An adaptive model for human factors assessment in maritime operations

Abstract

Complexity in marine operations requires a robust and dynamic framework for human error assessment to aid safety-based decision making under uncertainty.The current study presents a dynamic Human Factors Analysis and Classification System for Maritime Accident. The model is used for human factor assessment in critical maritime operations, considering the influential factors of dynamic cognitive human behavior and complex interactions among core risk factors. The HFACS-MA structure consists of five levels of human factors based on the International Maritime Organization (IMO) guiding principles and the Human Factor Analysis and Classification System (HFACS) concept. Based on three accident case studies, the study explores five levels of human role to develop a robust model structure for critical maritime operations. The developed structure is translated into a novel Bayesian network (BN) structure, capturing the dependencies among the risk influencing factors for the three accident scenarios. The developed model framework for the accident scenarios emphasizes the changing characteristics of human performance influential factors and the dynamic operating environment. The demonstrated case studies further confirm the model adaptiveness in human factor assessment, considering the dynamic decision-making influential factors and operational uncertainty.