Prognostic-based Maintenance Optimization in Complex Systems with Resource Limitation Constraints

Junkai He, Miguel F. Anjos, Makhlouf Hadji, Selma Khebbache

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper is concerned with prognostic information for maintenance optimization in complex systems. At each stage of such a system, we consider redundant components used as backup to guarantee the system’s availability. The Remaining Useful Life (RUL/prognostic information) of components is used to evaluate each component’s redundancy. We address RUL-based maintenance optimization under resource limitation to ensure the availability of the system such that production demands can be satisfied in a given maintenance planning horizon. We propose a mixed-integer linear programming approach to minimize the overall cost. Our numerical results on test instances show the efficiency of the proposed approach to attain optimal solutions.

Original languageEnglish
Title of host publicationICORES 2022 - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems
EditorsFederico Liberatore, Greg H. Parlier, Marc Demange
PublisherScience and Technology Publications, Lda
Pages169-176
Number of pages8
ISBN (Print)9789897585487
DOIs
Publication statusPublished - 1 Jan 2022
Externally publishedYes
Event11th International Conference on Operations Research and Enterprise Systems, ICORES 2022 - Virtual, Online
Duration: 3 Feb 20225 Feb 2022

Publication series

NameInternational Conference on Operations Research and Enterprise Systems
ISSN (Electronic)2184-4372

Conference

Conference11th International Conference on Operations Research and Enterprise Systems, ICORES 2022
CityVirtual, Online
Period3/02/225/02/22

Keywords

  • Complex System
  • Optimization
  • Predictive Maintenance
  • Prognostic Information
  • Remaining Useful Life
  • Resource Limitation

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