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Human factor risk assessment during emergency condition in harsh environment


Musharraf, M and Khan, FI and Veitch, B and MacKinnon, S and Imtiaz, S, Human factor risk assessment during emergency condition in harsh environment, Proceedings of the ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2013, 9-14 June 2013, Nantes, France, pp. 1-9. ISBN 9780791855331 (2013) [Refereed Conference Paper]

Copyright Statement

Copyright 2013 ASME

DOI: doi:10.1115/OMAE2013-10867


This paper presents a quantitative approach to human factors risk analysis during emergency conditions on an offshore petroleum facility located in a harsh environment. Due to the lack of human factors data for emergency conditions, most of the available human factors risk assessment methodologies are based on expert judgment techniques. Expert judgment is a valuable technique, however, it suffers from vagueness, subjectivity and incompleteness due to a lack of supporting empirical evidence. These weaknesses are often not accounted for in conventional human factors risk assessment. The available approaches also suffer from the unrealistic assumption of independence of the human performance shaping (HPS) factors and actions. The focus of this paper is to address the issue of handling uncertainty associated with expert judgments and to account for the dependency among the HPS factors and actions. These outcomes are achieved by integrating Bayesian Networks with Fuzzy and Evidence theories to estimate human error probabilities during different phases of an emergency. To test the applicability of the approach, results are compared with an analytical approach. The study demonstrates that the proposed approach is effective in assessing human error probability, which in turn improves reliability and auditability of human factors risk assessment. Copyright © 2013 by ASME.

Item Details

Item Type:Refereed Conference Paper
Keywords:analytical approach, emergency conditions, expert judgment technique, human error probability, human performance, offshore petroleum, quantitative approach, risk assessment methodologies, Arctic engineering, Bayesian networks, errors, probability
Research Division:Engineering
Research Group:Engineering practice and education
Research Field:Risk engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Khan, FI (Professor Faisal Khan)
ID Code:120761
Year Published:2013
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-30
Last Modified:2017-10-17

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