Assessing the mariner's role and human reliability in the post-accident evidence collection process: The case of ship grounding using a BN–SLIM approach

Abstract

Grounding accidents pose a significant risk to the environment, global logistics, maritime vessels and seafarers. A substantial proportion of literature pertaining to maritime accidents is dedicated to groundings, however to the best of knowledge, there is an absence of research papers investigating the processes of post-accident evidence collection. To address this gap, the present paper aims to identify an optimal evidence collection process for grounding accidents to evaluate the potential shortcomings and analyse the human factors contributing to deficiencies in this critical work. The evidence collection process on board is primarily coordinated by the master and supported by the officers, this study conceptually represents the mariner's collective role and reliability in managing post-accident documentation tasks. A fuzzy Bayesian Network (BN) is employed to model an ideal evidence collection framework and identify factors that may lead to failure in this intricate process. Subsequently, the human error probability (HEP) was determined with respect to the substantial tasks inherent in evidence collection process, by means of the Success Likelihood Index Method (SLIM). In addition, the performance-shaping factors (PSFs) that initiate errors must were identified. The BN results indicate that the most effective causes of evidence collection failure were the collection of weather reports, ECDIS records and VDR data. The SLIM findings suggest that tasks with the highest error probability will be encountered during the collection of bridge records, and pinpoints the importance of stress, leadership and knowledge as the most influential factors affecting this task. The proposed framework and the outcomes of this study may contribute to post-accident response strategies of ship operators, masters and maritime insurance providers by demonstrating the importance of human reliability in complex post-accident situations.