Predictive maintenance for multi-component systems of repairables with Remaining-Useful-Life prognostics and a limited stock of spare components. de Pater, I. & Mitici, M. Reliability Engineering & System Safety, 214:107761, October, 2021. Paper doi abstract bibtex Aircraft maintenance is undergoing a paradigm shift towards predictive maintenance, where the use of sensor data and Remaining-Useful-Life prognostics are central. This paper proposes an integrated approach for predictive aircraft maintenance planning for multiple multi-component systems, where the components are repairables. First, model-based Remaining-Useful-Life prognostics are developed. These prognostics are updated over time, as more sensor data become available. Then, a rolling horizon integer linear program is developed for the maintenance planning of multiple multi-component systems. This model integrates the Remaining-Useful-Life prognostics with the management of a limited stock of spare repairable components. The maintenance of the multiple systems is linked through the availability of spare components and shared maintenance time slots. Our approach is illustrated for a fleet of aircraft, each equipped with a Cooling System consisting of four Cooling Units. For an aircraft to be operational, a minimum of two Cooling Units out of the four need to be operational. The maintenance planning results show that our integrated approach reduces the costs with maintenance by 48% relative to a corrective maintenance strategy and by 30% relative to a preventive maintenance strategy. Moreover, using predictive maintenance, components are replaced in anticipation of failure without wasting their useful life. In general, our approach provides a roadmap from Remaining-Useful-Life prognostics to maintenance planning for multiple multi-component systems of repairables with a limited stock of spares.
@article{de_pater_predictive_2021,
title = {Predictive maintenance for multi-component systems of repairables with {Remaining}-{Useful}-{Life} prognostics and a limited stock of spare components},
volume = {214},
issn = {0951-8320},
url = {https://www.sciencedirect.com/science/article/pii/S095183202100288X},
doi = {10.1016/j.ress.2021.107761},
abstract = {Aircraft maintenance is undergoing a paradigm shift towards predictive maintenance, where the use of sensor data and Remaining-Useful-Life prognostics are central. This paper proposes an integrated approach for predictive aircraft maintenance planning for multiple multi-component systems, where the components are repairables. First, model-based Remaining-Useful-Life prognostics are developed. These prognostics are updated over time, as more sensor data become available. Then, a rolling horizon integer linear program is developed for the maintenance planning of multiple multi-component systems. This model integrates the Remaining-Useful-Life prognostics with the management of a limited stock of spare repairable components. The maintenance of the multiple systems is linked through the availability of spare components and shared maintenance time slots. Our approach is illustrated for a fleet of aircraft, each equipped with a Cooling System consisting of four Cooling Units. For an aircraft to be operational, a minimum of two Cooling Units out of the four need to be operational. The maintenance planning results show that our integrated approach reduces the costs with maintenance by 48\% relative to a corrective maintenance strategy and by 30\% relative to a preventive maintenance strategy. Moreover, using predictive maintenance, components are replaced in anticipation of failure without wasting their useful life. In general, our approach provides a roadmap from Remaining-Useful-Life prognostics to maintenance planning for multiple multi-component systems of repairables with a limited stock of spares.},
language = {en},
urldate = {2021-09-28},
journal = {Reliability Engineering \& System Safety},
author = {de Pater, Ingeborg and Mitici, Mihaela},
month = oct,
year = {2021},
keywords = {Aircraft Cooling Units, Aircraft predictive maintenance of repairables, Management of spare components, Multiple multi-component systems, RUL prognostics},
pages = {107761},
}
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These prognostics are updated over time, as more sensor data become available. Then, a rolling horizon integer linear program is developed for the maintenance planning of multiple multi-component systems. This model integrates the Remaining-Useful-Life prognostics with the management of a limited stock of spare repairable components. The maintenance of the multiple systems is linked through the availability of spare components and shared maintenance time slots. Our approach is illustrated for a fleet of aircraft, each equipped with a Cooling System consisting of four Cooling Units. For an aircraft to be operational, a minimum of two Cooling Units out of the four need to be operational. The maintenance planning results show that our integrated approach reduces the costs with maintenance by 48% relative to a corrective maintenance strategy and by 30% relative to a preventive maintenance strategy. 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