Abstract

This research project aims to develop a comprehensive decision-support tool for managing risks associated with ship foundering. By integrating Critical Barrier Management (CBM) and Bayesian Network (BN) models, the project creates a robust framework to enhance safety and operational efficiency in maritime operations. These methodologies provide maritime professionals with dynamic tools for understanding, evaluating, and mitigating risks, particularly during and after critical operation events such as collisions, groundings, and flooding. The primary objective is to enhance the management of critical barriers that prevent catastrophic outcomes in maritime accidents. This involves creating an interactive dashboard for real-time data visualization, developing a decision-support CBM framework to identify and manage critical control barriers and integrating BN models for a probabilistic approach to risk assessment. Key findings indicate that the integration of CBM and BN models offers a robust technique for risk assessment, significantly improving the accuracy of risk evaluations. The study also highlights the importance of addressing human factors, such as fatigue, in maritime safety. Recommendations include the adoption of CBM frameworks and BN models by maritime organizations, regular training, and awareness programs to address human factors, and future research to refine these models and explore emerging technologies for advanced risk assessment. By implementing these recommendations, maritime professionals can improve their understanding of critical barriers, enhance decision-making processes, and ensure safer maritime operations. Continuous refinement of these models and the incorporation of emerging technologies will further advance the field.

Keywords

Ship Foundering, Harsh Conditions, Human Error, Bayesian Network, Quantitative Risk Assessment, Decision-making

References

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