12. Accelerated Testing - References & Index

7/25/2019 12. Accelerated Testing - References & Index

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R E F E R E N C E S

Accelerated Testing Research: Special Publications

(2000), Societyof AutomotiveEngineers,

Warrendale,PA.

Chan,

H . Anthony (2001).

Accelerated Stress Testing Handbook: Guide for Achieving

Quality Products,

IEEE

Press,

Institute of Electrical and

Electronics

Engineers,

Piscataway,

NJ.

Dh i l l o n , B.S. (1985).

Quality Control, Reliability, and Engineering Design,

Marcel Dekker,

New York.

Dodson,

B.L. , and M.D. Mulcahy (1992).

Certified Reliability Engineer Examination

Study

Guide,

Quality Publishing,

Tucson,

AZ.

Dodson, Bryan (1994). Weibull Analysis with Software), ASQC Qua lity

Press,

Milwaukee, WI .

Dovich, R.A. (1990).

Reliability Statistics,

ASQC Quality

Press,

Milwaukee, WI .

Environmental Stress Screening Handbook

(2004), Thermotron Ltd. , Holland,

M I .

Fundamentals

of

Accelerated Stress Testing

(2004), Thermotron Ltd. , Holland, M I .

Hobbs, Gregg

K. (2000).

Accelerated Reliability Engineering: HALT and HASS,

JohnWiley

Sons,New York.

Ireson,

G.W., and C.F.Coombs(1996).

Handbook of Reliability Engineering and Management,

M cG r aw -H i l l,

New York.

Kapur, K.C., and L.R.Lamberson (1977).

Reliability in Engineering Design,

John Wiley &

Sons,New York.

Kie lp in sk i ,

T.J., and W. Nelson (1975). Optimum

CensoredAccelerated

L i f e

Tests

for Normal

and Lognormal L i f e Distributions, IEEE

Transactions on Reliability,

R-24:310-320,

Institute of Electrical and

Electronics

Engineers,

Piscataway,

NJ.

Krishnamoorthi, K.S. (1992).

Reliability Methods for Engineers,

ASQ Quality

Press,

Milwaukee, WI .

La l l ,

Pradeep,

Michael G.

Pecht,

and Edward B. Hakim, (1997). Influence of Temperature on

Microelectronics, CRC

Press,

Boca Raton,FL.

-247-


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ACCELERATED

TESTING

Lewis, E.E. (1995).

Introduction to Reliability Engineering,

JohnWiley &Sons,New York.

Meeker,

W., and W. Nelson (1976). Optimum

Accelerated

Li f eTestsfor Weibull and

Extreme

Value Distributions, IEEE Transactions on Reliability,

R-25:20-24,

Institute of Electri

cal and

ElectronicsEngineers, Piscataway,

NJ.

Meeker,W.Q., and G.J. Hahn (1985). How to Plan an Accelerated Life TestSome Practical

Guidelines,

ASQ QualityPress,Milwaukee, WI .

Nelson, W. (1990). Accelerated Testing: Statistical Models, Test Plans and Data Analysis,

JohnWiley &Sons,New York.

NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/

handbook/.

O'Connor, Patrick D.T. (2002). Practical Reliability Engineering,

John

Wiley &

Sons,

New York.

Shooman,M . L . (1990). Probabilistic Reliability: An Engineering Approach, RobertE. Krieger,

Malabar,FL.

Staudte,

Robert

G., and S.J. Sheather (1990). Robust Estimation and Testing, JohnWiley &

Sons,New York.

Tobias, PA., and D.C. Trindade (1995).

Applied Reliability,

Van Nostrand Reinhold, New

York .

U.S. Army MaterielSystemsAnalysis Ac t i v i t y (1999). Reliability Growth Handbook.

U.S.Departmentof

Defense.

M I L - HD BK - 18 9 : Reliability Growth Management, Naval Pub

lications and Forms

Center,

Philadelphia.

U.S.

Department

ofDefense. M I L - H D BK - 7 81 : Reliability Test Methods, Plans and Environ-

mentsfor Engineering Development, Qualification and Production, Naval

Publications

and FormsCenter, Philadelphia.

U.S. Department of

Defense.

MIL-STD-810: Environmental Test Methods and Engineering

Guidelines, Naval Publicationsand Forms

Center,

Philadelphia.

U.S.DepartmentofDefense. MIL-STD-1635: Reliability Growth Testing, Naval

Publications

and FormsCenter, Philadelphia.

Walker, N. Edward (1998).

