IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v225y2011i3p323-332.html
   My bibliography  Save this article

Quantitative risk assessment through hybrid causal logic approach

Author

Listed:
  • Y-F Wang
  • M Xie
  • M S Habibullah
  • K-M Ng

Abstract

In this paper, a hybrid causal logic (HCL) model is improved by mapping a fuzzy fault tree (FFT) into a Bayesian network (BN). The first step is to substitute an FFT for the traditional FT. The FFT is based on the Takagi–Sugeno model and the translation rules needed to convert the FFT into a BN are derived. The proposed model is demonstrated in a study of a fire hazard on an offshore oil production facility. It is clearly shown that the FFT can be directly converted into a BN and that the parameters of the FFT can be estimated more accurately using the basic inference techniques of a BN. The improved HCL approach is able to both accurately determine how failures cause an undesired problem using FFT and also model non-deterministic cause–effect relationships among system elements using the BN.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:risrel:v:225:y:2011:i:3:p:323-332
    DOI: 10.1177/1748006X10397370
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X10397370
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X10397370?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. 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.
    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. Bashari, H. & Smith, C. & Bosch, O.J.H., 2008. "Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks," Agricultural Systems, Elsevier, vol. 99(1), pages 23-34, December.
    4. Doguc, Ozge & Ramirez-Marquez, Jose Emmanuel, 2009. "A generic method for estimating system reliability using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 542-550.
    Full references (including those not matched with items on IDEAS)

    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. Ekanem, Nsimah & Mosleh, Ali & Shen, Song-Hua & Ramos, Marilia, 2024. "Phoenix–A model-based human reliability analysis methodology: Data sources and quantitative analysis procedure," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. Moglia, Magnus & Alexander, Kim S. & Thephavanh, Manithaythip & Thammavong, Phomma & Sodahak, Viengkham & Khounsy, Bountom & Vorlasan, Sysavanh & Larson, Silva & Connell, John & Case, Peter, 2018. "A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR," Agricultural Systems, Elsevier, vol. 164(C), pages 84-94.
    10. 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).
    11. Bjorkman, Kim, 2013. "Solving dynamic flowgraph methodology models using binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 206-216.
    12. Andrews, John & Fecarotti, Claudia, 2017. "System design and maintenance modelling for safety in extended life operation," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 95-108.
    13. Amrin, Andas & Zarikas, Vasileios & Spitas, Christos, 2018. "Reliability analysis and functional design using Bayesian networks generated automatically by an “Idea Algebra†framework," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 211-225.
    14. 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).
    15. Montewka, Jakub & Ehlers, Sören & Goerlandt, Floris & Hinz, Tomasz & Tabri, Kristjan & Kujala, Pentti, 2014. "A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 142-157.
    16. 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.
    17. Kondakci, Suleyman, 2015. "Analysis of information security reliability: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 275-299.
    18. Cai, Baoping & Liu, Yonghong & Liu, Zengkai & Tian, Xiaojie & Dong, Xin & Yu, Shilin, 2012. "Using Bayesian networks in reliability evaluation for subsea blowout preventer control system," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 32-41.
    19. Modibbo, Umar Muhammad & Arshad, Mohd. & Abdalghani, Omer & Ali, Irfan, 2021. "Optimization and estimation in system reliability allocation problem," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    20. Gehl, Pierre & Cavalieri, Francesco & Franchin, Paolo, 2018. "Approximate Bayesian network formulation for the rapid loss assessment of real-world infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 80-93.

    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:225:y:2011:i:3:p:323-332. 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.