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Determining the optimal maintenance action for a deteriorating repairable system

Authors
Kim, Teak-SooPark, Chong-SungAhn, Suneung
Issue Date
Jan-2008
Publisher
Elsevier BV
Keywords
power law failure model; Bayesian probability model; prior distribution; maintenance cost
Citation
Probabilistic Engineering Mechanics, v.23, no.1, pp 95 - 101
Pages
7
Indexed
SCIE
SCOPUS
Journal Title
Probabilistic Engineering Mechanics
Volume
23
Number
1
Start Page
95
End Page
101
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/42708
DOI
10.1016/j.probengmech.2007.12.003
ISSN
0266-8920
1878-4275
Abstract
This paper develops a decision model for risk management of the deterioration of a repairable system. When a failure occurs in a deteriorating system, an optimal maintenance decision that includes the possibility of system replacement, as compared to mere deterioration reduction, should be made. There are many uncertainties associated with deterioration, however, so the decision may require a probabilistic analysis. Here, a well-known nonhomogeneous Poisson process with a power law intensity function is used to model the uncertain behavior of the deteriorating system. A Bayesian statistical approach is adopted to allow for the uncertainty of the parameters of the power law intensity function, which imposes a conjugate prior distribution of the parameters. A power law maintenance cost function and the failure cost are analyzed to determine the magnitude of failure risk reduction by minimizing the expected cost incurred from the maintenance action and future failures. A numerical example is given. (c) 2007 Elsevier Ltd. All rights reserved.
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COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF INDUSTRIAL & MANAGEMENT ENGINEERING > 1. Journal Articles

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