Estimating component-defect probability from masked system success/failure data

Consider a system of k components that fails whenever there is a defect in at least one of the components. Due to cost and time constraints it is not feasible to learn exactly which components are defective. Instead, test procedures ascertain that the defective components belong to some subset of th...

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Bibliographic Details
Published in:IEEE transactions on reliability 1996-06, Vol.45 (2), p.238-243
Main Authors: Reiser, B., Flehinger, B.J., Conn, A.R.
Format: Article
Language:English
Subjects:
Applied sciences
Ceramics
Costs
Data analysis
Exact sciences and technology
Failure analysis
Life estimation
Lifetime estimation
Maximum likelihood estimation
Operational research and scientific management
Operational research. Management science
Reliability theory. Replacement problems
System testing
Time factors
Wires
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Summary:Consider a system of k components that fails whenever there is a defect in at least one of the components. Due to cost and time constraints it is not feasible to learn exactly which components are defective. Instead, test procedures ascertain that the defective components belong to some subset of the k components. This phenomenon is termed masking. The authors describe a 2-stage procedure in which a sample of masked subsets is subjected to intensive failure analysis. This enables maximum-likelihood estimation of the defect probability of each individual component and leads to diagnosis of the defective components in future masked failures.
ISSN:0018-9529
1558-1721
DOI:10.1109/24.510808