The Design Analysis Handbook,

Newnes, Boston.

Young, W.R. (1998).

Accelerated

Temperature Pharmaceutical ProductStability Determina

tions, Drug Development and Industrial Pharmacy.

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http://www.itl.nist.gov/div898/http://www.itl.nist.gov/div898/


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I N D E X

Accelerated testing

ambiguities in , 17

models for, 141-180

plans for, 103-140

purposeof, 1-2

tolerances

in, 5-8

see

alsoTesting

Acceleration, linear, 141-142

Acceptance testing, 119-121, 208

Acronyms,

list

of, 243-245

Ai r f l ow , 189-190, 194-195,202

Altitude,

219

A M S A A (ArmyMaterial

SystemsAnalysis

Act iv i ty ) reliabil i tygrowthmodel, 139-140

Analogic Corporation,ESS program results,

197

Arrheniusmodel, 149-157

Automobileresale

value, 16

Bathtub

curve, 182

Bayes' theorem, 68-71

Bayesian testing, 110-118

determiningparameters

for, 113-115

Weibulldistribution in ,

110-115

Bendix

Corporation, ESS program results, 197

Bias,lack of, 73

Binomial

distribution,5658

Bogey testing, 99, 109

Burn-in

testing, 185, 191

optimizing, 202-204

Casehistories, 197-198

Censoreddata,20, 53

Center of

gravity,

29

Central

limit

theorem, 40

Chamber, 201,213

Changecontrol,12

Characteristic

life,

34

Chemical

reactions, 149

Chi-squaredistribution,62-64

Chi-square significance, 224-225r

Coffin-Masonmodel, 170-171

Combinedenvironmental screening, 192-193

Combinedenvironmental testing, 218

Computercontrol,202

Concept

validation,

10-11

Condensation, 213

Confidence intervals

nonparametric, 99, 101

for

normaldistribution, 86-87

for Weibulldistribution,93-94

Confidence

limits,

53

Consistency, 73

Continuous modelingdistributions,33-54

Continuous variables, 20-21

Corrosion,219

Cumulativedensityfunction

hypergeometric, 58

standardnormal,45

Cumulativedistribution function, 25-27

binomial,57

exponential,80

F- 67

lognormal,

47

normal,89

Poisson, 55,229f

inprobability

plotting,

74, 80

standard

normal,

222-223f

Weibul l ,

37, 97

Cumulativehazardfunction, 74

exponential, 79

normal,in hazard

plotting,

87

Weibul l ,

95

Customer requirements, understanding, 9-10

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ACCELERATED TESTING

Cyclic

testing, 215-216

Defect

exposure

tests,

208

Defect

rate, manufacturing, 6

Degradation

testing models, 171-177

Degrees

of freedom, 164

Designlife, determining,

2-5

Designvalidation,

11

Developmenttests,

1

Discrete modeling

distributions,

55-61

identifying correct

distribution,

61,62/

Discrete variables, 21

Distributions

binomial,

56-58

chi-square, 62-64

continuous

modeling,

33-54

discrete

modeling,

55-61

identifying correct

distribution,

6162/

exponential,50-54

parameter estimation for, 74-75

reliabili tyfunction wi th acceleration

factor,142r

in

sequential testing, 125-126

F-distribution,

66-68

geometric, 60-61

hypergeometric, 58-60

lognormal,46-50

parameter estimation for, 91

reliabili tyfunction with acceleration

factor,142r

normal,

39-46

hazardplottingfor, 87-89

maximumlikelihoodestimation for,

84-87


probabilityplottingfor, 89-91

reliabili tyfunction wi th acceleration

factor,142/

Poisson, 55-56

posterior, 68

prior,

68

sampling,61-68

shapesof, comparing, 142-144

summary of, 71

f-distribution,

64-66

Weibull,

33-39

Bayesian, in sequential testing, 126-131

in

Bayesian testing, 110-115


maximum likelihoodestimation for,

92-94

parameter estimation for 92-99

probabilityplottingfor, 97-99

reliabili ty function wi th acceleration

factor, 142?

