Abstract
This paper focuses on developing an intelligent management model for safety risks in university laboratories based on digital twin technology to improve safety management efficiency and accuracy. The virtual simulation environment of the laboratory is constructed by using digital twin technology, which is combined with the DEMATEL-ISM method for risk identification and analysis. Fault tree analysis (FTA) method was utilized to construct a laboratory safety accident fault tree to identify and assess potential risk factors. It was found that safety risks in laboratories can be effectively identified and controlled by digital twin technology. The risk assessment showed that unregulated drug storage, lack of monitoring and warning devices, insufficient safety awareness, inadequate systems and unreasonable layout of water, electricity and gas pipelines were the main risk factors. The empirical analysis of 11 university laboratories revealed that most of the laboratories were at a “relatively safe” level. The intelligent management model of safety risk in university laboratories based on digital twins can effectively identify and assess the safety risk, provide a scientific basis for the formulation of safety management measures, and thus improve the efficiency and accuracy of laboratory safety management.
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