A Quantitative Analysis Method Based on Network Evolution for Risk Factors of Safety Production in Chemical Enterprises

As petrochemical industry enterprises expand their scale and production capacity, equipment and storage facilities are increasingly automated. But its production safety issues are gradually exposed, including fires, poisonings, and explosions caused by equipment failures or human error. These accidents not only cause severe economic losses and casualties to the industry, but also negatively impact the public interest. Therefore, strengthen risk management and assessment capabilities is urgent. Existing studies analyzing risk factors quantitatively focus on management factors, excluding human and environmental factors. To address this gap, this study proposes a quantitative analysis method that considers multiple factors such as human factors, environment conditions, material and machine conditions and management factors. Firstly, this study constructed a Chemical Enterprise Safety Risk Network (CESRN) based on complex network theory. Subsequently, a method for calculating node risk thresholds and dynamic risk values that considers multiple factors was designed. On this foundation, an accident evolution model for chemical enterprise production safety was established. Then, a quantitative evaluation of the importance of each risk factor was obtained, along with the formulation of specific control measures. Finally, actual accident cases were examined for verification. The results indicated that the proposed method can accurately simulate accidents' evolution and precisely calculate the degree of importance of each risk factor.