Duane reliabili tygrowthmodel, 136-138

Dust,219

Dynamic

screens,

195-196

Electrical

stress, 191,

218

Electrodynamic

shakers,

216, 217

Electronic

equipment, 184-185

estimatingshapeparameter for, 112-113

HALT

for, 179

reliabili tystandards

for, 149

Elephant

tests,

179

EngineeringDepartment, exampleresponse

from, 12

Environment,

test,207-208

Environmentalstress,

types of, 187-193

Environmental

stressscreening (ESS),

181-205

casehistories, 197-198

definitionof, 184

determining

screeninglevel, 199-200

equipment for, 200-202

evolutionof, 184-186

failureversus

productionlevel,200/

implementing

a program, 198-200

misconceptions about, 186-187

monitoring,

200

screencomplexitylevels, 195-196

screentypes, 193/

summary of, 205

Equipment

for

environmentalstress

screening, 200-202

test

methods and applications, 207-219

Estimation,

of parameters, 73-102

Exercised

screens,

196

Expectation, 29-30

Expected number oftrials, 124-125

Explosive

atmosphere, 219

Exponential

distribution,

50-54


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INDEX

Exponentialdistribution

cont.)

reliabil i ty function withacceleration factor,

142?

in

sequential testing, 125-126

Eyring

model, 157-168

F-distribution,66-68

F

significance, 226-227?

Failure analysis, 196

Failure

costs,

13

Failure

modes, detection of, 135

Failure

modesand effects analysis ( FM EA ) ,10

Failure

rate, 203

Failure

rateanalysis and corrective actions sys

tem(FRACAS),10

Failure-truncated testing, 113-114

Feedback

loop,

for

reliabil i tygrowth,

135-136

Fieldcorrelation, 142-148

Field

reliabil i ty,

example performance, 14?

Finaldemonstration, 135

Finance Department, exampleresponse from,

12

Financialconsiderations, 9-17

Fixturing,202

Frequency domain, 214-215

Ful l

functional

screens,196

Fungus, 219

Gamma

function, 31 n,

62, 221?

Geometricdistribution,60-61

Glossary, 233-242

Hardfailures, 195

Hazardfunction, 27-29

exponential, 51-52

for

linear acceleration, 141

lognormal,

49-50

normal,45, 46/

Weibul l ,36

Hazardplotting,74, 79, 80/

for

normal

distribution,

87-89

for Weibulldistribution,

95-96

Hewlett-Packard, ESS program results,

197-198

Hiddenreliabil i tycosts,15

High-temperatureburn-in,191

Highlyaccelerated life testing (HALT) ,

179-180

Highly

accelerated

stress

screen

(HASS),

179-180

Histogram,example, 21 /

Hydraulictesting, 216-217

Hypergeometricdistribution, 58-60

Ic ing,

219

Infancyfailure, 182, 185

Infant

mortalityperiod, 36

Instantaneous

failure

rate, 27

InstituteofEnvironmentalSciences,186

Instrumentation, 202

Intelligentdesign, 10

Interconnects, 202

Keypersonnel, 198-199

Kurtosis,30

Latent defects, 182

Life

cycle patterns, 182

Likelihoodfunction,

74

Likelihoodratio,119

Linearacceleration, 141-142

Lineardegradation, 172

Load

cycles, randomization of, 131-134

Local information matrix,74

Locationparameter, 34,49

Lognormal

distribution,

46-50

parameter estimation for, 91

reliabil i ty function withacceleration factor,

142?

