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Reliability Issues for DOD Systems: Report of a Workshop (2002)
Committee on National Statistics (CNSTAT)

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Reliability Issues for DoD Systems: Report of a Workshop

nonparametric methods, 5, 6, 15, 36, 41-47, 71

stochastic processes, 43, 44, 56-58

Experimental design, 1, 9, 35-36, 38

F

Failure modeling, 8-9

see also Fatigue modeling

“bad actors,”4, 8

components, 4, 8, 16, 17, 18, 20, 21, 22, 25

Integrated Reliability Growth Strategy, 30-31

PREDICT, 28-29, 65

historical perspectives, 11-12

physics of failure, 4, 8-9, 22, 58, 70, 71-73

reliability growth modeling, 11-34 (passim)

reliability modeling, other, 4, 8, 40, 42-46(passim), 57-60

Failure Reporting, Analysis, and Corrective Action System, 31

Fault trees, 29, 31, 62

Fatigue modeling, 2, 4, 5, 8

reliability growth models, 25

reliability modeling, other, 2, 5, 8, 35, 36, 56-60, 71, 72

Feedback loops, 4, 25

Ferguson, Jack, 55, 75, 86

Field performance data, 2, 4, 5, 13, 20-23, 24, 25, 26, 33, 37

data archive, 20

data bases, 21, 23

cost-effectiveness, 20, 21, 22, 26

training exercises, data from, 37, 38-39

Fries, Arthur, 32-33, 84

G

Gaussian distribution, 56-57

Gaver, Donald, 12-13, 16-18, 23, 24, 84

General Dynamics Advanced Technology, 30

Goodness of fit, 14, 42

H

Handbooks, 3, 6, 9, 10, 71

RAM Primer, 3, 5-6, 8, 9, 75-77

Hollis, Walter, 32, 84

Huller, Jerry, 50

I

Integrated Reliability Growth Strategy, 8, 30-32, 72

Internet, RAM Primer, 5

K

Kaplan-Meier estimates, 15

L

Learning curves, 14

Life-cycle factors, 6, 25, 32, 56

costs, 2, 4, 26, 63-69

warranty costs, 20, 21, 22, 23, 25, 61, 62, 63-64, 65, 67-68

Linear models, 11, 14, 55, 59, 74

Bayesian, 40, 41

Los Alamos National Laboratory, 28, 29

M

Maintainability, 4, 26

Maintenance, 12, 25

alternative models, 6-7

Management factors, 4, 9, 75, 78

Markov chain techniques, 48, 53-54

Material fatigue, see Failure modeling;

Fatigue modeling

Meeker, William, 13, 19-23, 24, 72, 85

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