Reliability prediction and testing textbook PDF
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ReliabilityPredictionandTestingTextbook Reliability Prediction and Testing Textbook LevM.Klyatis ProfessorEmeritus HabilitatedDr.-Ing.,Dr.ofTechnicalSciences,PhD EdwardL.Anderson BSinMechanicalEngineering Thiseditionfirstpublished2018 ©2018JohnWiley&Sons,Inc. Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,or transmitted,inanyformorbyanymeans,electronic,mechanical,photocopying,recordingor otherwise,exceptaspermittedbylaw.Adviceonhowtoobtainpermissiontoreusematerialfrom thistitleisavailableathttp://www.wiley.com/go/permissions. TherightofLevM.KlyatisandEdwardL.Andersontobeidentifiedastheauthorsofthiswork hasbeenassertedinaccordancewithlaw. RegisteredOffice JohnWiley&Sons,Inc.,111RiverStreet,Hoboken,NJ07030,USA EditorialOffice 111RiverStreet,Hoboken,NJ07030,USA Fordetailsofourglobaleditorialoffices,customerservices,andmoreinformationaboutWiley productsvisitusatwww.wiley.com. 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LibraryofCongressCataloging-in-PublicationData Names:Klyatis,LevM.,author.|Anderson,EdwardL.,1945-editor. Title:Reliabilitypredictionandtestingtextbook/byLevM.Klyatis; EdwardL.Anderson,languageeditor. Description:Hoboken,NJ,USA:Wiley,2018.|Includesbibliographical referencesandindex.| Identifiers:LCCN2017054872(print)|LCCN2017059378(ebook)|ISBN 9781119411925(pdf)|ISBN9781119411932(epub)|ISBN9781119411888 (cloth) Subjects:LCSH:Acceleratedlifetesting. Classification:LCCTA169.3(ebook)|LCCTA169.3.K59642018(print)|DDC 620/.00452–dc23 LCrecordavailableathttps://lccn.loc.gov/2017054872 CoverDesign:Wiley CoverImage:©naqiewei/GettyImages Setin10/12ptWarnockbySPiGlobal,Chennai,India PrintedintheUnitedStatesofAmerica 10 9 8 7 6 5 4 3 2 1 DEDICATION TomywifeNellyaKlyatis TomywifeCarolAnderson vii Contents Preface xi LevM.KlyatisandEdwardL.Anderson AbouttheAuthors xix Introduction xxiii LevM.Klyatis 1 AnalysisofCurrentPracticesinReliabilityPrediction 1 LevM.Klyatis 1.1 OverviewofCurrentSituationinMethodologicalAspectsof ReliabilityPrediction 1 1.1.1 WhatisaPotentialFailureMode? 5 1.1.2 GeneralModel 6 1.1.3 ClassicalTestTheory 6 1.1.4 Estimation 7 1.1.5 ReliabilityPredictionforMeanTimeBetweenFailures 9 1.1.6 AboutReliabilitySoftware 9 1.1.6.1 MIL-HDBK-217PredictiveMethod 10 1.1.6.2 Bellcore/TelcordiaPredictiveMethod 11 1.1.6.3 DiscussionofEmpiricalMethods 11 1.1.7 PhysicsofFailureMethods 12 1.1.7.1 Arrhenius’sLaw 12 1.1.7.2 EyringandOtherModels 12 1.1.7.3 HotCarrierInjectionModel 13 1.1.7.4 BlackModelforElectromigration 14 1.1.7.5 DiscussionofPhysicsofFailureMethods 14 1.1.8 LifeTestingMethod 15 1.1.8.1 Conclusions 15 1.1.8.2 FailureoftheOldMethods 17 1.1.9 SectionSummary 23 1.2 CurrentSituationinPracticalReliabilityPrediction 24 1.3 FromHistoryofReliabilityPredictionDevelopment 27 viii Contents 1.4 WhyReliabilityPredictionisNotEffectivelyUtilizedinIndustry 30 References 35 Exercises 40 2 SuccessfulReliabilityPredictionforIndustry 43 LevM.Klyatis 2.1 Introduction 43 2.2 Step-by-StepSolutionforPracticalSuccessfulReliability Prediction 46 2.3 SuccessfulReliabilityPredictionStrategy 48 2.4 TheRoleofAccurateDefinitionsinSuccessfulReliabilityPrediction: BasicDefinitions 49 2.5 SuccessfulReliabilityPredictionMethodology 53 2.5.1 CriteriaofSuccessfulReliabilityPredictionUsingResultsof AcceleratedReliabilityTesting 53 2.5.2 DevelopmentofTechniquesforProductReliabilityPredictionUsing AcceleratedReliabilityTestingResults 63 2.5.2.1 BasicConceptsofReliabilityPrediction 63 2.5.2.2 PredictionoftheReliabilityFunctionwithoutFindingtheAccurate AnalyticalorGraphicalFormoftheFailures’DistributionLaw 64 2.5.2.3 PredictionUsingMathematicalModelsWithoutIndicationofthe DependenceBetweenProductReliabilityandDifferentFactorsof ManufacturingandFieldUsage 65 2.5.2.4 PracticalExample 68 References 70 Exercises 71 3 TestingasaSourceofInitialInformationforSuccessful PracticalReliabilityPrediction 75 LevM.Klyatis 3.1 HowtheTestingStrategyImpactstheLevelofReliability Prediction 75 3.2 