Loose cargo testing, 215

Low-temperature

screen,

192

Manufacturing, 11-12

Manufacturingdefect rate, 6-7

ManufacturingDepartment, example

response

from,

12

Material

handling,

202

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ACCELERATED

TESTING

Maximum likelihoodestimation, 73-79

for

normal

distribution,

84-87

for Weibull

distribution,

92-94

Mean,

29

of

binomial distribution,

57

of

exponential

distribution,

53

of geometric

distribution,

60

of

hypergeometricfunction, 58

of lognormal

distribution,

49

ofnormal distribution,83

of/-distribution,

64

ofWeibulldistribution,37, 38/

Mean

time tofail ,39, 103, 104/

Mechanical

crack

growth

model, 170-171

Mechanicalshock, 217-218

Mechanical

tools, 215

M i l it a r y

standards,

185

Mission profiletesting, 185

Models

accelerated testing, 141-180

A M S A A reliabili tygrowth,

139-140

Arrhenius, 149-157

Coffin-Mason, 170-171

degradation testing, 171-177

Duane reliabili tygrowth, 136-138

elephant

test,

179

Eyring, 157-168

field correlation, 142-148

HALT

andHASS, 179-180

linearacceleration, 141-142

mechanical crack

growth,

170-171

qualitative

test,

176-180

reliabili tygrowth,

136-140

step-stress

testing, 177-178

voltage,

169-170

M odif iedorder of

failure,

81

Moisture,

wind ,

andrain,219

Monitoredscreens,196

M ul ti p lecensoring, 20

Nonparametric confidence intervals, 99, 101

Normal distribution,

39-46


maximumlikelihoodestimation for, 84-87

parameterestimation for, 83-91

probability

plotting

for, 89-91

reliabili ty

function

with

acceleration factor,

142/

Objective,

environmental

stress

screening, 198

Operatingcharacteristic (OC) curve, 122-124

Parameterestimation, 73-102

Pass-fail testing, 119-124

Pneumatic actuators, 215-216

Poisson cumulative

distribution

function,229/

Poisson

distribution,

55-56

Posterior

distribution,

68

Powercycling,191

Power spectral density, 215

Power supplies, 202

Prior distribution,68

Probability,fundamentals of, 19-31

Probability

densityfunction, 21-25

binomial,

56-57

chi-square, 63

exponential,50-51,75

F - 66, 67/

geometric, 60

hypergeometric, 58

forlinear acceleration, 141

lognormal,

47, 91

normal,83

Poisson, 55

posterior, 68

prior,

68

standardnormal,40, 41 /

/- 64, 65/

Weibul l ,

33, 92

Probabilityplotting,74,80-83

fornormal

distribution,

89-91

for Weibulldistribution,97-99

Product electronics, 202

Productfailure modes, 181

Product

reliabili ty

equation, 181-183

Profile,201

Qualificationtests,208

Qualitative

tests, 176-180

Quality

assurance

tests,

1

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INDEX

Random sampling, 19-21

Random

vibration,

190-191, 193, 194, 214

Randomizationof load cycles, 131-134

Reaction rate, 149

Real

wor ld

environment,

defining,

209-211

Reliabilityconfidence limits ,81

Reliabilitycosts, hidden, 15

Reliabilitydemonstration sample sizes, 2/

Reliability

function,

27

wi thacceleration factor, 142/

exponential,51

forlinear acceleration, 141

lognormal,47

Weibul l ,36

Reliability

growth,

134-140

models for, 136-140

processfor, 135-136

Reliabilityprogram

elements of, 9-17

examplescores,13/

financial

considerations for, 9-17

Reliabilitytesting, 103

Sample size

determining,

5

effect

of, 105-109

effect

on test duration, 115-118

reliabili tydemonstration, 2/

Sampling,

19-21

Sampling distributions,

61-68

Scale parameter, 34

Screens

dynamic,

195-196

exercised, 196

full

functional,

196

monitored,

196

static, 195

Second moment-generating

function,

29

Sequential testing, 119-131

BayesianWeibull

distribution in,

126-131

exponentialdistribution in , 125-126

Shape,of

distributions,

comparing, 142-144

Shape

parameter, 33

determining

value of, 118

effect of, 110-112

estimating, 112-113

Shipping

and

handling,

207, 209, 211

Shockresponsespectra, 217

Simulationtesting, 208-211

Sine

vibration

fixed frequency, 192

swept frequency, 192

Sinusoidal

input, 211-212, 214

Skewness, 30

Slip

table, 216

Soft

failures, 195

Standard

deviation,

of

normal

distribution,84

Standard normal cumulative density

function,

45

Standard normal cumulative

distribution

func

t ion,

47,222-223/

Standard normal

probability

density

function,

40,41/

Static

screens,

195

Statistical

sampling, 5

Steady

state

thermal testing, 212-213

Step-stress

testing, 177-178

Stimulationtesting, 211-212

Storage, 207, 209,210-211

Stress,

types of, 212-219

Stress

screening, environmental (ESS),

181-205

Stressuniformity,

194

Submersion, 219

Sufficiency,

73

Suppliers, in environmentalstressscreening,

198

Surfaced problems, 135

/Significance, 228

/-Distribution, 64-66

Temperature

cycling,

185, 187-190, 213

advantages

of, 193-195

Temperature testing, 212-214

Test

duration,

114-115

effect

of sample size on, 115-118

Testing

acceptance,

119-121, 208

Bayesian, 110-118

determining

parameters, 113-115

Weibull

distribution in ,

110-115

bogey, 99, 109

burn-in,

185, 191

optimizing,202-204


8/10

ACCELERATED TESTING

Testing cont.)

