Optimal Maintenance Policy for a Two-State System with Population Heterogeneity Under Partial Observation

Mizuki Kasuya and Lu Jin ()
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Mizuki Kasuya: University of Electro-Communications, Department of Informatics
Lu Jin: University of Electro-Communications, Department of Informatics

Chapter Chapter 18 in Quantitative Demography and Health Estimates, 2023, pp 235-245 from Springer

Abstract: Abstract We consider a single-unit system that is either in a good or deterioration state. The system deteriorates following a discrete-time Markov chain. The deterioration state is partially observed by sensors at equally spaced time epochs. The decision-maker must decide whether to continue operating the system for another time period or to perform replacement. The population of spare units for replacement is composed of various unit types that cannot be distinguished by their exterior appearance and that deteriorate in accordance with different transition probability matrices. Given the uncertainties due to the population heterogeneity and partial observation, we formulated the optimal decision-making problem for condition-based maintenance as a partially observable Markov decision process. The objective is to minimize the total expected discounted operating and replacement cost over an infinite horizon. The optimal maintenance policy is determined under the proposed model, and the result is shown by some numerical examples. Moreover, we discuss the effectiveness of the obtained maintenance policy in the presence of population heterogeneity

Keywords: Condition-based maintenance; Optimal decision-making; Partially observable Markov decision process (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-031-28697-1_18

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DOI: 10.1007/978-3-031-28697-1_18

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