統(tǒng)計(jì)質(zhì)量控制：英文版

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作　者：	（美）Eugene L.Grant，（美）Richard S.Leavenworth著
出版社：	清華大學(xué)出版社
叢編項(xiàng)：	國外大學(xué)優(yōu)秀教材工業(yè)工程系列
標(biāo)　簽：	工業(yè)經(jīng)濟(jì)理論工業(yè) 行業(yè)經(jīng)濟(jì) 經(jīng)濟(jì)

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ISBN：	9787900641984	出版時(shí)間：	2002-06-01	包裝：	平裝
開本：	23cm＋光盤1片	頁數(shù)：	784	字?jǐn)?shù)：

內(nèi)容簡介

　　本書是工業(yè)工程專業(yè)統(tǒng)計(jì)質(zhì)量控制的經(jīng)典教材，已經(jīng)出到第7版。與前幾版的做法一樣，對上一版的改進(jìn)一是體現(xiàn)在基本原理的表述上，二是使各種主題更接近時(shí)代。本書簡要概述了質(zhì)量控制的意義和歷史發(fā)展過程，重點(diǎn)講解了各種類型的控制圖和抽樣檢驗(yàn)體系和過程，而對概率和統(tǒng)計(jì)知識的介紹非常直觀和簡單。作者認(rèn)為這種方式對工程和商業(yè)領(lǐng)域的學(xué)生非常重要，這是因?yàn)殡m然他們的工業(yè)經(jīng)驗(yàn)不多，但是他們將來可能要對操作員和檢驗(yàn)員進(jìn)行統(tǒng)計(jì)質(zhì)量控制的課程培訓(xùn)。本書的第4部分頗具特色，主要涉及質(zhì)量決策的經(jīng)濟(jì)因素、質(zhì)量管理和問題解決的模式等內(nèi)容。隨著經(jīng)濟(jì)的發(fā)展和學(xué)科的交叉，工業(yè)工程所涉獵的主題已不僅僅局限于制造業(yè)。本書作者之一尤金·L·格蘭特（Eugege·L·Grant）曾是美國斯坦福大學(xué)的工程經(jīng)濟(jì)學(xué)教授，作為該領(lǐng)域的權(quán)威，他的視野較之一般專攻制造領(lǐng)域的教授更為寬廣，所以該書作為工業(yè)工程專業(yè)統(tǒng)計(jì)質(zhì)量控制的教材非常合適。

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圖書目錄

LISTOFEXAMPLES
PREFACE
PARTONEINTRODUCTION
1IntroductionandOverview
1.1TheMeaningofQuality/1.2TheFocusofThisBook/1.3TheControl-ChartViewpoint/1.4ScientificSampling/1.5UseofExamples/1.6MeaningsandUsageoftheWordsDefectiveandDefect/1.7ManyEconomyStudiesCallfortheViewpointofStatisticalQualityControl/1.8StatisticalQualityControlMayHaveUsefulBy-Products/1.9ReasonsfortheUseoftheAdjectiveStatistical/1.10FourDifferentLevelsofUnderstandingStatisticalQualityControl/1.11NonmanufacturingApplicationsofStatisticalQualityControlTechniques/1.12SomeTopicsCoveredinPartFourOfThisBook

PARTTWOSTATISTICALPROCESSCONTROL
2DirectionsforSimpleXandRCharts
2.1SettingUpandOperatingControlChartsforXandR/2.2ChecklistofNecessaryStepsinUsingXandRCharts/2.3SomeCommentsonComputerSoftwareforStatisticalProcessControl/Problems

3WhytheControlChartWorks;SomeStatisticalConcepts
3.1TheNeedforUnderstandingStatisticalPrinciples/3.2DescriptionofPatternsofVariation/3.3GraphicRepresentationofaFrequencyDistribution/3.4AveragesandMeasuresofDispersion/3.5SamplingStatisticsandUniverseParameters/3.6TheNormalCurve/3.7OtherFrequencyCurves/3.8WhattheAverageandStandardDeviationofaSetofNumbersReallyTell/Problems

