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Multi-objective decision-making model based on CBM for an aircraft fleet with reliability constraint

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  • Lin Lin
  • Bin Luo
  • ShiSheng Zhong

Abstract

Modern production management patterns, in which multi-unit (e.g. an aircraft fleet) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision-making. To schedule a good maintenance plan, not only does the individual aircraft maintenance have to be considered, but also the maintenance of the other aircraft in fleet have to be taken into account. Condition-based maintenance (CBM) is a maintenance scheme which recommends maintenance decisions according to equipment status collected by condition monitor over a period of time. Evaluating risk is necessary for scheduling appropriate maintenance, avoiding aircraft losses and maintaining the repairable components at a high-reliable state. In this paper, a novel two-models-fusion framework is proposed to predict the reliability of aircraft structures subjected to fatigue loads. Furthermore, we established a fleet maintenance decision-making model based on CBM for the maintenance of fatigue structures. The model concentrates on both minimising fleet maintenance cost and maximising fleet availability, overcoming the shortcomings of traditional fleet CBM research, which has simply focused on one or the other of these parameters. Finally, a case study regarding a fleet of 10 aircraft is conducted, and the results indicated that the proposed model efficiently generates outcomes that meet the schedule requirements.

Suggested Citation

  • Lin Lin & Bin Luo & ShiSheng Zhong, 2018. "Multi-objective decision-making model based on CBM for an aircraft fleet with reliability constraint," International Journal of Production Research, Taylor & Francis Journals, vol. 56(14), pages 4831-4848, July.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:14:p:4831-4848
    DOI: 10.1080/00207543.2018.1467574
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    Cited by:

    1. Cheng, Jianda & Cheng, Minghui & Liu, Yan & Wu, Jun & Li, Wei & Frangopol, Dan M., 2024. "Knowledge transfer for adaptive maintenance policy optimization in engineering fleets based on meta-reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    2. J.P. Sprong & X. Jiang & H. Polinder, 2020. "Deployment of Prognostics to Optimize Aircraft Maintenance – A Literature Review," Journal of International Business Research and Marketing, Inovatus Services Ltd., vol. 5(4), pages 26-37, May.
    3. Marcello Fera & Raffaele Abbate & Mario Caterino & Pasquale Manco & Roberto Macchiaroli & Marta Rinaldi, 2020. "Economic and Environmental Sustainability for Aircrafts Service Life," Sustainability, MDPI, vol. 12(23), pages 1-17, December.

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