Reliability prediction and testing textbook

262 Pages·2018·11.729 MB·English

by  Anderson, Edward, Klyatis, Lev M.

ReliabilityPredictionandTestingTextbook
Reliability Prediction and Testing Textbook
LevM.Klyatis
ProfessorEmeritus
HabilitatedDr.-Ing.,Dr.ofTechnicalSciences,PhD
EdwardL.Anderson
BSinMechanicalEngineering
Thiseditionfirstpublished2018
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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