Optimal maintenance planning for repairable multi-component systems subject to dependent competing risks
Nailong Zhang and
Qingyu Yang
IISE Transactions, 2015, vol. 47, issue 5, 521-532
Abstract:
Many complex multi-component systems suffer from dependent competing risks. The reliability modeling and maintenance planning of repairable dependent competing risks systems are challenging tasks because the repair of the failed component can change the lifetime of the other components when multiple components fail dependently. This article first proposes a generally dependent latent age model to capture the dependence of competing risks under general component repairs. Based on the proposed reliability model, both system- and component-level periodic inspection-based maintenance polices are considered for repairable multi-component systems that are subject to dependent competing risks. Under the system-level maintenance policy, the entire system is restored to the as-good-as-new state once a failure is detected. While under the component-level maintenance policy, only the failed component is repaired imperfectly. The optimal solution of the system-level policy is obtained by using renewal theory. The optimal solution of the component-level policy, however, cannot be obtained analytically, due to its complex failure and repair characteristics. A simulation-based optimization approach with stochastic approximation is developed to solve the optimization problem for the component-level policy. The developed methods are illustrated by using a cylinder head assembly cell that consists of multiple stations.
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://hdl.handle.net/10.1080/0740817X.2014.974115 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:47:y:2015:i:5:p:521-532
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20
DOI: 10.1080/0740817X.2014.974115
Access Statistics for this article
IISE Transactions is currently edited by Jianjun Shi
More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().