4WhytheControlChartWorks;SomeExamples
4.1TheUseofControlChartstoJudgeWhetherorNotaConstantSystemofChanceCausesIsPresent/4.2UseoftheControlChartinInterpretationofaFrequencyDistribution/4.3ContributionoftheControlCharttoEliminationofCausesofTrouble/4.4ChangesinUniverseAverage/4.5ShiftinUniverseDispersionwithNoChangeinUniverseAverage/4.6ChangesinUniverseAverageandUniverseDispersion/4.7APossibleViewoftheQuestionAnsweredbyaControlChart/4.8NonproductApplicationsOfControlChartsforVariables/4.9ConflictingExpressionsfortheStandardDeviationofaSetofNumbers/Problems

5SomeFundamentalsoftheTheoryofProbability
5.1ProbabilityHasaMathematicalMeaning/5.2ModernConceptsofProbabilityTheory/5.3SomeTheoremsoftheTheoryofProbability/5.4InfiniteandFiniteUniverses/5.5TheHypergeometricProbabilityDistribution/5.6TheBinomialasaProbabilityDistribution/5.7ThePoissonLawasaProbabilityDistribution/5.8TheNormalDistribution/5.9DecidingontheMethodtoBeUsedforCalculatingProbabilitiesinIndustrialSamplingProblems/5.10RelationshipbetweenControlChartsandCertainOtherStatisticalTechniques/5.11RandomVariables/5.12PointEstimatesandEstimators/5.13TheProblemofSelectingaParametertoDescribeUniverseDispersionandofChoosinganEstimatorforThatParameter/5.14SamplingfromaNormalDistribution/5.15TheoryofExtremeRuns/Problems

6TheControlChartforFractionRejected
6.1SomePracticalLimitationsofControlChartsforVariables/6.2ControlChartsforAttributes/6.3TheControlChartforFractionRejected/6.4TheBinomialasaProbabilityLawThatDeterminestheFluctuationsofFractionRejected/6.5ControlLimitsforthepChart/6.6ProblemsIntroducedbyVariableSubgroupSize/6.7ChecklistofNecessaryStepsinConnectionwithControlChartforFractionRejected/6.8SensitivityofthepChart/6.9NonproductApplicationsOfpandupCharts/6.1OpChartsAreNotSuitableforAllDataonFractionRejected/Problems

7TheControlChartforNonconformities
7.1ThePlaceofthecChartinStatisticalProcessControl/7.2DistinctionbetweenaNonconformingArticleandaNonconformity/7.3LimitsforthecChartAreBasedonthePoissonDistribution/7.4TheCombinationofPoissonDistributions/7.5ConditionsFavorabletotheEconomicUseoftheControlChartforNonconformities/7.6AdaptationsOfthecCharttoVariationsin1heAreaofOpportunityforaNonconformity/7.7ProbabilityLimitsforcanduCharts/7.8TheuChartforNonconformitiesperMultipleUnits/7.9ListingIndividualNonconformitiesontheFormContainingacoruChart/7.10TheIntroductionofaControlChartMayMotivateQualityImprovement/7.11ClassificationofNonconformitiesandTheirWeighting/7.12QChartsforQualityScoresandDChartsforDemeritClassifications/7.13Useof3cforApproximateCalculationofControlLimitsinSituationsInvolvingtheBinomialDistribution/7.14ApplicabilityOfcChartTechniqueinFieldsOtherThanStatisticalProcessControl/Problems

8RationalSubgrouping
8.1TheInformationGivenbytheControlChartDependsontheBasisUsedforSelectionofSubgroups/8.2TwoSchemesInvolvingOrderofProductionasaBasisforSubgrouping/8.3QuestionAddressedbytheShewhartControlChart/8.4SourcesofVariability/8.5OrderofProductionIsNotAlwaysaSufficientBasisforSubgrouping/8.6NeedforDiscriminationintheSelectionofSubgroups/8.7IdentificationonaControlChartofDifferentSourcesofSubgroups/8.8Precision,ReproducibilityandAccuracyofMethodsofMeasurement/8.9RelationshipbetweentheVariabilityofMeasuredValuesandthePrecisionoftheMethodofMeasurement/Problems