combined environmental,

218

cyclic,

215-216

defect exposure, 208

development, 1

electricalstress,218

electrodynamic, 216, 217

equipment methods and applications,

207-219

failure-truncated,

113-114

hydraulic,

216-217

loose cargo, 215

mechanical, 215

mechanical shock, 217-218

mission

profile,

185

pass-fail,

119-124

pneumatic, 215-216

qualification,208

qualityassurance,

1

sequential, 119-131

BayesianWeibulldistributionin,

126-131

exponentialdistribution in ,

125-126

simulation,

208-211

stimulation, 211-212

temperature, 212-214

thermal,steady state,212-213

time-truncated,

114

vibration,

185, 190-191, 192, 214-218

zero-failure, 109-118

guidelines for, 115-118

see

also

Accelerated testing

Thermalexpansion, 212

Thermal

shock, 192, 213-214

Time

domain, 214-215

Time

history pulse, 217

Time-truncatedtesting, 114

Tolerances

determining, 5-8

number of

combinations,

6/

worst-case, 5-8

Transitiontemperature of metals, 212

Type

I error, 106-109

Type error, 106, 109

U.S.

government documents, 231-232

Ultraviolet,

219

Unforeseen deficiencies, 134-135

Uni t ,

uniform

random number generation,

131-134

Userprofiles, 2-4

Variance,

29

of

binomial distribution,57

ofestimates,

74

ofexponentialdistribution,51

ofgeometricdistribution,60

ofhypergeometricfunction, 58

of

lognormal distribution,

49

minimum,

73

of

/-distribution,64

ofWeibull

distribution,37, 38/, 93

Vibration

testing, 185, 190-191, 192, 214-218

Voltage

margining,

191

Voltagemodels, 169-170

Wearoutperiod,36

Weibull

distribution,33-39

Bayesian, in sequential testing, 126-131

inBayesian testing, 110-115

hazard

plotting

for, 95-96

maximumlikelihood

estimation for, 92-94

parameter

estimation for 92-99

probabilityplotting

for, 97-99

reliabil i ty

function

with

acceleration factor,

142/

Zero-failure

testing, 109-118

guidelines

for, 115-118


9/10

B O U TT H E UT HOR S

ryanDodson

is the Director of

Reliability

Engineering

at Visteon in Dearborn,

Michigan.

He formerly was the

Manager of

Reliability

Engineering and

Quality

Informa

t i on

Systemsfor Continental Teves, Brake andChassis,

North

America. Prior to

joining

Continental Teves,

Dr.

Dodson held the positions of

Total

Quality Manage

ment

(T Q M )

Leader and

Reliability

Leader at

Alcoa

and

the position ofIndustrialEngineer at

Morton Th i oko l .

Dr.

Dodson has authored

seven

books and

five

com

mercial software programs, including the

Reliability

Engineering Handbook, Weibull

Analysis:

with Software,

and Certified

Reliability Engineer Examination Study

Guide. He

also

is the author of the International Quality

Federation's Six Sigma certification exam.

Dr.

Dodson holds a B.S. in petroleum engineering, an

M.S.

inindustrialengineering, an

M . B .A . ,

and a Doctor of

BusinessAdministration.

In addition,

he is a Certified Quality Engineer (CQE), a Certified

Reliability

Engineer (CRE), a Six Sigma

Master Black Belt, and a licensed Professional Engineer in Michigan and Indiana.

H a r r ySchwabhas almost

for tyyears

of experience as an

engineer, specializing in structural dynamics and vibra

tions. He holds a BachelorofAerospace Engineering

from

the Georgia Institute of

Technology,

an

M.S.

in Engineer

ing

Mechanics

f rom

the University of

MissouriRolla,

and an

M . B .A . f rom

the Florida Institute of Technology.

M r .

Schwab has worked

in

the

aerospace,

automotive, and

commercial

industries. The products

wi th

which he has

beeninvolved

include automobiles, trucks, railroad freight

cars,

aircraft,

boats,

and guided missiles. He has many

years

of experience inworking

wi th

random vibrations

and developed a method for deriving laboratory testing

-255-


10/10

ACCELERATED TESTING

environments fromnon-stationary data. This technique can be used to accurately simulate real-

wo r l denvironments

while

greatly decreasing

test

time.

M r . Schwab has authored several technicalpapers for SAE International and the Institute of

Environmental

Sciences

and Technology

(IEST),

as

we l l

as for other technical organizations

and

publications.

Thesecover the fields ofvibrationtesting and analysis. He developed innova

tivetesting techniques for both the aerospaceand automotive industries, and he is a registered

Professional Engineer in

Missouri

and Florida.

12. Accelerated Testing - References & Index

Documents

Transcript of 12. Accelerated Testing - References & Index