Akademik Məlumat İdarəetmə Sistemi
Journal of Ocean Engineering and Science, 2025 (SCI-Expanded, Scopus)
Mooring operations are considered one of the most high-risk activities in cargo ship operations due to the complex interplay of human factors, equipment condition and environmental factors. This paper investigates quantitatively the mooring line risk during cargo operations in ships. To achieve this purpose, a robust practical approach integrating improved Z-numbers and a Bayesian network is proposed to perform probabilistic risk analysis. In the approach, whilst improved Z-numbers are employed to model uncertainty more effectively, considering both the probability of failure and the confidence in the data, the Bayesian network is used to analyse causal relationships and update risk assessments dynamically based on real-time operational data and environmental conditions. The proposed approach enhances predictive accuracy, enabling ship crews or technical ship inspectors to make informed decisions on mitigating risks under uncertain and variable conditions. The findings of the paper show that the mooring line failure probability during cargo operations is 0.015, and the root cause, “failure to adapt to tidal conditions”, is the main contributing factor. The proposed risk assessment approach provides valuable contributions for implementing proactive risk mitigation strategies and enhancing operational safety in cargo operations in maritime transportation.