Bayesian best-worst method for cognitive reliability assessment in ballast water treatment systems on oil tankers

Operational safety and compliance with environmental regulations in the maritime sector are vital, particularly for Ballast Water Treatment Systems (BWTS) mandated by the Ballast Water Management (BWM) Convention. However, human errors during the operation of the complex systems significantly compromise their effectiveness and performance reliability. This article presents a robust approach to predict ship’s crew cognitive reliability and error systematically in tanker ship BWTS operations. The proposed approach integrates the Bayesian Best-Worst Method (BBWM), which probabilistically incorporates expert opinions to yield highly consistent CPC common performance condition (CPC) weights, which model the causal dependencies among cognitive performance factors using the weights. While the BBWM is employed to weight the CPC and to enhance the accuracy and robustness of the results, the Cognitive Reliability and Error Analysis Method (CREAM) systematically predict cognitive failure probability of ship crew. The findings show that “Verify BWTS readiness status" is having the highest cognitive failure probability value with 5.24E-02. This article provides practical insights to shipowners, superintendents, HSEQ managers, ship inspectors, Masters and chief engineers to enhance the safe and reliable operation of ballast water treatment systems on tanker ships.