Condition-based maintenance using the inverse Gaussian degradation model
Nan Chen,
Zhi-Sheng Ye,
Yisha Xiang and
Linmiao Zhang
European Journal of Operational Research, 2015, vol. 243, issue 1, 190-199
Abstract:
Condition-based maintenance has been proven effective in reducing unexpected failures with minimum operational costs. This study considers an optimal condition-based replacement policy with optimal inspection interval when the degradation conforms to an inverse Gaussian process with random effects. The random effects parameter is used to account for heterogeneities commonly observed among a product population. Its distribution is updated when more degradation observations are available. The observed degradation level together with the unit’s age are used for the replacement decision. The structure of the optimal replacement policy is investigated in depth. We prove that the monotone control limit policy is optimal. We also provide numerical studies to validate our results and conduct sensitivity analysis of the model parameters on the optimal policy.
Keywords: Optimal replacement; Inverse Gaussian process; Heterogeneity (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (53)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221714009527
Full text for ScienceDirect subscribers only
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:eee:ejores:v:243:y:2015:i:1:p:190-199
DOI: 10.1016/j.ejor.2014.11.029
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().