Quantitative human error assessment during abandon ship procedures in maritime transportation

Abstract

Human error prediction is always onerous work in the maritime domain since it is very difficult to obtain empirical data. One accepted method, Success Likelihood Index Method (SLIM), is utilized to assess human error as data is very scarce in the marine industry. The SLIM provides a quick tool to predict human error and evaluate human error probability (HEP) that occurs during the completion of a specific task. The weakness of the method is the subjectivity in the process of experts’ judgments causing difficulties in ensuring consistency. To remedy this gap, this paper proposes a fuzzy based SLIM technique which provides more accurate estimation during human error quantification. In the proposed approach, while the SLIM is utilized to estimate HEP, the fuzzy sets deal with the vagueness of expert judgments and expression in decision-making during the weighting process of performance shaping factors (PSF). To illustrate the proposed approach, the abandon ship procedure in marine transportation has been selected since the evacuation of the ship is critical to prevent the loss of life in the case of emergency. The outcomes of the paper can be utilized by ship owners, safety managers as well as ship management companies to minimize the likelihood of human error occurring within a specific task and to enhance overall levels of safety on-board a ship in the marine environment.