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Authors: Junkai He 1 ; Miguel F. Anjos 2 ; Makhlouf Hadji 1 and Selma Khebbache 1

Affiliations: 1 Technological Research Institute SystemX, 8 Avenue de la Vauve, 91120 Palaiseau, France ; 2 School of Mathematics, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, Scotland, U.K.

Keyword(s): Predictive Maintenance, Optimization, Complex System, Prognostic Information, Remaining Useful Life, Resource Limitation.

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.

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Paper citation in several formats:
He, J.; Anjos, M.; Hadji, M. and Khebbache, S. (2022). Prognostic-based Maintenance Optimization in Complex Systems with Resource Limitation Constraints. In Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - ICORES; ISBN 978-989-758-548-7; ISSN 2184-4372, SciTePress, pages 169-176. DOI: 10.5220/0010829100003117

@conference{icores22,
author={Junkai He. and Miguel F. Anjos. and Makhlouf Hadji. and Selma Khebbache.},
title={Prognostic-based Maintenance Optimization in Complex Systems with Resource Limitation Constraints},
booktitle={Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - ICORES},
year={2022},
pages={169-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010829100003117},
isbn={978-989-758-548-7},
issn={2184-4372},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - ICORES
TI - Prognostic-based Maintenance Optimization in Complex Systems with Resource Limitation Constraints
SN - 978-989-758-548-7
IS - 2184-4372
AU - He, J.
AU - Anjos, M.
AU - Hadji, M.
AU - Khebbache, S.
PY - 2022
SP - 169
EP - 176
DO - 10.5220/0010829100003117
PB - SciTePress

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