IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v94y2009i2p445-455.html
   My bibliography  Save this article

On the use of the hybrid causal logic method in offshore risk analysis

Author

Listed:
  • Røed, Willy
  • Mosleh, Ali
  • Vinnem, Jan Erik
  • Aven, Terje

Abstract

In the Norwegian offshore oil and gas industry risk analyses have been used to provide decision support for more than 20 years. The focus has traditionally been on the planning phase, but during the last years a need for better risk analysis methods for the operational phase has been identified. Such methods should take human and organizational factors into consideration in a more explicit way than the traditional risk analysis methods do. Recently, a framework, called hybrid causal logic (HCL), has been developed based on traditional risk analysis tools combined with Bayesian belief networks (BBNs), using the aviation industry as a case. This paper reviews this framework and discusses its applicability for the offshore industry, and the relationship to existing research projects, such as the barrier and operational risk analysis project (BORA). The paper also addresses specific features of the framework and suggests a new approach for the probability assignment process. This approach simplifies the assignment process considerably without loosing the flexibility that is needed to properly reflect the phenomena being studied.

Suggested Citation

  • Røed, Willy & Mosleh, Ali & Vinnem, Jan Erik & Aven, Terje, 2009. "On the use of the hybrid causal logic method in offshore risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 445-455.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:2:p:445-455
    DOI: 10.1016/j.ress.2008.04.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183200800135X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2008.04.003?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Atashfeshan, Nooshin & Saidi-Mehrabad, Mohammad & Razavi, Hamideh, 2021. "A novel dynamic function allocation method in human-machine systems focusing on trigger mechanism and allocation strategy," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    2. Groth, Katrina & Wang, Chengdong & Mosleh, Ali, 2010. "Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1276-1285.
    3. Fam, Mei Ling & He, Xuhong & Konovessis, Dimitrios & Ong, Lin Seng, 2020. "Using Dynamic Bayesian Belief Network for analysing well decommissioning failures and long-term monitoring of decommissioned wells," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    4. Kasai, Naoya & Matsuhashi, Shigemi & Sekine, Kazuyoshi, 2013. "Accident occurrence model for the risk analysis of industrialfacilities," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 71-74.
    5. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2016. "Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 93-112.
    6. Stein Haugen & Nathaniel John Edwin, 2017. "Dynamic risk analysis for operational decision support," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 41-63, November.
    7. Marhavilas, P.K. & Koulouriotis, D.E., 2012. "A combined usage of stochastic and quantitative risk assessment methods in the worksites: Application on an electric power provider," Reliability Engineering and System Safety, Elsevier, vol. 97(1), pages 36-46.
    8. Ramos, M.A. & Thieme, Christoph A. & Utne, Ingrid B. & Mosleh, A., 2020. "Human-system concurrent task analysis for maritime autonomous surface ship operation and safety," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    9. Baoping Cai & Yonghong Liu & Zengkai Liu & Xiaojie Tian & Yanzhen Zhang & Renjie Ji, 2013. "Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1293-1311, July.
    10. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    11. Quintanar-Gago, David A. & Nelson, Pamela F. & Díaz-Sánchez, à ngeles & Boldrick, Michael S., 2021. "Assessment of steam turbine blade failure and damage mechanisms using a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    12. Y-F Wang & M Xie & M S Habibullah & K-M Ng, 2011. "Quantitative risk assessment through hybrid causal logic approach," Journal of Risk and Reliability, , vol. 225(3), pages 323-332, September.
    13. 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.
    14. Hegde, Jeevith & Utne, Ingrid Bouwer & Schjølberg, Ingrid & Thorkildsen, Brede, 2018. "A Bayesian approach to risk modeling of autonomous subsea intervention operations," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 142-159.
    15. Mostafa Aliyari & Yonas Z Ayele & Abbas Barabadi & Enrique Lopez Droguett, 2019. "Risk analysis in low-voltage distribution systems," Journal of Risk and Reliability, , vol. 233(2), pages 118-138, April.
    16. Xu, Sheng & Kim, Ekaterina & Haugen, Stein & Zhang, Mingyang, 2022. "A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

    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:eee:reensy:v:94:y:2009:i:2:p:445-455. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.