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Li, P, Wang, Y and Yang, Z (2024) Risk assessment of maritime autonomous surface ships collisions using an FTA-FBN model. Ocean Engineering, 309. ISSN 0029-8018
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Risk assessment of maritime autonomous surface ships collisions using an FTA-FBN model.pdf - Published Version Available under License Creative Commons Attribution. Download (7MB) | Preview |
Abstract
Maritime autonomous surface ships (MASS), presenting the future of maritime transport, are attracting increasing attention from the international maritime community. The collision risk analysis of MASS reveals unsolved challenges, which without appropriate solutions, will result in the error prone development of the relevant risk control measures and policies. Among the challenges, two significant ones in the existing literature are the lack of historical failure data to realise quantitative risk assessment, and 2) the complex causal relationship among the relevant risk factors. This paper aims to develop a new Fault Tree Analysis-Fuzzy Bayesian Network (FTA-FBN) model to conduct the collision risk assessment of MASS with uncertainty in data. First, it establishes a causal relationship among the risk factors through an FTA. Secondly, mapping the obtained FTA diagram into a BN allows fault diagnosis and the identification of the most important factors influencing MASS collisions. In this process, a survey is conducted to collect the primary data for configuring the conditional probabilities of the relevant influential factors and quantifying the developed BN for risk diagnosis and prediction. Finally, the new model is verified by using sensitivity analysis and three axioms and then applied to conduct scenario-based risk prediction and diagnosis to generate insightful findings to guide MASS navigation safety. The results demonstrate that the FTA-FBN model realizes the simplification of the expert scoring process, reduces computational complexity, and addresses the challenge of constructing causal relationships between MASS collisions and their risk factors due to the scarcity of historical accident data. Additionally, the BN backward reasoning identifies key collision risks, including external physical attacks, inadequate training of shore-based operators, insufficient maintenance of ship equipment and systems, and cyber-security threats. The new model when being adapted, can provide a reference for the formulation of safe navigation policies and provide important insights for shipping companies to ensure the safe navigation of their ships and shipbuilders to optimise ship design.
| Item Type: | Article |
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| Uncontrolled Keywords: | Maritime autonomous surface ships; Maritime risk; Bayesian network; Fault tree analysis; Fuzzy theory; 0405 Oceanography; 0905 Civil Engineering; 0911 Maritime Engineering; Civil Engineering |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TC Hydraulic engineering. Ocean engineering V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering |
| Divisions: | Engineering |
| Publisher: | Elsevier |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 08 Nov 2024 15:02 |
| Last Modified: | 08 Nov 2024 15:15 |
| DOI or ID number: | 10.1016/j.oceaneng.2024.118444 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/24721 |
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