Title: Risk analysis using object-oriented Bayesian network: a case study of ammonia leakage of refrigeration system

Authors: Dheyaa A. Khudhur; Tuan Amran Tuan Abdullah; Norafneeza Norazahar

Addresses: Department of Chemical Engineering, Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia ' Department of Chemical Engineering, Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, Skudai, Johor Bahru, Malaysia; Centre of Hydrogen Energy, Institute of Future Energy, Universiti Teknologi Malaysia, Skudai, Johor Bahru, Malaysia ' Department of Chemical Engineering, Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, Skudai, Johor Bahru, Malaysia; Centre of Hydrogen Energy, Institute of Future Energy, Universiti Teknologi Malaysia, Skudai, Johor Bahru, Malaysia

Abstract: The increasing complexity of refrigeration systems has introduced major concerns into industrial safety and assets. This paper aims to develop a risk analysis framework for an ammonia refrigeration system using Object-Oriented Bayesian Network (OOBN). The failure causes of ammonia leakage are identified through a historical review of past accidents over a ten-year period and the Fault Tree (FT) is then constructed. Failure probabilities are quantified using objective data sources (plant-specific accident records) for known failure rates and subjective data sources (expert judgments and fuzzy set theory) for uncertain ones. The OOBN model is employed to analyse and evaluate the leakage risk. The results revealed that valve seal failures and flange breakages are critical factors in ammonia leakage, necessitating top priority in risk management. Moreover, the developed framework provides the decision-makers a robust tool for implementing safety measures to prevent and mitigate ammonia leakage incidents effectively.

Keywords: ammonia; Bayesian network; object-oriented Bayesian network; refrigeration; risk assessment.

DOI: 10.1504/IJRS.2025.145522

International Journal of Reliability and Safety, 2025 Vol.19 No.2, pp.107 - 131

Received: 06 Aug 2024
Accepted: 20 Nov 2024
Published online: 02 Apr 2025 *

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