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A model for preventive maintenance planning by genetic algorithms based in cost and reliability

Author

Listed:
  • Lapa, Celso Marcelo F.
  • Pereira, Cláudio Márcio N.A.
  • de Barros, Márcio Paes

Abstract

This work has two important goals. The first one is to present a novel methodology for preventive maintenance policy evaluation based upon a cost-reliability model, which allows the use of flexible intervals between maintenance interventions. Such innovative features represents an advantage over the traditional methodologies as it allows a continuous fitting of the schedules in order to better deal with the components failure rates. The second goal is to automatically optimize the preventive maintenance policies, considering the proposed methodology for systems evaluation.

Suggested Citation

  • Lapa, Celso Marcelo F. & Pereira, Cláudio Márcio N.A. & de Barros, Márcio Paes, 2006. "A model for preventive maintenance planning by genetic algorithms based in cost and reliability," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 233-240.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:2:p:233-240
    DOI: 10.1016/j.ress.2005.01.004
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    Citations

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    Cited by:

    1. Ye, Zhisheng & Li, Zhizhong & Xie, Min, 2010. "Some improvements on adaptive genetic algorithms for reliability-related applications," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 120-126.
    2. Certa, Antonella & Galante, Giacomo & Lupo, Toni & Passannanti, Gianfranco, 2011. "Determination of Pareto frontier in multi-objective maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 861-867.
    3. Gao, Yicong & Feng, Yixiong & Zhang, Zixian & Tan, Jianrong, 2015. "An optimal dynamic interval preventive maintenance scheduling for series systems," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 19-30.
    4. Do, Phuc & Vu, Hai Canh & Barros, Anne & Bérenguer, Christophe, 2015. "Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 56-67.
    5. Koutras, V.P. & Malefaki, S. & Platis, A.N., 2017. "Optimization of the dependability and performance measures of a generic model for multi-state deteriorating systems under maintenance," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 73-86.
    6. Huang, Zhouchun & Zheng, Qipeng Phil, 2020. "A multistage stochastic programming approach for preventive maintenance scheduling of GENCOs with natural gas contract," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1036-1051.
    7. Zhao, Xufeng & Al-Khalifa, Khalifa N. & Magid Hamouda, Abdel & Nakagawa, Toshio, 2017. "Age replacement models: A summary with new perspectives and methods," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 95-105.
    8. Samrout, M. & Châtelet, E. & Kouta, R. & Chebbo, N., 2009. "Optimization of maintenance policy using the proportional hazard model," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 44-52.
    9. Chou, Jui-Sheng & Le, Thanh-Son, 2011. "Reliability-based performance simulation for optimized pavement maintenance," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1402-1410.
    10. Khaled Alhamad & Yousuf Alkhezi, 2024. "Hybrid Genetic Algorithm and Tabu Search for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants," Mathematics, MDPI, vol. 12(12), pages 1-26, June.
    11. Mohammad Doostparast & Farhad Kolahan & Mahdi Doostparast, 2015. "Optimisation of PM scheduling for multi-component systems – a simulated annealing approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1199-1207, May.

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