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A new modeling approach to the safety evaluation of N-modular redundant computer systems in presence of imperfect maintenance

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  • Flammini, Francesco
  • Marrone, Stefano
  • Mazzocca, Nicola
  • Vittorini, Valeria

Abstract

A large number of safety-critical control systems are based on N-modular redundant architectures, using majority voters on the outputs of independent computation units. In order to assess the compliance of these architectures with international safety standards, the frequency of hazardous failures must be analyzed by developing and solving proper formal models. Furthermore, the impact of maintenance faults has to be considered, since imperfect maintenance may degrade the safety integrity level of the system. In this paper, we present both a failure model for voting architectures based on Bayesian networks and a maintenance model based on continuous time Markov chains, and we propose to combine them according to a compositional multiformalism modeling approach in order to analyze the impact of imperfect maintenance on the system safety. We also show how the proposed approach promotes the reuse and the interchange of models as well the interchange of solving tools.

Suggested Citation

  • Flammini, Francesco & Marrone, Stefano & Mazzocca, Nicola & Vittorini, Valeria, 2009. "A new modeling approach to the safety evaluation of N-modular redundant computer systems in presence of imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(9), pages 1422-1432.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:9:p:1422-1432
    DOI: 10.1016/j.ress.2009.02.014
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    References listed on IDEAS

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    1. M M Hosseini & R M Kerr & R B Randall, 1999. "A hybrid maintenance model with imperfect inspection for a system with deterioration and Poisson failure," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(12), pages 1229-1243, December.
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    Cited by:

    1. Baoping Cai & Yonghong Liu & Zengkai Liu & Xiaojie Tian & Yanzhen Zhang & Renjie Ji, 2013. "Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1293-1311, July.
    2. Ding, Long & Wang, Hong & Jiang, Jin & Xu, Aidong, 2017. "SIL verification for SRS with diverse redundancy based on system degradation using reliability block diagram," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 170-187.
    3. Alebrant Mendes, Angélica & Coit, David W. & Duarte Ribeiro, José Luis, 2014. "Establishment of the optimal time interval between periodic inspections for redundant systems," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 148-165.
    4. Cai, Baoping & Liu, Yu & Fan, Qian, 2016. "A multiphase dynamic Bayesian networks methodology for the determination of safety integrity levels," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 105-115.
    5. Di Giandomenico, F. & Itria, M.L. & Masci, P. & Nostro, N., 2014. "Automated synthesis of dependable mediators for heterogeneous interoperable systems," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 220-232.
    6. 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.

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