IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v135y2015icp55-63.html
   My bibliography  Save this article

Analytical method for optimization of maintenance policy based on available system failure data

Author

Listed:
  • Coria, V.H.
  • Maximov, S.
  • Rivas-Dávalos, F.
  • Melchor, C.L.
  • Guardado, J.L.

Abstract

An analytical optimization method for preventive maintenance (PM) policy with minimal repair at failure, periodic maintenance, and replacement is proposed for systems with historical failure time data influenced by a current PM policy. The method includes a new imperfect PM model based on Weibull distribution and incorporates the current maintenance interval T0 and the optimal maintenance interval T to be found. The Weibull parameters are analytically estimated using maximum likelihood estimation. Based on this model, the optimal number of PM and the optimal maintenance interval for minimizing the expected cost over an infinite time horizon are also analytically determined. A number of examples are presented involving different failure time data and current maintenance intervals to analyze how the proposed analytical optimization method for periodic PM policy performances in response to changes in the distribution of the failure data and the current maintenance interval.

Suggested Citation

  • Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.
    • Handle: RePEc:eee:reensy:v:135:y:2015:i:c:p:55-63
    DOI: 10.1016/j.ress.2014.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832014002750
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2014.11.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    2. Pintelon, L. M. & Gelders, L. F., 1992. "Maintenance management decision making," European Journal of Operational Research, Elsevier, vol. 58(3), pages 301-317, May.
    3. Castro, I.T., 2009. "A model of imperfect preventive maintenance with dependent failure modes," European Journal of Operational Research, Elsevier, vol. 196(1), pages 217-224, July.
    4. Balakrishnan, N. & Kateri, M., 2008. "On the maximum likelihood estimation of parameters of Weibull distribution based on complete and censored data," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2971-2975, December.
    5. Cavory, G. & Dupas, R. & Goncalves, G., 2001. "A genetic approach to the scheduling of preventive maintenance tasks on a single product manufacturing production line," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 135-146, December.
    6. XiaoFei, Lu & Min, Liu, 2014. "Hazard rate function in dynamic environment," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 50-60.
    7. Do, Phuc & Voisin, Alexandre & Levrat, Eric & Iung, Benoit, 2015. "A proactive condition-based maintenance strategy with both perfect and imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 22-32.
    8. Bruns, Peter, 2002. "Optimal maintenance strategies for systems with partial repair options and without assuming bounded costs," European Journal of Operational Research, Elsevier, vol. 139(1), pages 146-165, May.
    9. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    10. You, Ming-Yi & Li, Hongguang & Meng, Guang, 2011. "Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 590-598.
    11. Cho, Danny I. & Parlar, Mahmut, 1991. "A survey of maintenance models for multi-unit systems," European Journal of Operational Research, Elsevier, vol. 51(1), pages 1-23, March.
    12. Tian, Zhigang & Liao, Haitao, 2011. "Condition based maintenance optimization for multi-component systems using proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 581-589.
    13. Nakagawa, Toshio & Kowada, Masashi, 1983. "Analysis of a system with minimal repair and its application to replacement policy," European Journal of Operational Research, Elsevier, vol. 12(2), pages 176-182, February.
    14. Wang, Wenbin, 2012. "An overview of the recent advances in delay-time-based maintenance modelling," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 165-178.
    15. Jiang, Xiaomo & Yuan, Yong & Liu, Xian, 2013. "Bayesian inference method for stochastic damage accumulation modeling," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 126-138.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sánchez-Herguedas, Antonio & Mena-Nieto, Angel & Rodrigo-Muñoz, Francisco, 2021. "A new analytical method to optimise the preventive maintenance interval by using a semi-Markov process and z-transform with an application to marine diesel engines," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    2. de Jonge, Bram & Jakobsons, Edgars, 2018. "Optimizing block-based maintenance under random machine usage," European Journal of Operational Research, Elsevier, vol. 265(2), pages 703-709.
    3. Ágota Bányai, 2021. "Energy Consumption-Based Maintenance Policy Optimization," Energies, MDPI, vol. 14(18), pages 1-33, September.
