Design and Development of a Responsible Care Evaluation System for Hazardous Chemical Warehousing Enterprises

In response to the inadequate implementation of responsible care and the lack of systematic evaluation systems in hazardous chemical warehousing enterprises, this study proposes a responsible care evaluation system centered on the AHP-Fuzzy Comprehensive Evaluation Model, integrated with IoT data collection and big data analytics. By constructing 21 specific indicators across five dimensions—namely safety management, environmental protection, health protection, compliance operation, and community interaction—and utilizing the Entropy Weight-TOPSIS algorithm for weight optimization and comprehensive evaluation, the system achieves a dynamic quantitative assessment of responsible care levels in hazardous chemical warehousing enterprises. These 21 indicators cover daily operational data and long-term performance metrics, ensuring no core aspect of responsible care is omitted. Developed with a microservice architecture and front-end/back-end separation technology, the system includes modules for data collection, indicator management, model calculation, and visual display, with each module designed to be independently deployable and scalable to adapt to enterprise-specific needs. Practical application shows that the system improves responsible care evaluation accuracy to 88.3%, shortens early warning response time by 40%, and provides a scientific digital tool for enterprise responsible care management, effectively bridging the gap between theoretical responsible care frameworks and on-the-ground operational practices.