TheRoleofFieldInfluencesonAccurateSimulation 80 3.3 BasicConceptsofAcceleratedReliabilityandDurabilityTesting Technology 83 3.4 WhySeparateSimulationofInputInfluencesisnotEffectivein AcceleratedReliabilityandDurabilityTesting 88 References 96 Exercises 97 4 ImplementationofSuccessfulReliabilityTestingand Prediction 101 LevM.Klyatis 4.1 DirectImplementation:FinancialResults 102 Contents ix 4.1.1 Cost-EffectiveTestSubjectDevelopmentandImprovement 107 4.1.1.1 Example1 108 4.1.1.2 Example2 109 4.2 StandardizationasaFactorintheImplementationofReliability TestingandPrediction 110 4.2.1 ImplementationofReliabilityTestingandSuccessfulReliability PredictionthroughtheApplicationofStandardEP-456“Testand ReliabilityGuidelines”forFarmMachinery 110 4.2.2 HowtheWorkinSAEG-11Division,ReliabilityCommitteeAssisted inImplementingAcceleratedReliabilityTestingasaComponentof SuccessfulReliabilityPrediction 111 4.2.3 DevelopmentandImplementationofReliabilityTestingduringthe WorkfortheInternationalElectrotechnicalCommission(IEC),USA RepresentativeforInternationalOrganizationforStandardization (ISO),ReliabilityandRisk(IEC/ISOJointStudyGroup) 149 4.3 ImplementingReliabilityTestingandPredictionthrough Presentations,Publications,NetworkingasChatwiththeExperts, Boards,Seminars,Workshops/SymposiumsOvertheWorld 155 4.4 ImplementationofReliabilityPredictionandTestingthrough CitationsandBookReviewsofLevKlyatis’sWorkAroundthe World 183 4.5 WhySuccessfulProductPredictionReliabilityhasnotbeenWidely EmbracedbyIndustry 193 References 194 Exercises 195 5 ReliabilityandMaintainabilityIssueswithLow-Volume, Custom,andSpecial-PurposeVehiclesandEquipment 197 EdwardL.Anderson 5.1 Introduction 197 5.2 CharacteristicsofLow-Volume,Custom,andSpecial-Purpose VehiclesandEquipment 200 5.2.1 ProductResearch 202 5.2.2 VendorStrength 203 5.2.3 SelectaMatureProduct 203 5.2.4 DevelopaStrongPurchaseContract 203 5.2.5 EstablishaSymbioticRelationship 204 5.2.6 UtilizeConsensusStandards 204 5.2.7 UserGroups/ProfessionalSocieties 205 5.2.8 Prerequisites 205 5.2.9 ExtendedWarranties 206 5.2.10 Defect/FailureDefinitions/Remedies 206 5.2.11 Pre-Awardand/orPreproductionMeetings 207 5.2.12 Variation 208 x Contents 5.2.13 FactoryInspections 209 5.2.14 PrototypeFunctionalorPerformanceTesting 210 5.2.15 AcceptanceTesting 210 5.2.16 “LeadtheFleet”Utilization 211 5.2.17 Reserves 212 5.2.18 ProblemLog 213 5.2.19 Self-Help 213 References 214 Exercises 214 6 ExemplaryModelsofProgramsandIllustrationsfor ProfessionalLearninginReliabilityPredictionand AcceleratedReliabilityTesting 217 LevM.Klyatis 6.1 ExamplesoftheProgram 217 6.1.1 Example1.SeveralDays’Course:“SuccessfulPredictionofProduct ReliabilityandNecessaryTesting” 217 6.1.2 Example2.One-DayCourse“MethodologyofReliability Prediction” 218 6.1.3 Example3.One–TwoDays’Course(ortutorial)“Accelerated ReliabilityandDurabilityTestingTechnologyasSourceofObtaining InformationforSuccessfulReliabilityPrediction” 219 6.1.4 Example4.One–TwoDays’Seminar“FoundationforDesigning SuccessfulAcceleratedTesting” 219 6.2 IllustrationsfortheseandOtherProgramsinReliabilityPrediction andTesting 220 6.2.1 Examples:TextfortheSlides 220 6.2.2 ExamplesofFigures 228 Index 243 xi Preface LevM.Klyatisand EdwardL.Anderson WhenLevKlyatisbeganhisengineeringcareerin1958asatestengineeratthe UkrainianStateTestCenterforfarmmachinery,hewassurprisedtolearnthat, evenafterextensivetestingbythiscenter,thetestingwasnotaccuratelypre- dictingthereliabilityoftheproductsasusedbyfarmers.Thistestcenterwould conductfarmmachineryfieldtestingduringoneseasonofoperation,andmake therecommendationtomanufacturethenewproductbasedonresultsofthis single-seasontesting. Neither the designers, nor test engineers, nor the researchers, nor other decision-makersinvolvedknewwhatwouldhappenafterthefirstseason.The testcenterwasnotaccuratelypredictingtrueproductreliabilityduringthelife cycle of the machines. Later, Lev Klyatis realized that this situation was not uniquetofarmmachinery,butwasrelatedtootherareasofindustryandother countries over the world, even when