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Methodological developments for probabilistic risk analyses of socio-technical systems

Author

Listed:
  • A Léger
  • P Weber
  • E Levrat
  • C Duval
  • R Farret
  • B Iung

Abstract

Nowadays, the risk analysis of critical systems cannot be focused only on a technical dimension. Indeed, well-known accidents in nuclear or aerospace areas underlined initiating causes also related to technical and organizational viewpoints. This led to the development of methods for risk assessment considering three main aspects on the system resources: the technical process, the operator constraining the process, and the organization constraining human actions on the process. However, only few scientific works have tried to join these methods in a unique and global approach. Thus this paper focuses on a methodology that aims to achieve the integration of the different methods in order to assess the risks probabilistically. The integration is based on (a) system knowledge structuring and (b) its unified modelling by means of Bayesian networks also supporting quantification and simulation phases. The methodology is applied to an industrial case to show its feasibility and to draw conclusions regarding the model relevance for system risk analysis. The results of the methodology can be used by decision makers to prioritize their actions when faced with potential or real risks.

Suggested Citation

  • A Léger & P Weber & E Levrat & C Duval & R Farret & B Iung, 2009. "Methodological developments for probabilistic risk analyses of socio-technical systems," Journal of Risk and Reliability, , vol. 223(4), pages 313-332, December.
    • Handle: RePEc:sae:risrel:v:223:y:2009:i:4:p:313-332
    DOI: 10.1243/1748006XJRR230
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    References listed on IDEAS

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    1. Galán, S.F. & Mosleh, A. & Izquierdo, J.M., 2007. "Incorporating organizational factors into probabilistic safety assessment of nuclear power plants through canonical probabilistic models," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 1131-1138.
    2. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    3. Gregoriades, Andreas & Sutcliffe, Alistair, 2008. "Workload prediction for improved design and reliability of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 530-549.
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    1. Medina-Oliva, G. & Weber, P. & Iung, B., 2013. "PRM-based patterns for knowledge formalisation of industrial systems to support maintenance strategies assessment," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 38-56.

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