Opportunistic preventive maintenance strategy of a multi-component system with hierarchical structure by simulation and evaluation

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Equipment usually consists of many components arranged in hierarchical structure. In order to achieve efficient maintenance strategy, the system hierarchy should be taken into account. In this paper, we first give a nomenclature to describe a system composed of multiple non-identical components in a hierarchical structure, the system for an age-based and an opportunistic preventive maintenance strategies is modeled by using a Markov Decision Process (MDP). Then, near-optimal policies are found through the SARSA(λ) algorithm from Reinforcement Learning (RL), where the expected discounted cost is minimized. Simulation experiments to compare near-optimal policies obtained by SARSA(λ) are performed for both strategies with corrective maintenance and with age-based preventive maintenance policy obtained from renewal reward theory. We show that the proposed opportunistic preventive maintenance outperforms other strategies.
Publisher
Institute of Electrical and Electronics Engineers Inc.
Issue Date
2016-09
Language
English
Citation

21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016, pp.7733708

DOI
10.1109/ETFA.2016.7733708
URI
http://hdl.handle.net/10203/216352
Appears in Collection
IE-Conference Papers(학술회의논문)
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