• 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