Performance analysis of an aggregation and disaggregation solution procedure to obtain a maintenance plan for a partially observable multi-component system

TitlePerformance analysis of an aggregation and disaggregation solution procedure to obtain a maintenance plan for a partially observable multi-component system
Publication TypeJournal Article
Year of Publication2017
AuthorsÖzgür-Ünlüakın, D., and T. Bilgiç
JournalReliability Engineering & System Safety
Volume167
Pagination652-662
ISSN0951-8320
KeywordsAggregation, Disaggregation, Dynamic Bayesian networks, Maintenance, Multi-component systems, Partially observable Markov decision processes
Abstract

We analyze the performance of an aggregation and disaggregation procedure in giving the optimal maintenance decisions for a multi-component system under partial observations in a finite horizon. The components deteriorate in time and their states are hidden to the decision maker. Nevertheless, it is possible to observe signals about the system status and to replace components in each period. The aim is to find a cost effective replacement plan for the components in a given time horizon. The problem is formulated as a partially observable Markov decision process (POMDP). We aggregate states and actions in order to reduce the problem space and obtain an optimal aggregate policy which we disaggregate by simulating it using dynamic Bayesian networks (DBN). The procedure is statistically compared to an approximate POMDP solver that uses the full state space information. Cases where aggregation performs relatively better are isolated and it is shown that k-out-of-n systems belong to this class.

URLhttps://www.sciencedirect.com/science/article/pii/S095183201730443X
DOI10.1016/j.ress.2017.04.013