they claimed to be doing accelerated reliabilitytesting. Whyarewewritingthisbook?Aswillbeseen,itistheauthor’sobservation thatthedevelopmentsoftechnology,methodologies,hardware,andsoftware are advancing at an unprecedented rate. But, in the same time, we find that reliabilitytestingandpredictionareadvancingmuchmoreslowly;andinmany casesitiscommontofindreliabilitytestingandpredictionmethodologiesthat havechangedlittleinthepast60–70years.Asproductcomplexityincreases, the need for near-perfect product reliability, which is founded on the ability toaccuratelypredictreliabilitypriortowidespreadproductionandmarketing, becomesacompany’scriticalobjective.Failuretopredictandremedyfailures canresultinhumantragedy,aswellasseriousfinanciallossestothecompany. Considerthetwofollowingrecentexamples. On May 31, 2009, Air France’s flight AF447 departed Rio de Janeiro en routetoPariscarrying228passengersandcrew;severalhoursintotheflightit crashedintotheAtlanticOcean,killingallonboard[1,2].Acontributingfactor in the accident was pitot tubes, which were believed to have iced, resulting xii Preface in the loss of accurate airspeed and altitude information. The pitot tubes were known to have a problem with icing and had been replaced by several other airlines. Following the accident, The European Aviation Safety Agency (EASA)madecompulsorythereplacementoftwooutofthreeairspeedpitot’s on Airbus A330s and A340s AD (204-03-33 Airbus Amendment 3913-447. Docked 2001- NM-302-AD), and the FAA followed with a near-identical requirement in promulgating Docket No. FAA-2009-0781 AD 2009-18-08 Final Rule Airworthiness Directive AD concerning Airbus A330 and A340 airplanes.Itisprofoundlytroublingthatinageofstate-of-the-artfly-by-wire jetaircraft,wewouldbeencounteringproblemswithpitottubeicing[3]. InFebruary2014,GeneralMotorsissuedarecallforover2.6millionvehicles to correct an ignition switch defect responsible for at least 13 deaths, and possiblemorethan100,andthisdoesnotincludethoseseriouslyinjured.The ignitionswitchcouldmovefromthe“On”positiontothe“Acc”position;and, when this happened, safety systems, such as air bags, anti-lock brakes, and powersteering,couldbedisabledwiththevehiclemoving.Theproblemwas initiallyuncoveredbyGMasearlyas2001,withcontinuedrecommendations tochangethedesignthrough2005,butthisrecommendationwasrejectedby management. BytheendofMarchof2015thecosttoGMfortheignitionswitchrecalls was $200 million and was expected to reach as much as $600 million [4–6]. Addtothefinanciallossthepersonaltragedyofthosekilledorinjuredandto theirfamilies,andthetruecostoffailedreliabilitypredictionbecomesevident. By the end of the next decade it is almost a certainty that you will be shar- ingtheroadwithsometypeofautonomousvehicle[7–9].Considerthedegree ofreliabilitypredictionthatwillbeneededtoprovidethelevelofconfidence needed.Whetheryouaredrivinganautonomousvehicleormerelysharingthe roadwiththem,youareliterallybettingyourlifeontheadequacyandaccuracy ofthereliabilitytestingforeachcriticalcomponentanddecision-makingpro- cess.Consideringthat,today,wearehavingdifficultieswithignitionswitches andpitottubes,thiswillbeamajorundertaking. Thisisparticularlysowhenthetestingwillneedtoaccountforsuchvaried environmentalconditionsasheat,cold,rain,snow,roadwaysalt,andvarious other expected and unexpected contaminants. Couple this with the 10 years pluslifeoftheaverageautomobile[10],andreliabilityassuranceagainstawide varietyofdegradationsisnecessary,andalllifefailuremodesmustdefaulttoa fail-safemode.Theseareonlyexamplesfrommanyreal-lifeproblemsthatare connectedwithinadequatereliabilitypredictionandtestingmethods. Unfortunately,toooftenthesecostsforfailedreliabilitypredictionandtest- ingareneverfactoredintoanorganization’sdecision-makingprocesses.While the human and financial impacts of responsible new product development should be foremost in an organization’s (including research and pre-design, andtesting)activitiesandconcerns,toooftentheyareoverlookedorassumed
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