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System-based risk analysis in a tram operating system: Integrating Monte Carlo simulation with the functional resonance analysis method

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  • Kaya, Gulsum Kubra
  • Ozturk, Fatih
  • Sariguzel, Emine Emel

Abstract

Safety management in tram systems is considered to be effective, but improvement is still necessary. This study applies the Functional Resonance Analysis Method (FRAM) by integrating Monte Carlo simulations and a criticality matrix to explore how the system-based perspective would enrich the quantified risk-orientated analysis in a tram operating system. The study models the tram operating system, estimates performance variability, identifies critical couplings and assesses risks presented by those couplings. The findings showed that a daily tram operating system runs with a degree of variability, in which tram driver- and pedestrian-related actions are the most variable ones. Performance variability in the system was most often due to the need for responding to unforeseen change. Such variability was usually essential to sustaining the tram system's successful operation. However, the findings also revealed that the tram operating system was exposed to several risks due to uncontrolled variability. The findings indicate that the system-based approach reveals all system interactions, considers aggregated variability and leads to comprehensive risk analysis of the tram operating system under various real-life working conditions.

Suggested Citation

  • Kaya, Gulsum Kubra & Ozturk, Fatih & Sariguzel, Emine Emel, 2021. "System-based risk analysis in a tram operating system: Integrating Monte Carlo simulation with the functional resonance analysis method," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021003550
    DOI: 10.1016/j.ress.2021.107835
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    References listed on IDEAS

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    Cited by:

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    8. Wang, Yanzhong & Xie, Bin & E, Shiyuan, 2022. "Adaptive relevance vector machine combined with Markov-chain-based importance sampling for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(C).

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