Poisoning and Asphyxiation Risk Assessment in a Steel Plant Based on Fuzzy Bayesian Network

There is a lack of a quantitative assessment of the risk factors associated with poisoning and asphyxiation accidents in steel enterprises, especially the insufficient treatment of uncertainty in risk analysis. To address this issue, this work proposed a risk assessment method based on fuzzy Bayesian network (FBN), which established a risk assessment indicator system for poisoning and asphyxiation from four aspects, including human, material, environmental, and management factors, and illustrated the relationship between these risk factors through fault tree analysis (FTA). Taking a steel plant in China as an example, fuzzy set theory (FST) and expert surveys were combined to determine the prior probabilities and conditional probabilities of Bayesian network (BN) nodes. The results show that (i) the probability of poisoning and asphyxiation accidents in this steel plant is 74%; (ii) among the various influencing factors, defective or inadequate monitoring and alarm devices, isolation devices, equipment inspection systems, and toxic gas operation management are identified as the critical contributors; and (iii) this accident probability has decreased to 47% after rectification measures and reassessment. The findings of this research offer valuable insights for steel enterprises in preventing poisoning and asphyxiation accidents.