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

Benjamin Reiser; Betty J. Flehinger; Andrew R. Conn

doi:10.1109/24.510808

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

Benjamin Reiser, Betty J. Flehinger, Andrew R. Conn

Research output: Contribution to journal › Article › peer-review

Abstract

Summary & Conclusions - Consider a system of k components that fails whenever there is a defect in at least one of the components. Due to cost & 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. We 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.

Original language	English
Pages (from-to)	238-243
Number of pages	6
Journal	IEEE Transactions on Reliability
Volume	45
Issue number	2
DOIs	https://doi.org/10.1109/24.510808
State	Published - 1996
Externally published	Yes

Bibliographical note

Funding Information:
We are grateful for the thorough review & editing of Dr. R. A. Evans. We thank Peggy Cargiulo for her manuscript preparation. Benjamin Reiser was a visiting scientist on leave from the University of Haifa. Andrew R. Conn’s research was supported in part by the Advanced Research Projects Agency of the Department of Defense and was monitored by the US Air Force Office of Scientific Research under Contract No. F49620-9 1- C-0079. The US Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright hereon.

Keywords

Defect probability
Diagnostic probability
Masking
System component

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Electrical and Electronic Engineering

Access to Document

10.1109/24.510808

Cite this

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abstract = "Summary & Conclusions - Consider a system of k components that fails whenever there is a defect in at least one of the components. Due to cost & 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. We 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.",

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AB - Summary & Conclusions - Consider a system of k components that fails whenever there is a defect in at least one of the components. Due to cost & 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. We 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.

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

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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