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A conditional dependence-based marine logistics support risk model

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  • Rahman, Md Samsur
  • Khan, Faisal
  • Shaikh, Arifusalam
  • Ahmed, Salim
  • Imtiaz, Syed

Abstract

Industries and researchers have renewed interest in the Arctic as well as the sub-Arctic regions due to the proven hydrocarbon reserves. The main challenges of operations in these regions arise due to their remoteness and extreme weather conditions. These conditions also put major challenges to plan emergency logistics support, which is currently offered either by helicopters or marine vessels. This paper analyzes the risk-based marine logistics support model in an offshore facility operating in the far northern (sub-arctic) region. A Bayesian network (BN) approach is used to develop the risk model considering interdependencies and conditional relationships among the contributing factors. Exploration in the Flemish Pass Basin located offshore Newfoundland and Labrador, Canada, is selected as a case study to demonstrate the methodology. The study identifies the critical elements of a marine logistics operation that need attention to reduce its associated risk. The corresponding safety measures are identified and implemented into the risk model. Appropriate risk management strategies are proposed to support marine logistics operations.

Suggested Citation

  • Rahman, Md Samsur & Khan, Faisal & Shaikh, Arifusalam & Ahmed, Salim & Imtiaz, Syed, 2020. "A conditional dependence-based marine logistics support risk model," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:reensy:v:193:y:2020:i:c:s0951832018312419
    DOI: 10.1016/j.ress.2019.106623
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    References listed on IDEAS

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    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. Refaul Ferdous & Faisal Khan & Rehan Sadiq & Paul Amyotte & Brian Veitch, 2011. "Fault and Event Tree Analyses for Process Systems Risk Analysis: Uncertainty Handling Formulations," Risk Analysis, John Wiley & Sons, vol. 31(1), pages 86-107, January.
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    Cited by:

    1. Adland, Roar & Jia, Haiying & Lode, Tønnes & Skontorp, Jørgen, 2021. "The value of meteorological data in marine risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan, 2022. "An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    3. Ji, Chenyi & Su, Xing & Qin, Zhongfu & Nawaz, Ahsan, 2022. "Probability Analysis of Construction Risk based on Noisy-or Gate Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    4. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    5. Yue, Guo & Tailai, Guo & Dan, Wei, 2021. "Multi-layered coding-based study on optimization algorithms for automobile production logistics scheduling," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    6. Ilin, Igior & Kersten, Wolfgang & Jahn, Carlos & Weigell, Jürgen & Levina, Anastasia & Kalyazina, Sofia, 2020. "State of research in arctic maritime logistics," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 383-407, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    7. Rahman, Md Samsur & Colbourne, Bruce & Khan, Faisal, 2021. "Risk-Based Cost Benefit Analysis of Offshore Resource Centre to Support Remote Offshore Operations in Harsh Environment," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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