A new methodology to integrate human factors analysis and classification system with Bayesian Network

Abstract

In this paper, a new methodology, which integrates human factors analysis and classification system (HFACS) with Bayesian Network (BN), is proposed to assess the contribution of human and organizational factors in maritime accidents. As a means of making up the lack of quantitative analysis within HFACS, the integration of BN and fuzzy analytical hierarchy process (AHP) have been selected to estimate quantitatively the contribution of human error to the accident. At the same time, the HFACS' 4-level structure provides a systematic guideline in the construction of the BN to model how human errors are related to form a network. Fuzzy AHP and decomposition method are applied to estimate the conditional probabilities of BN, which is more efficient manner and can reduce subjective biases. A case study of ship collision showed that the method is more flexible to seek out the critical latent human and organizational errors using the advantages of both techniques.