Research Article
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Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach

Year 2023, Volume: 8 Issue: 1, 36 - 47, 10.08.2023
https://doi.org/10.26650/JTL.2023.1243766

Abstract

Solid bulk cargo liquefaction is hazardous for bulk carrier ships as they reduce the stability of the ship. Most dry bulk ship owners face solid bulk cargo liquefaction during the carriage of ore cargoes. The consequences of cargo liquefaction could have catastrophic effects such as the ship sinking or capsizing. To improve the process of safety during the shipment of bulk cargo and reduce potential consequences, a detailed risk analysis is needed. The purpose of this paper is to conduct a systematic probabilistic risk analysis of the liquefaction of solid bulk cargo in the marine sector in order to allay this concern in order to deal with complex causation and uncertainty resulting from complex interdependence among risk factors, limited data, and a complex environment. A Bayesian network (BN) method under fuzzy logic has been utilized in the research. Whilst the BN enables us to calculate the conditional probability of each basic event in the graph, the fuzzy logic tackles uncertainty and the vagueness of expert judgment. The findings of the paper will assist solid bulk cargo owners and shippers in reducing the risk of solid bulk cargo liquefaction during maritime transportation.

References

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Year 2023, Volume: 8 Issue: 1, 36 - 47, 10.08.2023
https://doi.org/10.26650/JTL.2023.1243766

Abstract

References

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  • Hanninen, M., Valdez Banda, O. A., & Kujala, P. (2014). Bayesian network model of maritime safety management. Expert Systems with Applications, 41(17), 7837-7846. https://doi.org/10.1016/j.eswa.2014.06.029 google scholar
  • John, A., Yang, Z., Riahi, R., & Wang, J. (2016). A risk assessment approach to improve the resilience of a seaport system using Bayesian networks. Ocean Engineering, 111, 136-147. https://doi.org/10.1016/j.oceaneng.2015.10.048 google scholar
  • Jones, B., Jenkinson, I., Yang, Z., & Wang, J. (2010). The use of Bayesian network modelling for maintenance planning in a manufacturing industry. Reliability Engineering & System Safety, 95(3), 267-277. google scholar
  • Kabir, G., Tesfamariam, S., Francisque, A., & Sadiq, R. (2015). Evaluating risk of water mains failure using a Bayesian belief network model. European Journal of Operational Research, 240(1), 220-234. https://doi.org/10.1016/j.ejor.2014.06.033 google scholar
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  • Kaptan, M. (2021b). Risk assessment for transporting ammonium nitrate-based fertilizers with bulk carriers. Journal of ETA Maritime Science, 9(2), 130-137. google scholar
  • Kaptan, M. (2021b). Risk assessment for transporting ammonium nitrate-based fertilizers with bulk carriers. Journal of ETA Maritime Science, 9(2), 130-137. google scholar
  • Kerner, B. S., & Herrtwich, R. G. (2001). Traffic flow forecasting. At-Automatisierungstechnik, 49(11), 505-511.https://doi.org/10.1524/auto.2001.49.11.505 google scholar
  • Khan, B., Khan, F., & Veitch, B. (2020). A Dynamic Bayesian Network model for ship-ice collision risk in the Arctic waters. Safety Science, 130, 104858. google scholar
  • Khan, S., Khan, F., & Zhang, B. (2012). Reverse e-logistics for SMEs in Pakistan. In Advances in Intelligent and Soft Computing: Vol. 115 AISC (Issue VOL. 2). https://doi.org/10.1007/978-3-642-25349-231 google scholar
  • Khakzad, N., Khan, F., Amyotte, P. (2013). Quantitative risk analysis of offshore drilling operations: A Bayesian approach. Safety science, 57, 108-117. google scholar
  • Khakzad, N., Khan, F., Amyotte, P. (2011). Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches. Reliability Engineering System Safety, 96(8): 925-932. google scholar
  • Kuzu, A. C., Akyuz, E., Arslan, O. (2019). Application of fuzzy fault tree analysis (FFTA) to maritime industry: a risk analysing of ship mooring operation. Ocean Engineering, 179, 128-134. google scholar
  • Lampis, M., Andrews, J. D. (2009). Bayesian belief networks for system fault diagnostics. Quality and Reliability Engineering International, 25(4), 409-426. google scholar
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  • Lavasani, S. M. M., Wang, J., Yang, Z., Finlay, J. (2012). Application of MADM in a fuzzy environment for selecting the best barrier for offshore wells. Expert Systems with Applications, 39(3), 2466-2478. https://doi.org/10.1016/j.eswa.2011.08.099 google scholar
  • Lavasani, S. M., Ramzali, N., Sabzalipour, F., Akyuz, E. (2015). Utilisation of Fuzzy Fault Tree Analysis (FFTA) for quantified risk analysis of leakage in abandoned oil and natural-gas wells. Ocean Engineering, 108, 729-737. https://doi.org/10.1016/j.oceaneng.2015.09.008. google scholar
  • Li, Y., Xu, D., Shuai, J. (2020). Real-time risk analysis of road tanker containing flammable liquid based on fuzzy Bayesian network. Process Safety and Environmental Protection, 134, 36-46. google scholar
  • Norrington, L., Quigley, J., Russell, A., Van der Meer, R. (2008). Modelling the reliability of search and rescue operations with Bayesian Belief Networks. Reliability Engineering and System Safety, 93(7), 940-949. https://doi.org/10.1016/j.ress.2007.03.006 google scholar
  • Özaydın, E., Fışkın, R., Uğurlu, Ö., Wang, J. (2022). A hybrid model for marine accident analysis based on Bayesian Network (BN) and Association Rule Mining (ARM). Ocean Engineering, 247, 110705. google scholar
  • Pan, R., Zhou, X., Lin, X. (2012). The assessment of cylinder liner by HAZOP analysis and fuzzy comprehensive evaluation. Advanced Materials Research, 562-564, 650-653. https://doi.org/10.4028/www.scientific.net/AMR.562-564.650 google scholar
  • Ping, P., Wang, K., Kong, D., Chen, G. (2018). Estimating probability of success of escape, evacuation, and rescue (EER) on the offshore platform by integrating Bayesian Network and Fuzzy AHP. Journal of Loss Prevention in the Process Industries, 54(January), 57-68. https://doi.org/10.1016/j.jlp.2018.02.007 google scholar
  • Pristrom, S., Yang, Z., Wang, J., Yan, X. (2016). A novel flexible model for piracy and robbery assessment of merchant ship operations. Reliability Engineering System Safety, 155, 196-211. google scholar
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There are 68 citations in total.

