Analysing cargo shifting risk on Ro-Ro ship with a cloud modelling and Bayesian belief network approach

Cargo transportation by Ro-Ro (Roll-On/Roll-Off) ships poses significant risks to ship stability, crew safety, the marine environment, and cargo. To mitigate risk, a detailed risk assessment is paramount. This paper presents a robust approach that combines the Cloud Model (CM) and a Bayesian Belief Network (BBN) to evaluate the potential risks associated with cargo shifting on Ro-Ro ships. In this paper, the CM is applied to handle uncertainty and randomness in linguistic risk factors by transforming qualitative assessments into quantitative measures. The BBN is then employed to capture causal relationships among these factors and to provide a comprehensive analysis of their interdependencies through conditional probabilities. Hence, a comprehensive risk assessment is performed through a case study involving Ro-Ro cargo shifting. The paper's findings indicate that the cargo shifting risk on Ro-Ro ships is 4.83E-02. The research outcomes advance operational safety practices on Ro-Ro ships and support the development of proactive mitigation strategies for cargo shifting risks.