This study analyzes maritime collision causation using an integrated Fault Tree Analysis (FTA) and Monte Carlo simulation framework based on 112 collision accidents involving 224 vessels, extracted from official accident investigation reports. A structured database of 18 basic events was developed and grouped into three intermediate categories: shipboard operation, shore management, and external environment. These events were used to construct a probabilistic fault tree model of collision occurrence. Analytical FTA was applied to identify minimum cut sets, calculate event probabilities, and evaluate basic-event importance using the Fussell–Vesely measure. The results show that all minimum cut sets are of first order and that shipboard operational factors dominate the collision risk profile. In particular, personnel and manning deficiencies, crew resource management failures, and shipboard social environment were identified as the most influential contributors. Shore management factors exhibited a secondary contribution, while external environmental factors showed a smaller influence. Monte Carlo simulation with 3,000,000 iterations validated the analytical results and stabilized the importance rankings, confirming the robustness of the findings. The proposed approach provides a transparent, data-driven framework for collision risk prioritization and supports targeted safety interventions focusing on onboard human and organizational performance.
Jovanović et al. (Wed,) studied this question.