IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v234y2020i3p470-486.html
   My bibliography  Save this article

A failure interaction model for multicomponent repairable systems

Author

Listed:
  • Vimal Vijayan
  • Sanjay K Chaturvedi
  • Ritesh Chandra

Abstract

Modeling of stochastic dependency among components in a repairable system is still a challenging task when dealing with the maintenance of multicomponent systems. With the help of stochastic dependency information, failure of a component brings attention to the components having strong interactions with the failed component. With this information, one can plan the maintenance of components in a better way. Since a change in failure probability of a component (due to deterioration or failure of a component in a given time interval) influences the failure probabilities of other components in the system, therefore, in this article, we consider probability of failure to represent the state of the component to model the stochastic dependency among components. We apply the Bayesian belief network to model such scenario of dependency among the components and present two case studies to compute various probabilities. In the first study, expert elicitation is being used, whereas the time between failure of the components is used in the second case to calculate failure probabilities. To illustrate the applicability of the proposed approach, one case study for each is presented. The first case study takes the case of an army truck through expert elicitation approach whereas the second case study deals with a rolling mill gearbox whose time between failure of components was available.

Suggested Citation

  • 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.
  • Handle: RePEc:sae:risrel:v:234:y:2020:i:3:p:470-486
    DOI: 10.1177/1748006X19897828
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X19897828
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X19897828?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. Robin P. Nicolai & Rommert Dekker, 2008. "Optimal Maintenance of Multi-component Systems: A Review," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 11, pages 263-286, Springer.
    2. Philip A. Scarf & Mohammed Deara, 2003. "Block replacement policies for a two‐component system with failure dependence," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(1), pages 70-87, February.
    3. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    4. 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.
    5. Dekker, R. & Wildeman, R. E. & van Egmond, R., 1996. "Joint replacement in an operational planning phase," European Journal of Operational Research, Elsevier, vol. 91(1), pages 74-88, May.
    6. Yontay, Petek & Pan, Rong, 2016. "A computational Bayesian approach to dependency assessment in system reliability," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 104-114.
    7. Zhang, Nan & Fouladirad, Mitra & Barros, Anne, 2018. "Optimal imperfect maintenance cost analysis of a two-component system with failure interactions," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 24-34.
    8. Bo Henry Lindqvist, 2008. "Maintenance of Repairable Systems," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 10, pages 235-261, Springer.
    9. Sun, Yong & Ma, Lin & Mathew, Joseph & Zhang, Sheng, 2006. "An analytical model for interactive failures," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 495-504.
    10. Wilson, Alyson G. & McNamara, Laura A. & Wilson, Gregory D., 2007. "Information integration for complex systems," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 121-130.
    11. Yan-Hui Lin & Yan-Fu Li & Enrico Zio, 2016. "Reliability assessment of systems subject to dependent degradation processes and random shocks," IISE Transactions, Taylor & Francis Journals, vol. 48(11), pages 1072-1085, November.
    12. Murthy, D. N. P. & Nguyen, D. G., 1985. "Study of a multi-component system with failure interaction," European Journal of Operational Research, Elsevier, vol. 21(3), pages 330-338, September.
    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. 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.

    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. 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.
    2. Van Horenbeek, Adriaan & Pintelon, Liliane, 2013. "A dynamic predictive maintenance policy for complex multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 39-50.
    3. Tazi, Nacef & Châtelet, Eric & Bouzidi, Youcef, 2018. "How combined performance and propagation of failure dependencies affect the reliability of a MSS," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 531-541.
    4. 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.
    5. Do, Phuc & Assaf, Roy & Scarf, Phil & Iung, Benoit, 2019. "Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 86-97.
    6. Markus Bohlin & Mathias Wärja, 2015. "Maintenance optimization with duration-dependent costs," Annals of Operations Research, Springer, vol. 224(1), pages 1-23, January.
    7. Vu, Hai Canh & Do, Phuc & Barros, Anne & Bérenguer, Christophe, 2014. "Maintenance grouping strategy for multi-component systems with dynamic contexts," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 233-249.
    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. Zhicheng Zhu & Yisha Xiang & Bo Zeng, 2021. "Multicomponent Maintenance Optimization: A Stochastic Programming Approach," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 898-914, July.
    10. Zhang, Nan & Cai, Kaiquan & Zhang, Jun & Wang, Tian, 2022. "A condition-based maintenance policy considering failure dependence and imperfect inspection for a two-component system," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    11. 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.
    12. Amrin, Andas & Zarikas, Vasileios & Spitas, Christos, 2018. "Reliability analysis and functional design using Bayesian networks generated automatically by an “Idea Algebra†framework," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 211-225.
    13. 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).
    14. Do, Phuc & Bérenguer, Christophe, 2020. "Conditional reliability-based importance measures," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    15. Andersen, Jesper Fink & Andersen, Anders Reenberg & Kulahci, Murat & Nielsen, Bo Friis, 2022. "A numerical study of Markov decision process algorithms for multi-component replacement problems," European Journal of Operational Research, Elsevier, vol. 299(3), pages 898-909.
    16. Zhang, Nan & Fouladirad, Mitra & Barros, Anne & Zhang, Jun, 2020. "Condition-based maintenance for a K-out-of-N deteriorating system under periodic inspection with failure dependence," European Journal of Operational Research, Elsevier, vol. 287(1), pages 159-167.
    17. Urbani, Michele & Brunelli, Matteo & Punkka, Antti, 2023. "An approach for bi-objective maintenance scheduling on a networked system with limited resources," European Journal of Operational Research, Elsevier, vol. 305(1), pages 101-113.
    18. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    19. Wei Peng & Xiaoling Zhang & Hong-Zhong Huang, 2016. "A failure rate interaction model for two-component systems based on copula function," Journal of Risk and Reliability, , vol. 230(3), pages 278-284, June.
    20. Scarf, Philip A., 1997. "On the application of mathematical models in maintenance," European Journal of Operational Research, Elsevier, vol. 99(3), pages 493-506, June.

    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:sae:risrel:v:234:y:2020:i:3:p:470-486. 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: SAGE Publications (email available below). General contact details of provider: .

    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.