Prediction of human error probability under Evidential Reasoning extended SLIM approach: The case of tank cleaning in chemical tanker

Abstract

Critical shipboard operations are carried out on chemical tanker ships where human performance is prominent. That is why the assessment of the human error probability (HEP) is quite important. The Success Likelihood Index Method (SLIM) is an effective tool widely applied for HEP estimation and considers the performance shaping factors (PSF) that affect human error. However, in traditional SLIM, subjective and conflicting opinions of raters are needed during rating and weighting. To solve this problem, this paper extends SLIM with the Evidential Reasoning (ER) approach. In the ER-SLIM model, the belief degrees of the experts are aggregated and HEP can be estimated in a complex uncertain environment. This paper proposes a unique human error prediction model that reveals the potential contributions of human errors to the maritime domain To illustrate the feasibility and practicality of the developed model, the tank cleaning operation on the chemical tanker ship is investigated as a case study. The findings of the study guide maritime stakeholders in minimizing the human error probability in tank cleaning operations and enhancing the safety of chemical tanker ships.