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Efficient availability assessment of reconfigurable multi-state systems with interdependencies

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  • George-Williams, Hindolo
  • Patelli, Edoardo

Abstract

Realistic engineering systems often possess attributes that complicate their availability assessment. Notable examples being complex topology, multi-state behaviour, component interdependencies, and interactions with external phenomena. For such systems, analytical techniques have limited applicability, and efficient simulation techniques are, therefore, required. In this paper, a novel load-flow simulation approach is proposed to simplify the availability assessment of realistic engineering systems. The approach is simple and generally applicable to systems, including those with limited maintenance teams, reconfiguration requirements, and multiple commodity flows. A novel metric for assessing maintenance inadequacy and a real-time component ranking procedure are also introduced. In real-time ranking, failed components are assigned maintenance priorities during simulation in accordance with how much their availability improves system performance and how many idle maintenance teams there are. This eliminates the need for component importance ranking algorithms prior to simulation, which for some systems may be unnecessary. The applicability of the approach is demonstrated by analysing an offshore plant producing oil, gas, and water. The solution obtained is compared against another Monte Carlo simulation-based solution that requires the enumeration of the plant’s cut-sets. The proposed approach is shown to be more intuitive, robust to human-induced errors, and require less human effort.

Suggested Citation

  • George-Williams, Hindolo & Patelli, Edoardo, 2017. "Efficient availability assessment of reconfigurable multi-state systems with interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 431-444.
  • Handle: RePEc:eee:reensy:v:165:y:2017:i:c:p:431-444
    DOI: 10.1016/j.ress.2017.05.010
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    References listed on IDEAS

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    1. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    2. Adachi, Takao & Ellingwood, Bruce R., 2008. "Serviceability of earthquake-damaged water systems: Effects of electrical power availability and power backup systems on system vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 78-88.
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    4. Feng, Geng & Patelli, Edoardo & Beer, Michael & Coolen, Frank P.A., 2016. "Imprecise system reliability and component importance based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 116-125.
    5. George-Williams, Hindolo & Patelli, Edoardo, 2016. "A hybrid load flow and event driven simulation approach to multi-state system reliability evaluation," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 351-367.
    6. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    7. 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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    Cited by:

    1. Huang, Xianzhen & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2019. "A heuristic survival signature based approach for reliability-redundancy allocation," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 511-517.
    2. Liu, Yu & Chen, Yiming & Jiang, Tao, 2018. "On sequence planning for selective maintenance of multi-state systems under stochastic maintenance durations," European Journal of Operational Research, Elsevier, vol. 268(1), pages 113-127.
    3. Zhang, Yongjin & Zhao, Ming & Zhang, Yanjun & Pan, Ruilin & Cai, Jing, 2020. "Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers," European Journal of Operational Research, Elsevier, vol. 283(2), pages 491-510.
    4. Hindolo George-Williams & Geng Feng & Frank PA Coolen & Michael Beer & Edoardo Patelli, 2019. "Extending the survival signature paradigm to complex systems with non-repairable dependent failures," Journal of Risk and Reliability, , vol. 233(4), pages 505-519, August.

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