Details

Primary Language English
Subjects Maritime Engineering
Journal Section Research Article
Authors

Muhammet Aydın 0000-0002-5478-0909

Publication Date August 10, 2023
Submission Date January 28, 2023
Acceptance Date March 1, 2023
Published in Issue Year 2023 Volume: 8 Issue: 1

Cite

APA Aydın, M. (2023). Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach. Journal of Transportation and Logistics, 8(1), 36-47. https://doi.org/10.26650/JTL.2023.1243766
AMA Aydın M. Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach. JTL. August 2023;8(1):36-47. doi:10.26650/JTL.2023.1243766
Chicago Aydın, Muhammet. “Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach”. Journal of Transportation and Logistics 8, no. 1 (August 2023): 36-47. https://doi.org/10.26650/JTL.2023.1243766.
EndNote Aydın M (August 1, 2023) Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach. Journal of Transportation and Logistics 8 1 36–47.
IEEE M. Aydın, “Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach”, JTL, vol. 8, no. 1, pp. 36–47, 2023, doi: 10.26650/JTL.2023.1243766.
ISNAD Aydın, Muhammet. “Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach”. Journal of Transportation and Logistics 8/1 (August 2023), 36-47. https://doi.org/10.26650/JTL.2023.1243766.
JAMA Aydın M. Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach. JTL. 2023;8:36–47.
MLA Aydın, Muhammet. “Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach”. Journal of Transportation and Logistics, vol. 8, no. 1, 2023, pp. 36-47, doi:10.26650/JTL.2023.1243766.
Vancouver Aydın M. Risk Assessment of Solid Bulk Cargo Liquefaction Consequences in Maritime Transportation under a Fuzzy Bayesian Network Approach. JTL. 2023;8(1):36-47.



The JTL is being published twice (in April and October of) a year, as an official international peer-reviewed journal of the School of Transportation and Logistics at Istanbul University.