Analysis and Coding of Lifeboat Accidents

Abstract

Several studies have shown that lifeboat was not as safe as it was supposed to be. Even though there is less number of lifeboat accidents that contribute to the total shipping accidents, lifeboat accidents caused a lot of fatalities and injuries to seafarers, most in maintenance, survey or drilling. Seafarers’ confidence of lifeboats was seriously reduced.

In this report, a coding structure is proposed after analyzing several lifeboat accidents by using one primary method called Events and Causal Factor Charting (ECFC) and an assisting method called Influence Diagrams. Further, the probabilistic model is proposed by utilizing the Bayesian Belief Network (BBN) to help build a model for analyzing the relationship between different causal events (variables). A human and organizational factors analysis is carried out after the BBN approach. A Human Factors Analysis and Classification System (HFACS) is proposed in that chapter.

A specific coding structure for lifeboat accidents is addressed in the research. This could help collecting lifeboat accident data in a more professional way and provide the sounding data support for the future quantification work. The BBN and HFACS work was proved to be feasible and beneficial for the analysis of lifeboat accidents. Future technical analysis could be provided based on the research.

Key Words: Lifeboat, Influence Diagram, Coding, BBN, HFACS