DocumentCode :
1830674
Title :
A new methodology to integrate human factors analysis and classification system with Bayesian Network
Author :
Wang, Yan Fu ; Roohi, Shahrzad Faghih ; Hu, Xiu Ming ; Xie, Min
Author_Institution :
Dept. of Ind. & Syst. Eng., Nat. Univ. of Singapore, Singapore, Singapore
fYear :
2010
fDate :
7-10 Dec. 2010
Firstpage :
1776
Lastpage :
1780
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.
Keywords :
belief networks; decision making; fuzzy set theory; marine engineering; marine safety; pattern classification; Bayesian network; classification system; fuzzy analytical hierarchy process; human factors analysis; maritime accidents; ship collision study; Accidents; Bayesian methods; Engines; Human factors; Humans; Safety; Systematics; Bayesian Network; Fuzzy Analytical Hierarchy Process; Human factors analysis and classification system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on
Conference_Location :
Macao
ISSN :
2157-3611
Print_ISBN :
978-1-4244-8501-7
Electronic_ISBN :
2157-3611
Type :
conf
DOI :
10.1109/IEEM.2010.5674564
Filename :
5674564
Link To Document :
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