An Improved EW-FCE Model for Risk Identification in Mines Laboratory Safety

To address the limitations of single evaluation methods, complex risk factors, and subjective weight allocation in university mining lab safety management, this study proposes an improved EW-FCE model integrating entropy weighting and fuzzy comprehensive evaluation. A multi-level evaluation index system was developed, covering personnel status, hazardous objects, operating environment, and lab standardization (4 secondary and 24 tertiary indicators). By combining objective entropy weights with quantitative risk affiliation from fuzzy evaluation, the model overcomes traditional subjectivity. Applied to a key mining lab in Shanxi, it calculated indicator weights and overall risk values using survey data. Key risk factors identified include special equipment operation certification (weight 0.0909), heavy machinery maintenance records (0.0813), and radioactivity detector qualification (0.0761). The model enables scientific risk ranking and aligns closely with actual lab safety conditions, offering a practical tool for safety management and supporting AI-assisted decision-making in engineering universities.