Estimation of Human Errors During Cargo Unloading Operations on Bulk Carriers Using SLIM and Interval Type 2 Fuzzy Sets

Abstract

Cargo unloading operations on bulk carriers are critical shipboard operations. Many tasks are expected to fulfill by the ship's personnel to safely complete this type of operation. However, many human errors may occur during this process, and this situation threatens the safety of life and property. In this respect, this study predicts potential human errors and probabilities that may occur during cargo unloading operations on bulk carrier ships. In this study, an integrated human error prediction approach is proposed using interval type 2 fuzzy sets and the success likelihood index method. Thus, within the scope of this study, a model was obtained that allows human errors to be evaluated both qualitatively and quantitatively. Because of the analyzes made, it has been found that the most common human errors that occur while unloading cargo operations on bulk carriers occur in the processes of following the ballast operation and performing the tasks to prevent excessive trim/list formation on board ship, respectively. In addition, it was concluded that the factors that most shape the performance of the ship's personnel are education, communication, and experience.

Keywords

• unloading operation
• slim
• it2fs
• human error prediction
• bulk carrier