Bayesian analysis of system availability with geometric failure law in life testing

Bayesian analysis of system availability with geometric failure law in life testing Purpose – The main objective of this paper is to consider the problem of a system amenable to maintenance and to provide to posterior analysis, Bayesian point estimators and Bayesian availability analysis of a k − out of − m system with geometric failure as well as repair time distribution. Design/methodology/approach – The study considers a Bayesian approach, treats these population models as random quantities and makes good use of old information to construct a prior distribution model for these parameters, and then make use of current data to revise this starting assessment in the form of a posterior distribution model for the population model parameters, while the primary motivation to use a Bayesian reliability method is typically a desire to save on test time and materials cost. Findings – The study clearly demonstrates that, when inspections are performed at specific intervals, time is not continuous and is measured on a discrete scale. It considers the number of successful cycles or operations before failure, then the repair process helps to improve the system reliability. Originality/value – The proposed methodology represents an efficient way to evaluate the maintenance performance when time is not continuous and measured on a discrete scale. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Quality in Maintenance Engineering Emerald Publishing

Bayesian analysis of system availability with geometric failure law in life testing

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Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
1355-2511
DOI
10.1108/13552511011048931
Publisher site
See Article on Publisher Site

Abstract

Purpose – The main objective of this paper is to consider the problem of a system amenable to maintenance and to provide to posterior analysis, Bayesian point estimators and Bayesian availability analysis of a k − out of − m system with geometric failure as well as repair time distribution. Design/methodology/approach – The study considers a Bayesian approach, treats these population models as random quantities and makes good use of old information to construct a prior distribution model for these parameters, and then make use of current data to revise this starting assessment in the form of a posterior distribution model for the population model parameters, while the primary motivation to use a Bayesian reliability method is typically a desire to save on test time and materials cost. Findings – The study clearly demonstrates that, when inspections are performed at specific intervals, time is not continuous and is measured on a discrete scale. It considers the number of successful cycles or operations before failure, then the repair process helps to improve the system reliability. Originality/value – The proposed methodology represents an efficient way to evaluate the maintenance performance when time is not continuous and measured on a discrete scale.

Journal

Journal of Quality in Maintenance EngineeringEmerald Publishing

Published: Jun 1, 2010

Keywords: Maintenance; Bayesian statistical decision theory; Tests and testing

References

  • Geometric failure law in life testing
    Yaqub, M.; Khan, A.H.

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