9StatisticalAnalysisofProcessCapabilityandforProcessImprovement
9.1ProcessCapabilityasaSteptowardProcessImprovement/9.2ProcessCapabilityandPerformanceIndexes/9.3QualitybyDesign:DesignandInspectionSpecifications/9.4StatisticalMethodsMayHelpinSettingBetterSpecificationLimits/9.5SomeCommonMethodsofInterpretationOfaPilotRunasaBasisforSettingTolerances/9.6TwoStatisticalTheoremsofGreatImportanceintheInterrelationshipofTolerances/9.7Experimentation/Problems

10SomeSpecialProcessControlProcedures
10.1SomeMiscellaneousTopics/10.2SomeSpecialTopicsonShewhartControlChartsforVariables/10.3SomeRelatedSpecialProcedures/10.4AGeneralTestforHomogeneity/10.5ProbabilityLimitsonControlChartsforVariables/10.6ControlChartsforMovingAverages/10.7XChartwithaLinearTrend/10.8NarrowLimitGaging/10.9WorkingwithShortProductionRuns/10.10ASuccessChartforProductionRunsofExtremelyHighQuality/10.11CombiningProcessControlandProductAcceptance/10.12CumulativeSumControlChartforAverages/Problems

PARTTHREESCIENTIFICSAMPLING
11SomeFundamentalConceptsinScientificSampling
11.1TheImportanceofSampling/11.2SomeWeaknessesofCertainTraditionalPracticesinAcceptanceSampling/11.3PurposeofThisChapter/11.4Lot-by-LotAcceptanceUsingSingleSamplingbyAttributes/11.5OCCurveofanIdealSamplingPlan/11.6TheIndexingofAcceptancePlansbyaSinglePointontheOCCurve/11.7AverageOutgoingQualityandtheAOQL/11.8DoubleSampling/11.9ChoosingaSamplingPlantoMinimizeAverageTotalInspection/11.10MultipleandSequentialSampling/11.11RandomnessinAcceptanceSampling/Problems

12AnAQLSystemforLot-by-LotAcceptanceSamplingbyAttributes
12.1SelectinganAcceptanceInspectionProcedure/12.2AHistoricalNoteRegardingAcceptanceSamplingSystemsBasedontheAQLConcept/12.3SomeDecisionsMadeintheOriginalEstablishmentoftheAQLasaQualityStandard/12.4SomeAspectsoftheMasterTablesReproducedfromtheABCStandard/12.5DeterminingtheSampleSizeCodeLetter/12.6OCCurvesunderNormal,Tightened.andReducedInspection/12.7Single,Double,andMultipleSamplingPlansinAQLSystems/12.8ClassificationofDefects/12.9TheFormationofInspectionLots/12.10AcceptanceBasedonNumbersofDefects/12.11ASystematicRecordofQualityHistoryIsanImportantAspectofStatisticalAcceptanceProcedures/12.12SelectinganAcceptancePlanforanIsolatedLot/12.13ImportanceofAOQLValuesinSamplingPlansBasedontheAQL/Problems

13OtherProceduresforAcceptanceSamplingbyAttributes
13.1TwoUsefulVolumesofStandardTables/13.2TheDodge-RomigTables/13.3SomeReasonsforNotBasingaQualityStandardonaProvisionforScreeningInspection/13.4DesigningSingleSamplingPlansforStipulatedProducer'sandConsumer'sRisks/13.5ASimpleAQLSystemProposedbyDodge/13.6DesignOfaSequentialPlanHavinganOCCurvePassingthroughTwoDesignatedPointsl13.7Dodge'sChainSamplingInspectionPlan/Problems

14SystemsforAcceptanceSamplingfromContinuousProduction
14.1Dodge'sAOQLPlanforContinuousProduction-CSP-1/14.2MultilevelContinuousSamplingPlans(CSP-M)/14.3TheMIL-STD-1235SystemforSamplingfromContinuousProduction/14.4AOQFunctionsofSomeContinuousSamplingSchemes/14.5Skip-LotSampling/14.6FurtherCommentonContinuousSamplingPlans/14.7UniqueFeaturesofCSPPlansasGuidesforSPCSampling/Problems

