Samples MINITAB Book Chapter 4 · [Pareto Charts, Cause-and-effect Diagrams, Multi-vari Charts,...

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Lean Six Sigma: Training/Certification Books and Resources 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 and statistical tools used in the Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process. The chapters in this book provide concepts, understanding, and computer applications of Six Sigma DMAIC tools. The statistical tools used in the DMAIC process are discussed with step‐wise MINITAB computer applications. The following are samples from the book randomly selected from different chapters: 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. Chapter Highlights This chapter deals with the quality tools widely used in Six Sigma and quality improvement programs. The chapter includes the seven basic tools of quality, the seven new tools of quality, and another set of useful tools in Lean Six Sigma that we refer to –“beyond the basic and new tools of quality.” The objective of this chapter is to enable you to master these tools of quality and use these tools in detecting and solving quality problems in Six Sigma projects. You will find these tools to be extremely useful in different phases of Six Sigma. They are easy to learn and very useful in drawing meaningful conclusions from data. In this chapter, you will learn the concepts, various applications, and computer instructions for these quality tools of Six Sigma. This chapter will enable you to: 1. Learn the seven graphical tools considered the basic tools of quality. These are: (i) Process Maps (ii) Check sheets (iii) Histograms (iv) Scatter Diagrams (v) Run Charts/Control Charts (vi) CauseandEffect (Ishikawa)/Fishbone Diagrams (vii) Pareto Charts/Pareto Analysis
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Transcript of Samples MINITAB Book Chapter 4 · [Pareto Charts, Cause-and-effect Diagrams, Multi-vari Charts,...

  • 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.

    ChapterHighlightsThischapterdealswiththequalitytoolswidelyusedinSixSigmaandqualityimprovementprograms. 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

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    5.0437E+005.0254E+005.0072E+004.9889E+004.9707E+004.9525E+00

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    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

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    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 ($)

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    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

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    65605550454035302520151051

    10

    9

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    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

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    UCL=75.03195

    LCL=75.00528

    37332925211713951

    0.048

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    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

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    P ersonnel

    S tress and fatigueHealth

    P ersonal problem sLack of com m unication

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    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 ethodsW ork design problem

    T echnologyNo autom ation

    P oor skillsInstructions

    P rocess planing W ork m ethods

    F atigueLack of training

    Observer errorsW rong gaging

    Gage problemEquipm ent

    C alibration

    W ork conditionsDistractions

    NoiseHeat

    DirtDust

    Hum idityT 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

    Draw

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    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

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    Figure5.38:ParetoChartofDefectDatawithCumulativePointsPlotted

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  • 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.….

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    Figure5.67:AMulti‐VariChartforStrengthbyAlloyTypeandThickness

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    Figure5.68:AMulti‐VariChartforStrengthbyThicknessandAlloyType

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    Figure5.72:InteractionPlotofStrengthbyThicknessandStrengthbyAlloyType

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