IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0207390.html
   My bibliography  Save this article

A multi-event combination maintenance model based on event correlation

Author

Listed:
  • Chunhui Guo
  • Chuan Lyu
  • Jiayu Chen
  • Dong Zhou

Abstract

Due to the complexity of large production systems, maintenance events are diverse, simultaneous and dynamic. Appropriate maintenance management of complex large production systems can guarantee high availability and save maintenance costs. However, current maintenance decision-making methods mainly focus on the maintenance events of single-components and series connection multi-components; little research pays attention to the combination maintenance of different maintenance events. Therefore, this paper proposes a multi-event combination maintenance model based on event correlation. First, the maintenance downtime and cost of three types of maintenance events under different maintenance beginning times and degrees are analysed. Then, shared maintenance downtime and cost models are established by maintenance event correlations. In addition, a multi-event combination maintenance model is constructed to achieve the goal of the highest availability and the lowest cost rate in both the decision-making cycle and the remaining life. Moreover, a particle swarm optimization algorithm based on interval segmentation for model solving is designed. Finally, a numerical example is presented to illustrate the model.

Suggested Citation

  • Chunhui Guo & Chuan Lyu & Jiayu Chen & Dong Zhou, 2018. "A multi-event combination maintenance model based on event correlation," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-24, November.
    • Handle: RePEc:plo:pone00:0207390
    DOI: 10.1371/journal.pone.0207390
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0207390
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0207390&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0207390?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
    ---><---

    References listed on IDEAS

    as
    1. Bloch-Mercier, Sophie, 2002. "A preventive maintenance policy with sequential checking procedure for a Markov deteriorating system," European Journal of Operational Research, Elsevier, vol. 142(3), pages 548-576, November.
    2. Naijun Sha & Rong Pan, 2014. "Bayesian analysis for step-stress accelerated life testing using weibull proportional hazard model," Statistical Papers, Springer, vol. 55(3), pages 715-726, August.
    3. David Assaf & J. George Shanthikumar, 1987. "Optimal Group Maintenance Policies with Continuous and Periodic Inspections," Management Science, INFORMS, vol. 33(11), pages 1440-1452, November.
    4. Zhao, Jianmin & Chan, A.H.C. & Roberts, C. & Madelin, K.B., 2007. "Reliability evaluation and optimisation of imperfect inspections for a component with multi-defects," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 65-73.
    5. Wang, Wenbin, 2007. "A two-stage prognosis model in condition based maintenance," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1177-1187, November.
    6. Berg, Menachem, 1976. "Optimal replacement policies for two-unit machines with increasing running costs 1," Stochastic Processes and their Applications, Elsevier, vol. 4(1), pages 89-106, January.
    7. Wildeman, R. E. & Dekker, R. & Smit, A. C. J. M., 1997. "A dynamic policy for grouping maintenance activities," European Journal of Operational Research, Elsevier, vol. 99(3), pages 530-551, June.
    8. Milia Habib & Farouk Yalaoui & Hicham Chehade & Iman Jarkass & Nazir Chebbo, 2017. "Multi-objective design optimisation of repairable -out-of- subsystems in series with redundant dependency," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7000-7021, December.
    9. Rabah Ammour & Edouard Leclercq & Eric Sanlaville & Dimitri Lefebvre, 2017. "State estimation of discrete event systems for RUL prediction issue," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7040-7057, December.
    10. Mengfei Fan & Zhiguo Zeng & Enrico Zio & Rui Kang & Ying Chen, 2017. "A stochastic hybrid systems based framework for modeling dependent failure processes," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-22, February.
    11. Ferreira, Rodrigo J.P. & de Almeida, Adiel Teixeira & Cavalcante, Cristiano A.V., 2009. "A multi-criteria decision model to determine inspection intervals of condition monitoring based on delay time analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 905-912.
    12. Faris M Alwan & Adam Baharum & Geehan S Hassan, 2013. "Reliability Measurement for Mixed Mode Failures of 33/11 Kilovolt Electric Power Distribution Stations," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    13. Yu Zhou & Gang Kou & Daji Ergu & Yi Peng, 2013. "Mission Availability for Bounded-Cumulative-Downtime System," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-10, July.
    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. Jin, Yuxue & Geng, Jie & Lv, Chuan & Chi, Ying & Zhao, Tingdi, 2023. "A methodology for equipment condition simulation and maintenance threshold optimization oriented to the influence of multiple events," Reliability Engineering and System Safety, Elsevier, vol. 229(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. 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.
    2. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    3. Dao, Cuong D. & Zuo, Ming J. & Pandey, Mayank, 2014. "Selective maintenance for multi-state series–parallel systems under economic dependence," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 240-249.
    4. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    5. Wang, Wenbin, 2013. "Models of inspection, routine service, and replacement for a serviceable one-component system," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 57-63.
    6. 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.
    7. Wooseung Jang & J. George Shanthikumar, 2002. "Stochastic allocation of inspection capacity to competitive processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(1), pages 78-94, February.
    8. Ayse Sena Eruguz & Tarkan Tan & Geert‐Jan van Houtum, 2017. "Optimizing usage and maintenance decisions for k‐out‐of‐n systems of moving assets," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(5), pages 418-434, August.
    9. Phuc Do & Christophe Bérenguer, 2022. "Residual life-based importance measures for predictive maintenance decision-making," Journal of Risk and Reliability, , vol. 236(1), pages 98-113, February.
    10. 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.
    11. Nguyen, Ho Si Hung & Do, Phuc & Vu, Hai-Canh & Iung, Benoit, 2019. "Dynamic maintenance grouping and routing for geographically dispersed production systems," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 392-404.
    12. W Wang, 2011. "Overview of a semi-stochastic filtering approach for residual life estimation with applications in condition based maintenance," Journal of Risk and Reliability, , vol. 225(2), pages 185-197, June.
    13. Le Son, Khanh & Fouladirad, Mitra & Barros, Anne & Levrat, Eric & Iung, Benoît, 2013. "Remaining useful life estimation based on stochastic deterioration models: A comparative study," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 165-175.
    14. Vimal Vijayan & Sanjay K Chaturvedi, 2021. "Multi-component maintenance grouping optimization based on stochastic dependency," Journal of Risk and Reliability, , vol. 235(2), pages 293-305, April.
    15. Zhou, Zhi-Jie & Hu, Chang-Hua & Xu, Dong-Ling & Chen, Mao-Yin & Zhou, Dong-Hua, 2010. "A model for real-time failure prognosis based on hidden Markov model and belief rule base," European Journal of Operational Research, Elsevier, vol. 207(1), pages 269-283, November.
    16. Yonit Barron, 2018. "Group maintenance policies for an R-out-of-N system with phase-type distribution," Annals of Operations Research, Springer, vol. 261(1), pages 79-105, February.
    17. Vimal Vijayan & Sanjay K Chaturvedi & Ritesh Chandra, 2020. "A failure interaction model for multicomponent repairable systems," Journal of Risk and Reliability, , vol. 234(3), pages 470-486, June.
    18. Panagiotidou, S. & Tagaras, G., 2012. "Optimal integrated process control and maintenance under general deterioration," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 58-70.
    19. Zafar Hameed & Jørn Vatn, 2012. "Role of grouping in the development of an overall maintenance optimization framework for offshore wind turbines," Journal of Risk and Reliability, , vol. 226(6), pages 584-601, December.
    20. Markus Bohlin & Mathias Wärja, 2015. "Maintenance optimization with duration-dependent costs," Annals of Operations Research, Springer, vol. 224(1), pages 1-23, January.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0207390. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.