A risk-based modelling approach to predict human error-induced oil pollution accident in bunker transferring operation

Abstract

Risk of oil pollution during bunker transfer operation remains a significant threat to marine ecosystems and safety as human error being a major contributing factor. This article proposes probabilistic risk modelling framework integrating Dempster-Shafer evidence theory (D-S), Cognitive Reliability and Error Analysis Method (CREAM) and Fault Tree Analysis (FTA) to quantify human error-induced bunker pollution accident in maritime transport. Since DS-CREAM approach is applied to capture epistemic uncertainty and quantification of human error probability incorporating evidence-based reasoning and context-dependent performance shaping factors (PSFs), FT performs probabilistic risk modelling for oil pollution accident. The findings show that occurrence probability of TE (Oil pollution accident risk on-board bunker transfer operation) is found 1.566E-01. Beside its robust theoretical background, the findings of the research will contribute safety and marine environment researchers, professionals, ship crew and superintendents for minimising oil pollution risk and enhancing operational safety during ship to ship bunker transfer operation. The proposed modelling will also provide a robust decision-support tool for risk management and oil pollution prevention in maritime bunker transfer operations.