    4. Sheu, Shey-Huei & Tsai, Hsin-Nan & Sheu, Uan-Yu & Zhang, Zhe George, 2019. "Optimal replacement policies for a system based on a one-cycle criterion," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    5. Martón, I. & Martorell, P. & Mullor, R. & Sánchez, A.I. & Martorell, S., 2016. "Optimization of test and maintenance of ageing components consisting of multiple items and addressing effectiveness," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 151-158.
    6. Francesco Corman & Sander Kraijema & Milinko Godjevac & Gabriel Lodewijks, 2017. "Optimizing preventive maintenance policy: A data-driven application for a light rail braking system," Journal of Risk and Reliability, , vol. 231(5), pages 534-545, October.
    7. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    8. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    2. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2015. "Multi-level predictive maintenance for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 83-94.
    3. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    4. Jiawen Hu & Zuhua Jiang & Haitao Liao, 2017. "Preventive maintenance of a batch production system under time-varying operational condition," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5681-5705, October.
    5. Zhang, Xiaohong & Zeng, Jianchao, 2017. "Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems," European Journal of Operational Research, Elsevier, vol. 262(2), pages 479-498.
    6. Olde Keizer, Minou C.A. & Flapper, Simme Douwe P. & Teunter, Ruud H., 2017. "Condition-based maintenance policies for systems with multiple dependent components: A review," European Journal of Operational Research, Elsevier, vol. 261(2), pages 405-420.
    7. Ece Zeliha Demirci & Joachim Arts & Geert-Jan Van Houtum, 2022. "A restless bandit approach for capacitated condition based maintenance scheduling," DEM Discussion Paper Series 22-01, Department of Economics at the University of Luxembourg.
    8. Tian, Zhigang & Liao, Haitao, 2011. "Condition based maintenance optimization for multi-component systems using proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 581-589.
    9. Zhu, Qiushi & Peng, Hao & Timmermans, Bas & van Houtum, Geert-Jan, 2017. "A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs," International Journal of Production Economics, Elsevier, vol. 193(C), pages 365-380.
    10. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2017. "Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 249-261.
    11. Levitin, Gregory & Finkelstein, Maxim & Huang, Hong-Zhong, 2019. "Scheduling of imperfect inspections for reliability critical systems with shock-driven defects and delayed failures," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 89-98.
    12. Zhuoqi Zhang & Su Wu & Binfeng Li & Seungchul Lee, 2015. "(, ) type maintenance policy for multi-component systems with failure interactions," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(6), pages 1051-1064, April.
    13. Berrade, M.D. & Scarf, P.A. & Cavalcante, C.A.V., 2018. "Conditional inspection and maintenance of a system with two interacting components," European Journal of Operational Research, Elsevier, vol. 268(2), pages 533-544.
    14. de Jonge, Bram & Klingenberg, Warse & Teunter, Ruud & Tinga, Tiedo, 2016. "Reducing costs by clustering maintenance activities for multiple critical units," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 93-103.
    15. Francesco Corman & Sander Kraijema & Milinko Godjevac & Gabriel Lodewijks, 2017. "Optimizing preventive maintenance policy: A data-driven application for a light rail braking system," Journal of Risk and Reliability, , vol. 231(5), pages 534-545, October.
    16. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper, 2016. "Clustering condition-based maintenance for systems with redundancy and economic dependencies," European Journal of Operational Research, Elsevier, vol. 251(2), pages 531-540.
    17. Zhou, Xiaojun & Huang, Kaimin & Xi, Lifeng & Lee, Jay, 2015. "Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 231-237.
    18. Seyedhosseini, Seyed Mohammad & Moakedi, Hamid & Shahanaghi, Kamran, 2018. "Imperfect inspection optimization for a two-component system subject to hidden and two-stage revealed failures over a finite time horizon," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 141-156.
    19. Shahraki, Ameneh Forouzandeh & Yadav, Om Prakash & Vogiatzis, Chrysafis, 2020. "Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    20. Yuri Merizalde & Luis Hernández-Callejo & Oscar Duque-Perez & Víctor Alonso-Gómez, 2019. "Maintenance Models Applied to Wind Turbines. A Comprehensive Overview," Energies, MDPI, vol. 12(2), pages 1-41, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:135:y:2015:i:c:p:55-63. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.