IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v92y2007i10p1413-1420.html
   My bibliography  Save this article

Bayesian networks for multilevel system reliability

Author

Listed:
  • Wilson, Alyson G.
  • Huzurbazar, Aparna V.

Abstract

Bayesian networks have recently found many applications in systems reliability; however, the focus has been on binary outcomes. In this paper we extend their use to multilevel discrete data and discuss how to make joint inference about all of the nodes in the network. These methods are applicable when system structures are too complex to be represented by fault trees. The methods are illustrated through four examples that are structured to clarify the scope of the problem.

Suggested Citation

  • Wilson, Alyson G. & Huzurbazar, Aparna V., 2007. "Bayesian networks for multilevel system reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1413-1420.
  • Handle: RePEc:eee:reensy:v:92:y:2007:i:10:p:1413-1420
    DOI: 10.1016/j.ress.2006.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832006001980
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2006.09.003?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. 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.
    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. Lei Jiang & Yiliu Liu & Xiaomin Wang & Mary Ann Lundteigen, 2019. "Operation-oriented reliability and availability evaluation for onboard high-speed train control system with dynamic Bayesian network," Journal of Risk and Reliability, , vol. 233(3), pages 455-469, June.
    2. Iamsumang, Chonlagarn & Mosleh, Ali & Modarres, Mohammad, 2018. "Monitoring and learning algorithms for dynamic hybrid Bayesian network in on-line system health management applications," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 118-129.
    3. Urbina, Angel & Mahadevan, Sankaran & Paez, Thomas L., 2011. "Quantification of margins and uncertainties of complex systems in the presence of aleatoric and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1114-1125.
    4. Taleb-Berrouane, Mohammed & Khan, Faisal & Amyotte, Paul, 2020. "Bayesian Stochastic Petri Nets (BSPN) - A new modelling tool for dynamic safety and reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Lu, Lu & Xu, Zhengguo & Wang, Wenhai & Sun, Youxian, 2013. "A new fault detection method for computer networks," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 45-51.
    6. Zhong, X. & Ichchou, M. & Saidi, A., 2010. "Reliability assessment of complex mechatronic systems using a modified nonparametric belief propagation algorithm," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1174-1185.
    7. Kondakci, Suleyman, 2015. "Analysis of information security reliability: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 275-299.
    8. Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    9. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    10. Song, Yufei & Mi, Jinhua & Cheng, Yuhua & Bai, Libing & Chen, Kai, 2020. "A dependency bounds analysis method for reliability assessment of complex system with hybrid uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    11. Bodda, Saran Srikanth & Gupta, Abhinav & Dinh, Nam, 2020. "Enhancement of risk informed validation framework for external hazard scenario," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    12. Dongjin Lee & Rong Pan, 2017. "Predictive maintenance of complex system with multi-level reliability structure," International Journal of Production Research, Taylor & Francis Journals, vol. 55(16), pages 4785-4801, August.
    13. Li, Mingyang & Liu, Jian & Li, Jing & Uk Kim, Byoung, 2014. "Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 158-164.
    14. Jia, Xiang & Guo, Bo, 2022. "Reliability analysis for complex system with multi-source data integration and multi-level data transmission," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    15. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    16. Wilson, Alyson G. & Anderson-Cook, Christine M. & Huzurbazar, Aparna V., 2011. "A case study for quantifying system reliability and uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1076-1084.
    17. Zhang, Xiaoge & Mahadevan, Sankaran & Deng, Xinyang, 2017. "Reliability analysis with linguistic data: An evidential network approach," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 111-121.
    18. 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.
    19. Li, Gong & Shi, Jing, 2012. "Applications of Bayesian methods in wind energy conversion systems," Renewable Energy, Elsevier, vol. 43(C), pages 1-8.
    20. Kwag, Shinyoung & Gupta, Abhinav & Dinh, Nam, 2018. "Probabilistic risk assessment based model validation method using Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 380-393.
    21. Kelly, Dana L. & Smith, Curtis L., 2009. "Bayesian inference in probabilistic risk assessment—The current state of the art," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 628-643.
    22. Cai, Baoping & Liu, Yonghong & Liu, Zengkai & Tian, Xiaojie & Dong, Xin & Yu, Shilin, 2012. "Using Bayesian networks in reliability evaluation for subsea blowout preventer control system," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 32-41.

    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. 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.
    3. Peng, Weiwen & Huang, Hong-Zhong & Li, Yanfeng & Zuo, Ming J. & Xie, Min, 2013. "Life cycle reliability assessment of new products—A Bayesian model updating approach," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 109-119.
    4. Quigley, John & Walls, Lesley, 2011. "Mixing Bayes and empirical Bayes inference to anticipate the realization of engineering concerns about variant system designs," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 933-941.
    5. Zhong, X. & Ichchou, M. & Saidi, A., 2010. "Reliability assessment of complex mechatronic systems using a modified nonparametric belief propagation algorithm," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1174-1185.
    6. Guo, Jian & (Steven) Li, Zhaojun & (Judy) Jin, Jionghua, 2018. "System reliability assessment with multilevel information using the Bayesian melding method," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 146-158.

    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:92:y:2007:i:10:p:1413-1420. 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.