IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v223y2009i4p313-332.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1243/1748006XJRR230
    Download Restriction: no
    File URL: https://libkey.io/10.1243/1748006XJRR230?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pan, Yue & Ou, Shenwei & Zhang, Limao & Zhang, Wenjing & Wu, Xianguo & Li, Heng, 2019. "Modeling risks in dependent systems: A Copula-Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 416-431.
    2. Rogerson, Ellen C. & Lambert, James H., 2012. "Prioritizing risks via several expert perspectives with application to runway safety," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 22-34.
    3. Chiming Guo & Shiyu Gong & Lin Tan & Bo Guo, 2012. "Extended GTST‐MLD for Aerospace System Safety Analysis," Risk Analysis, John Wiley & Sons, vol. 32(6), pages 1060-1071, June.
    4. Ibsen Chivatá Cárdenas & Saad S.H. Al‐Jibouri & Johannes I.M. Halman & Frits A. van Tol, 2014. "Modeling Risk‐Related Knowledge in Tunneling Projects," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 323-339, February.
    5. Marquez, David & Neil, Martin & Fenton, Norman, 2010. "Improved reliability modeling using Bayesian networks and dynamic discretization," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 412-425.
    6. 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.
    7. Vimal Vijayan & Sanjay K Chaturvedi, 2021. "Multi-component maintenance grouping optimization based on stochastic dependency," Journal of Risk and Reliability, , vol. 235(2), pages 293-305, April.
    8. Vimal Vijayan & Sanjay K Chaturvedi & Ritesh Chandra, 2020. "A failure interaction model for multicomponent repairable systems," Journal of Risk and Reliability, , vol. 234(3), pages 470-486, June.
    9. Michail Cheliotis & Evangelos Boulougouris & Nikoletta L Trivyza & Gerasimos Theotokatos & George Livanos & George Mantalos & Athanasios Stubos & Emmanuel Stamatakis & Alexandros Venetsanos, 2021. "Review on the Safe Use of Ammonia Fuel Cells in the Maritime Industry," Energies, MDPI, vol. 14(11), pages 1-20, May.
    10. Carole Duval & Geoffrey Fallet-Fidry & Benoît Iung & Philippe Weber & Eric Levrat, 2012. "A Bayesian network-based integrated risk analysis approach for industrial systems: application to heat sink system and prospects development," Journal of Risk and Reliability, , vol. 226(5), pages 488-507, October.
    11. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    12. Ait Mokhtar, El Hassene & Laggoune, Radouane & Chateauneuf, Alaa, 2023. "Imperfect maintenance modeling and assessment of repairable multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    13. Iamsumang, Chonlagarn & Mosleh, Ali & Modarres, Mohammad, 2018. "Monitoring and learning algorithms for dynamic hybrid Bayesian network in on-line system health management applications," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 118-129.
    14. Daniele Codetta-Raiteri & Luigi Portinale, 2014. "Approaching dynamic reliability with predictive and diagnostic purposes by exploiting dynamic Bayesian networks," Journal of Risk and Reliability, , vol. 228(5), pages 488-503, October.
    15. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    16. Maria Elena De Giuli & Alessandro Greppi & Marina Resta, 2019. "An Object-Oriented Bayesian Framework for the Detection of Market Drivers," Risks, MDPI, vol. 7(1), pages 1-18, January.
    17. Xiahou, Tangfan & Zheng, Yi-Xuan & Liu, Yu & Chen, Hong, 2023. "Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    18. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    19. Zhong, Shengtong & Langseth, Helge & Nielsen, Thomas Dyhre, 2014. "A classification-based approach to monitoring the safety of dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 61-71.
    20. Bandeira, Michelle Carvalho Galvão Silva Pinto & Correia, Anderson Ribeiro & Martins, Marcelo Ramos, 2018. "General model analysis of aeronautical accidents involving human and organizational factors," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 137-146.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:risrel:v:223:y:2009:i:4:p:313-332. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.