IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v240y2026i2p641-653.html

Reliability analysis of phased-mission system with common cause failure based on discrete-time Bayesian network

Author

Listed:
  • Lili Bai
  • Jiaqi Shen
  • Yuning Qiu
  • Yan Zhang

Abstract

Discrete-time Bayesian networks (DTBN), as an extension of Bayesian networks, is an effective tool for analyzing the reliability of phased mission systems (PMS). Currently, the reliability analysis of phased-mission system (PMS) with common cause failures (CCF) based on discrete-time Bayesian networks (DTBN) is mostly implemented by adding events or nodes to represent the influence of CCF, which increases the complexity of system analysis to a certain extent. Therefore, in this paper, a new algorithm combining PMS-DTBN with Efficient Decomposition and Aggregation (EDA) method is proposed to simplify the process of system reliability analysis under CCF by reducing the size of the DTBN model. The model is applied to a concrete example about the first re-orbiting process of a geosynchronous orbit satellite to verify the practical applicability of the developed approach. Meanwhile, by comparing the calculation results with those of the Monte Carlo method, under the same equipment, the proposed method can ensure higher solution accuracy and computational efficiency, with the relative error constrained to less than 0.001%.

Suggested Citation

  • Lili Bai & Jiaqi Shen & Yuning Qiu & Yan Zhang, 2026. "Reliability analysis of phased-mission system with common cause failure based on discrete-time Bayesian network," Journal of Risk and Reliability, , vol. 240(2), pages 641-653, April.
  • Handle: RePEc:sae:risrel:v:240:y:2026:i:2:p:641-653
    DOI: 10.1177/1748006X251380917
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X251380917
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X251380917?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:sae:risrel:v:240:y:2026:i:2:p:641-653. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.