University of Tasmania

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A virtual experimental technique for data collection for a Bayesian network approach to human reliability analysis

journal contribution
posted on 2023-05-19, 10:40 authored by Musharraf, M, Bradbury-Squires, D, Faisal KhanFaisal Khan, Veitch, B, Mackinnon, S, Imtiaz, S
Bayesian network (BN) is a powerful tool for human reliability analysis (HRA) as it can characterize the dependency among different human performance shaping factors (PSFs) and associated actions. It can also quantify the importance of different PSFs that may cause a human error. Data required to fully quantify BN for HRA in offshore emergency situations are not readily available. For many situations, there is little or no appropriate data. This presents significant challenges to assign the prior and conditional probabilities that are required by the BN approach. To handle the data scarcity problem, this paper presents a data collection methodology using a virtual environment for a simplified BN model of offshore emergency evacuation. A two-level, three-factor experiment is used to collect human performance data under different mustering conditions. Collected data are integrated in the BN model and results are compared with a previous study. The work demonstrates that the BN model can assess the human failure likelihood effectively. Besides, the BN model provides the opportunities to incorporate new evidence and handle complex interactions among PSFs and associated actions.


Publication title

Reliability Engineering and System Safety








Australian Maritime College


Elsevier Sci Ltd

Place of publication

United Kingdom

Rights statement

Copyright 2014 Elsevier Ltd.

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in engineering