IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v31y2020i3d10.1007_s10845-019-01475-y.html
   My bibliography  Save this article

Optimization of preventive maintenance for series manufacturing system by differential evolution algorithm

Author

Listed:
  • Xiaofeng Wang

    (School of Intelligent Manufacturing, Changchun Sci-Tech University)

  • Shu Guo

    (School of Intelligent Manufacturing, Changchun Sci-Tech University)

  • Jian Shen

    (School of Intelligent Manufacturing, Changchun Sci-Tech University)

  • Yang Liu

    (School of Intelligent Manufacturing, Changchun Sci-Tech University)

Abstract

The costs of preventive maintenance have been extensively studied by scholars across all preventive optimization model disciplines. However, one phenomenon fails to be fully studied: breakdown and breakdown maintenance costs. We set out to fill this gap in this study. This study considered the cost of equipment preventive maintenance, and the breakdown maintenance cost caused by an accidental breakdown. In order to more accurately establish the reliability model of equipment breakdown, the three-parameter Weibull distribution was applied to set up the reliability model of equipment and the differential evolution algorithm was adopted to optimize the parameters. On this basis, preventive maintenance was regarded as imperfect maintenance in the study of preventive maintenance strategies for single equipment. In consideration of the combined influence of preventive maintenance and breakdown maintenance, a maintenance strategy in which preventive maintenance times N served as the decision variable was obtained to build a mathematical model on benefit expectation of single equipment in unit time. Based on the research of single equipment, a further study was performed on the multi-equipment series system. Moreover, two strategies were given, both of which use preventive maintenance times N as the decision variable. The first strategy is to take the average cost rate of the system under long-term operation as the optimization objective, while the second strategy is to apply single component maintenance strategy in series system. In the numerical example study, a series manufacturing system composed of two devices was chosen as the research object. Interestingly, we discussed the effect of initial conditions of two-parameter DE on output results. After acquiring the optimal initialization parameters, the failure rate function was achieved by the DE to estimate the parameters of three-parameter Weibull distribution. Meanwhile, the maintenance times N was optimized according to the two strategies respectively. The best result were selected from the results of both strategies based on availability. Thus, the validity and practicability of the proposed research methods are verified.

Suggested Citation

  • Xiaofeng Wang & Shu Guo & Jian Shen & Yang Liu, 2020. "Optimization of preventive maintenance for series manufacturing system by differential evolution algorithm," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 745-757, March.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:3:d:10.1007_s10845-019-01475-y
    DOI: 10.1007/s10845-019-01475-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-019-01475-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-019-01475-y?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. Zhang, Mimi & Gaudoin, Olivier & Xie, Min, 2015. "Degradation-based maintenance decision using stochastic filtering for systems under imperfect maintenance," European Journal of Operational Research, Elsevier, vol. 245(2), pages 531-541.
    2. V. Jayabalan & Dipak Chaudhuri, 1992. "Optimal maintenance and replacement policy for a deteriorating system with increased mean downtime," Naval Research Logistics (NRL), John Wiley & Sons, vol. 39(1), pages 67-78, February.
    3. Dui, Hongyan & Si, Shubin & Yam, Richard C.M., 2017. "A cost-based integrated importance measure of system components for preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 98-104.
    4. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    5. 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.
    6. Vladimir Stojanovic & Novak Nedic, 2016. "A Nature Inspired Parameter Tuning Approach to Cascade Control for Hydraulically Driven Parallel Robot Platform," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 332-347, January.
    7. Nourelfath, Mustapha & Châtelet, Eric & Nahas, Nabil, 2012. "Joint redundancy and imperfect preventive maintenance optimization for series–parallel multi-state degraded systems," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 51-60.
    8. Mahmood Shafiee & Maxim Finkelstein & Ming Zuo, 2013. "Optimal burn-in and preventive maintenance warranty strategies with time-dependent maintenance costs," IISE Transactions, Taylor & Francis Journals, vol. 45(9), pages 1024-1033.
    9. Zhou, Xiaojun & Xi, Lifeng & Lee, Jay, 2007. "Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation," Reliability Engineering and System Safety, Elsevier, vol. 92(4), pages 530-534.
    10. Aghezzaf, El-Houssaine & Khatab, Abdelhakim & Tam, Phuoc Le, 2016. "Optimizing production and imperfect preventive maintenance planning׳s integration in failure-prone manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 190-198.
    11. A. Khatab, 2018. "Maintenance optimization in failure-prone systems under imperfect preventive maintenance," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 707-717, March.
    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. Liu, Gehui & Chen, Shaokuan & Jin, Hua & Liu, Shuang, 2021. "Optimum opportunistic maintenance schedule incorporating delay time theory with imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    2. Ye, Zhenggeng & Yang, Hui & Cai, Zhiqiang & Si, Shubin & Zhou, Fuli, 2021. "Performance evaluation of serial-parallel manufacturing systems based on the impact of heterogeneous feedstocks on machine degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    3. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Liu, Gehui & Chen, Shaokuan & Ho, Tinkin & Ran, Xinchen & Mao, Baohua & Lan, Zhen, 2022. "Optimum opportunistic maintenance schedule over variable horizons considering multi-stage degradation and dynamic strategy," Reliability Engineering and System Safety, Elsevier, vol. 225(C).

