# Application of Extension Engineering in Safety Evaluation of Chemical Enterprises
## 1 Introduction  
Industrial safety is an important guarantee technology for industrial upgrading to fully automated production of intelligent systems. Industrial accidents have their own characteristics; accidents are relatively rare compared with the whole life cycle of production, and the scope of consequences is large [1, 2]. The characteristics of equipment reliability are not always the determining factors when assessing industrial safety risks; the industrial safety of complex processes is influenced by both external and internal factors [3, 4]. During the production process, the geographical location, the quality of the raw materials, the weather conditions, unsafe conditions of the environment, the technological process, unsafe operation of personnel, the unsafe state of objects, and many other factors can cause negative phenomena. However, most of the raw materials and products of chemical enterprises are in flammable, explosive, toxic, and harmful states. These dangerous goods easily cause casualties and property losses in accidents [5, 6]. Early detection of these factors is important to take timely preventive measures to prevent the occurrence of harm. To study the abnormal behavior of complex process systems, the mathematical modeling method is usually used, and the problem of studying various processes is simplified to the problem of studying the properties of mathematical models. Thus, the risk early warning model for the production process of chemical enterprises is established, and the massive data accumulated over the years in the chemical industry are used for risk early warning. Therefore, how to incorporate environmental factors in the production process into thesafety assessment and provide safety-security assisted decision support for chemical enterprise managers has become an urgent problem to be solved in the safety-security field of intelligent factories. Most of the existing factory risk assessment methods use index or probability evaluation [7; 8; 9]. The adoption of the index makes the system structure complex, and it is difficult to express that the evaluation of the risk unit has a feasible method using the probability. The evaluation method focuses on different production links and aspects that are not the same, and it is difficult to form a complete system. At the same time, although single factor and single index evaluation are widely used in a short time due to their simplicity and convenience, there are some shortcomings, such as insufficient comprehensive information and easy distortion, which cannot meet the increasingly strict and accurate requirements of chemical factory risk evaluation. In recent years, it has gradually developed from single factor and single index analysis to systematic comprehensive evaluation and examination direction. For the evaluation of complex dangerous environments, the most commonly used evaluation methods mainly include the comprehensive index method [10], set pair analysis method [11], fuzzy comprehensive evaluation method [12], neural network method [13], gray theory comprehensive evaluation method [14], and ICI Mond evaluation method [15]. The literature [7] established a security system dynamics model based on the methods of system dynamics. The model reflects the complex relationship among the safety factors of the storage and distribution station. The methods of system dynamics are used to model and analyze the relationship among the safety influencing factors. The literature [10] established the index system for coal mine safety assessment according to the influencing factors of coal mine safety: a comprehensive safety evaluation model for coal mine is built on the basis of analytic hierarchy process, and the effective safe management measures are proposed. The literature [11] built an evaluation and prediction model for occupational hazards in coal mines based on set pair analysis. The model uses three aspects of identity-discrepancy-contrast to study the relationship between uncertainty and certainty of a factor or event.