15SystemsforAcceptanceSamplingbyVariables
15.1SomeAdvantagesandLimitationsOfAcceptanceSamplingbyVariablesl15.2SomeDifferentTypesofAcceptanceCriteriaInvolvingVariables/15.3UsingPlottedFrequencyDistributionsinAcceptanceSampling/15.4UseofControlChartstoIdentifyGrandLots/15.5ComputingtheOCCurveforaKnown-SigmaVariablesSamplingPlanBasedontheAssumptionofaNormalDistributioni15.6SomeGeneralAspectsofMilitaryStandard414l15.7NumericalDatatoIllustrateNormalInspectionunderMIL-STD-414/15.8TightenedInspectioninMIL-STD-414l15.9ReducedInspectioninMIL-STD-414/15.10AnUpperSpecificationLimitinMIL-STD-414/15.11Two-SidedSpecificationsinMlL-STD-414/15.12TheRelationshipamongSampleSizesundertheStandardDeviationMethod,theRangeMethod,andtheProceduresAssumingKnownVariability/15.13SomeCommentsonTable15.4/15.14TheChoicebetweenUnknown-SigmaandKnown-SigmaPlans/15.15SomeSourcesofOCCurvesforVariablesPlansBasedontheAssumptionofNormality/15.16CommentontheAssumptionofaNormalDistributioninKnown-SigmaandUnknown-SigmaPlans/15.17Acceptance/RejectionPlansMayBeDevisedtoAcceptonVariablesCriteriabuttoRejectOnlyonAttributesCriteria/15.18InternationalandCommercialStandardsCorrespondingtoMIL-STD-414/Problems

16SomeAspectsofLifeTestingandReliability
16.1PurposeofThisChapter/16.2AConventionalModeloftheProbabilityofEquipmentFailure/16.3SomeModemDefinitionsofReliability/16.4TheRelationshipbetweenaConstantFailureRateandMeanLifeorMeanTimebetweenFailures/16.5AnExperimenttoIllustrateCertainAspectsofaConstantFailureRate/16.6The"Exponential"ReliabilityFunctionThatResultsfromtheAssumptionofaConstantFailureRate/16.7PrincipalU.S.GovernmentDocumentsThatTreatLifeTestingundertheAssumptionofaConstantFailureRate/16.8TheBroadGeneralUsefulnessofSamplingandTastingStandards/Problems

PARTFOURSOMERELATEDTOPICS
17SomeEconomicAspectsofQualityDecisions
17.1ProblemsofBusinessAltemativesAreProblemsinEconomy/17.2SomeBasicConceptsinEngineeringEconomy/17.3ThreeGeneralClassesOfConsequencesThatShouldBeRecognizedinMakingCertainQualityDecisions/17.4Taguchi'sLossFunction/17.5SomeEconomicAspectsoftheMarginofSafetyinDesignSpecifications/17.6SomeSpecialDifficultiesofEstimatingIndirectCostsinEconomyStudies/17.7DidItPaytoUseStatisticalQualityControl?/17.8TheIncreasingImportanceofCostsRelatedtoProductLiability/Problems

18SomeSignificantEventsintheDevelopmentofStatisticalQualityControl
18.1QualityandStandardization/18.2TheTwoArchitectsofStatisticalQualityControl/18.3QualityAssuranceScienceandWorldWarII/18.4Japan'sRecoveryasaWorldClassIndustrialPower/18.5TheQualityCulturalRevolutionintheUnitedStates/18.6U.S.AwardsforQualityandProductivityImprovement/18.7QualitySystemStandardsandStandardization/18.8AnApologytoThoseNotMentioned

19ModelsforQualityManagementandProblemSolving
19.1Evolutionofthe"QualityWheel"/19.2NamesUsedtoDescribetheQualityManagementMovement/19.3TheBaldrigeCriteriaasaQualityManagementModel/19.4ComparingtheBaldrigeCriteriaandISO9000Requirements/19.5Problem-SolvingModelsComparedtoManagementModels/19.6The"SevenBasicToolsofStatisticalProcessControl"/19.7TrackingandCelebratingQuality

20DemonstratingtheOperationofSystemsOfChanceCauses
20.1UseofGroupExperimentsinIntroducingtheSubjectsofControlChartsandAcceptanceSamplingProcedures/20.2DemonstratingFrequencyDistributionsandControlChartsforVariables/20.3DemonstratingAcceptanceSamplingbyAttributes/20.4Deming'sRedBeadExperiment

APPENDIXES
1GlossaryofSymbols
2Bibliography
3Tables
NAMEINDEX
SUBJECTINDEX