    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. Zhou, Xiaojun & Wu, Changjie & Li, Yanting & Xi, Lifeng, 2016. "A preventive maintenance model for leased equipment subject to internal degradation and external shock damage," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 1-7.
    3. Wu, Fan & Niknam, Seyed A. & Kobza, John E., 2015. "A cost effective degradation-based maintenance strategy under imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 234-243.
    4. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    5. Lin, Zu-Liang & Huang, Yeu-Shiang & Fang, Chih-Chiang, 2015. "Non-periodic preventive maintenance with reliability thresholds for complex repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 145-156.
    6. Xian Zhao & Xinqian Huang & Jinglei Sun, 2020. "Reliability modeling and maintenance optimization for the two-unit system with preset self-repairing mechanism," Journal of Risk and Reliability, , vol. 234(2), pages 221-234, April.
    7. Lee, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    8. Zhengxin Zhang & Xiaosheng Si & Changhua Hu & Xiangyu Kong, 2015. "Degradation modeling–based remaining useful life estimation: A review on approaches for systems with heterogeneity," Journal of Risk and Reliability, , vol. 229(4), pages 343-355, August.
    9. Ji Hwan Cha & Maxim Finkelstein, 2020. "On optimal life extension for degrading systems," Journal of Risk and Reliability, , vol. 234(3), pages 487-495, June.
    10. Liu, Gehui & Chen, Shaokuan & Ho, Tinkin & Ran, Xinchen & Mao, Baohua & Lan, Zhen, 2022. "Optimum opportunistic maintenance schedule over variable horizons considering multi-stage degradation and dynamic strategy," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    11. Doostparast, Mohammad & Kolahan, Farhad & Doostparast, Mahdi, 2014. "A reliability-based approach to optimize preventive maintenance scheduling for coherent systems," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 98-106.
    12. Dai, Anshu & Wang, Xin & Li, Yu & Li, Ting & He, Shuguang, 2023. "Design of a performance-based warranty policy with replacement–repair strategy and cumulative cost threshold," International Journal of Production Economics, Elsevier, vol. 255(C).
    13. Xiaohui Chen & Lin Zhang & Ze Zhang, 2020. "An integrated model for maintenance policies and production scheduling based on immune–culture algorithm," Journal of Risk and Reliability, , vol. 234(5), pages 651-663, October.
    14. Insua, David Rios & Ruggeri, Fabrizio & Soyer, Refik & Wilson, Simon, 2020. "Advances in Bayesian decision making in reliability," European Journal of Operational Research, Elsevier, vol. 282(1), pages 1-18.
    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. Liu, Gehui & Chen, Shaokuan & Jin, Hua & Liu, Shuang, 2021. "Optimum opportunistic maintenance schedule incorporating delay time theory with imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    17. Mosayebi Omshi, E. & Grall, A. & Shemehsavar, S., 2020. "A dynamic auto-adaptive predictive maintenance policy for degradation with unknown parameters," European Journal of Operational Research, Elsevier, vol. 282(1), pages 81-92.
    18. Hu, Jiawen & Jiang, Zuhua & Liao, Haitao, 2017. "Preventive maintenance of a single machine system working under piecewise constant operating condition," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 105-115.
    19. Jiawen Hu & Zuhua Jiang & Hong Wang, 2017. "Joint Optimization of Production Plan and Preventive Maintenance Schedule by Stackelberg Game," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-28, August.
    20. Thiago Lima de Barros & Rodrigo Sampaio Lopes, 2021. "Continuous improvement of imperfect maintenance actions in PAS and PAR models," Journal of Risk and Reliability, , vol. 235(5), pages 941-958, October.

    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:spr:joinma:v:31:y:2020:i:3:d:10.1007_s10845-019-01475-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.