Human error probability prediction for cargo sampling process on chemical tanker ship under extended SLIM Evidential Reasoning approach

Abstract

Cargo sampling, which indicates the condition of the cargo on the ship, is one of the important chemical tanker shipboard operations where human performance is prominent. Any negligence during the cargo sampling process can result in loss of human life, environmental disasters and financial losses. Therefore, evaluating human performance in the cargo sampling process on chemical tanker ships is vital to avoid these. This paper aims to evaluate the contribution of human errors to the cargo sampling process. Hence, the Success Probability Index Method (SLIM) is conducted, incorporating Evidential Reasoning (ER) approach. While SLIM systematically predicts human error probabilities (HEP) considering performance shaping factors (PSFs), ER deals with the uncertain and subjective judgments of experts in the step of rating and weighting PSFs. Based on the presented ER-SLIM model, HEP can be estimated by aggregating the belief degree of the experts and human performance for the cargo sampling process can be evaluated. The outputs of the paper provide a practical contribution to chemical tanker ship owners, health safety environment and quality (HSEQ) managers, maritime safety professionals and, chemical tanker officers in order to minimize the probability of human error in the cargo sampling process, as well as the theoretical background.