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Quantitative risk prognostics framework based on Petri Net and Bow-Tie models

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  • Vileiniskis, Marius
  • Remenyte-Prescott, Rasa

Abstract

A simulation framework based on the Petri Net model is proposed in this paper used for performing quantitative risk prognosis through extending the Bow-Tie model. A Petri Net model is built to include features, specific to assets, such as the condition of the asset, the projected operational usage, inspection and maintenance policies and degradation process, so that the future condition of the asset over time can be estimated. Several new Petri Net modelling features which advance the traditional Bow-Tie approach are proposed, such as asset usage generating and usage dependent transitions, and the possibility of entering evidence about the actual condition of the asset through the use of truncated distributions. Monte Carlo simulation method is used to simulate the developed Petri Net model over a selected time frame, in order to obtain statistics necessary to perform risk assessment using the Bow-Tie model. The paper reports on the overall proposed methodology and then focusses on the development of the Petri Net model. The methodology is applied in risk prognostics of operating an underground passenger lift. In particular, the combination of the Petri Net and the Bow-Tie models is illustrated to predict the likelihood and the consequences of an event when a lift gets stuck in a shaft between landings.

Suggested Citation

  • Vileiniskis, Marius & Remenyte-Prescott, Rasa, 2017. "Quantitative risk prognostics framework based on Petri Net and Bow-Tie models," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 62-73.
    • Handle: RePEc:eee:reensy:v:165:y:2017:i:c:p:62-73
    DOI: 10.1016/j.ress.2017.03.026
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    References listed on IDEAS

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    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2012. "Dynamic risk analysis using bow-tie approach," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 36-44.
    2. Darren Prescott & John Andrews, 2013. "A track ballast maintenance and inspection model for a rail network," Journal of Risk and Reliability, , vol. 227(3), pages 251-266, June.
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    Cited by:

    1. Xie, Shuyi & Dong, Shaohua & Chen, Yinuo & Peng, Yujie & Li, Xincai, 2021. "A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. Li, Weijun & Sun, Qiqi & Zhang, Jiwang & Zhang, Laibin, 2024. "Quantitative risk assessment of industrial hot work using Adaptive Bow Tie and Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    3. Wu, Daohua & Zheng, Wei, 2018. "Formal model-based quantitative safety analysis using timed Coloured Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 62-79.
    4. Jun Zhang & Haifeng Bian & Huanhuan Zhao & Xuexue Wang & Linlin Zhang & Yiping Bai, 2020. "Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines," IJERPH, MDPI, vol. 17(6), pages 1-17, March.
    5. Rungskunroch, Panrawee & Jack, Anson & Kaewunruen, Sakdirat, 2021. "Benchmarking on railway safety performance using Bayesian inference, decision tree and petri-net techniques based on long-term accidental data sets," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

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