Maintenance Planning under Imperfect Monitoring: an Efficient POMDP Model Using Interpolated Value Function - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IFAC-PapersOnLine Année : 2022

Maintenance Planning under Imperfect Monitoring: an Efficient POMDP Model Using Interpolated Value Function

Résumé

We develop in this paper a partially observable Markov decision process (POMDP) model for a maintenance planning problem and solve it with an efficient point-based value iteration (PBVI) algorithm. We consider a single-unit system, subjected to random degradation and failures, and for which the current degradation state can be partially observed via an imperfect monitoring system. The system state space is finite, and we model the following maintenance operations: i) perfect inspection, ii) preventive maintenance and iii) corrective maintenance. The goal is to optimize the maintenance policy by taking into account the imperfect monitoring data in order to minimize the expected discounted maintenance cost over an infinite time horizon. We formulate the problem as a POMDP where, at each time step, it should be decided whether or not to conduct a maintenance operation, and if so, which one. To keep the model general and flexible, we suppose that monitoring data are collected every K time steps (i.e. one observation epoch). The model is completed by a constraint imposing that only one maintenance operation can be conducted per observation epoch. Eventually, we solve it using a PBVI algorithm. The value function is approximated by interpolation of grid data points, and new relevant points are dynamically added into the grid where they most improve the value function. This approach is compared to a POMDP modeling based on approximate sample paths (ASP); when evaluated in different cost scenarios, the proposed approach systematically finds better maintenance policies for a comparable computation time. The computation of a lower bound finally proves that we are able to get the optimal value of the problem with satisfying precision.
Fichier principal
Vignette du fichier
ifacconf_v4_8pages_Matthieu_ROUX.pdf (420.57 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03702092 , version 1 (22-06-2022)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Matthieu Roux, Yiping Fang, A Barros. Maintenance Planning under Imperfect Monitoring: an Efficient POMDP Model Using Interpolated Value Function. IFAC-PapersOnLine, 2022, ⟨10.1016/j.ifacol.2022.09.012⟩. ⟨hal-03702092⟩
84 Consultations
102 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More