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Radyban: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks

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  • Montani, S.
  • Portinale, L.
  • Bobbio, A.
  • Codetta-Raiteri, D.

Abstract

In this paper, we present Radyban (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained.

Suggested Citation

  • Montani, S. & Portinale, L. & Bobbio, A. & Codetta-Raiteri, D., 2008. "Radyban: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 922-932.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:7:p:922-932
    DOI: 10.1016/j.ress.2007.03.013
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    References listed on IDEAS

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    1. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
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    4. F De Carlo & O Borgia & M Tucci, 2011. "Risk-based inspections enhanced with Bayesian networks," Journal of Risk and Reliability, , vol. 225(3), pages 375-386, September.
    5. 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.
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    10. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.
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    12. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2013. "Risk-based design of process systems using discrete-time Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 5-17.
    13. 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.
    14. 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.
    15. Amir Masoud Mirhosseini & S. Adib Nazari & A. Maghsoud Pour & S. Etemadi Haghighi & M. Zareh, 2019. "Probabilistic failure analysis of hot gas path in a heavy-duty gas turbine using Bayesian networks," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1173-1185, October.

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