Structured replacement policies for a system subject to random mission types

This paper optimizes condition‐based replacement policies for a mission‐oriented system. The key challenge in our problem is that the system does not work under a fixed mission type but is subject to an infinite sequence of random types of missions assigned in a Markovian manner, which is realistic...

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Vydáno v:Naval research logistics Ročník 71; číslo 7; s. 1055 - 1069
Hlavní autor: Zheng, Rui
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, USA John Wiley & Sons, Inc 01.10.2024
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Témata:
Condition monitoring
condition‐based maintenance
Cost analysis
Decisions
Iterative algorithms
Markov decision process
Markov processes
Missions
Optimization
Policies
policy iteration
random mission type
structural analysis
ISSN:0894-069X, 1520-6750
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Shrnutí:This paper optimizes condition‐based replacement policies for a mission‐oriented system. The key challenge in our problem is that the system does not work under a fixed mission type but is subject to an infinite sequence of random types of missions assigned in a Markovian manner, which is realistic in many practical situations. The mission process modulates the deterioration process. Taking advantage of the opportunities when missions are switched, condition monitoring is conducted to support replacement decision‐making. This paper considers two practical scenarios in which the type of the next mission is either available or unavailable at each decision epoch. The objective is to determine the optimal replacement decisions for both scenarios that minimize their long‐run expected average cost rates. The optimization problems are analyzed in the framework of the Markov decision process. The optimal decisions of both scenarios are proven to be of partially monotone control‐limit forms. Near‐optimal policies with multilevel thresholds are provided for more convenient decision‐making. The policy iteration algorithm is modified for efficient optimization. A numerical example is used to demonstrate the feasibility of the proposed approach.
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ISSN:0894-069X
1520-6750
DOI:10.1002/nav.22201