrangedasclickthecirclenexttoSinglecolumnand::ClicktheOptionstabandtypeatitleforyourplotClickOK

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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


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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

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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

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C entralizedQuality check

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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

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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


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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

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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

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300

250

200

150

100

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100

80

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Pareto Chart of Defects in Machined Parts

Figure5.38:ParetoChartofDefectDatawithCumulativePointsPlotted

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(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.….

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Figure5.67:AMulti‐VariChartforStrengthbyAlloyTypeandThickness

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Multi-Vari Chart for Strength by Thickness - Alloy Type

Figure5.68:AMulti‐VariChartforStrengthbyThicknessandAlloyType

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720

710

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720

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Figure5.72:InteractionPlotofStrengthbyThicknessandStrengthbyAlloyType

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