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Operational risk assessment model for marine vessels

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  • Aziz, Abdul
  • Ahmed, Salim
  • Khan, Faisal
  • Stack, Chris
  • Lind, Annes

Abstract

This paper presents a practical approach to quantify the risk associated with different systems in a marine vessel using the existing operational database. A structured bow-tie methodology is proposed to assess risk. The first step was the development of probable failure scenarios for four different events, namely, fire and explosion, propulsion engine failure, power failure, and maneuverability failure. The second step includes the formulation of corresponding bow-tie models representing these scenarios using vessel configuration and process information. Using the failure data for different elements obtained from the vessel's maintenance logbook and incident records, the frequency of events and failure rates of the safety barriers are estimated to quantify risk. Operational data from the vessel, a single engine ice-breaker bulk career navigating mainly in the Canadian sub-arctic region, validated the proposed model. The methodology is verified by comparing the model's observations with an alternative dataset (actual failure scenario from the ship). The proposed methodology is expected to serve as a useful tool for marine vessel's safety and risk management.

Suggested Citation

  • Aziz, Abdul & Ahmed, Salim & Khan, Faisal & Stack, Chris & Lind, Annes, 2019. "Operational risk assessment model for marine vessels," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 348-361.
  • Handle: RePEc:eee:reensy:v:185:y:2019:i:c:p:348-361
    DOI: 10.1016/j.ress.2019.01.002
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    References listed on IDEAS

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    4. Goerlandt, Floris & Montewka, Jakub, 2015. "Maritime transportation risk analysis: Review and analysis in light of some foundational issues," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 115-134.
    5. Marvin Rausand & Jørn Vatn, 2008. "Reliability Centred Maintenance," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 4, pages 79-108, Springer.
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    Citations

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    Cited by:

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    2. Elidolu, Gizem & Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan & Arslanoglu, Yasin, 2023. "Operational risk assessment of ballasting and de-ballasting on-board tanker ship under FMECA extended Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) approach," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Deng, Wanyi & Ma, Xiaoxue & Qiao, Weiliang, 2024. "A novel methodology to quantify the impact of safety barriers on maritime operational risk based on a probabilistic network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    4. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C., 2022. "Casualty analysis methodology and taxonomy for FPSO accident analysis," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    5. Park, Jaehun & Lee, Byung Kwon, 2020. "Liner-dedicated manageability estimation for port operational reliability," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    6. Kandemir, Cagatay & Celik, Metin, 2021. "Determining the error producing conditions in marine engineering maintenance and operations through HFACS-MMO," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    7. Fu, Shanshan & Yu, Yuerong & Chen, Jihong & Xi, Yongtao & Zhang, Mingyang, 2022. "A framework for quantitative analysis of the causation of grounding accidents in arctic shipping," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Zhuang Li & Shenping Hu & Guoping Gao & Yongtao Xi & Shanshan Fu & Chenyang Yao, 2020. "Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network," Sustainability, MDPI, vol. 13(1), pages 1-17, December.

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