Journal
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
Volume 227, Issue 9, Pages 2090-2103Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0954406212469773
Keywords
Predictive maintenance; spare parts inventory; dynamic programming; hidden semi-Markov model
Categories
Funding
- National Natural Science Foundation of China [71131005]
- Shanghai Municipal Education Commission [09SG17]
- Shanghai Education Development Foundation
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The maintenance strategies optimization can play a key role in the industrial systems, in particular to reduce the related risks and the maintenance costs, improve the availability, and the reliability. Spare part demands are usually generated by the need of maintenance. It is often dependent on the maintenance strategies, and a better practice is to deal with these problems simultaneously. This article presents a stochastic dynamic programming maintenance model considering multi-failure states and spare part inventory. First, a probabilistic maintenance model called hidden semi-Markov model with aging factor is used to classify the multi-failure states and obtain transition probabilities among multi-failure states. Then, spare parts inventory cost is integrated into the maintenance model for different failure states. Finally, a double-layer dynamic programming maintenance model is proposed to obtain the optimal spare parts inventory and the optimal maintenance strategy through which the minimum total cost can be achieved. A case study is used to demonstrate the implementation and potential applications of the proposed methods.
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