Enhancing the safety performance of EOT crane operations by integrating VR training and granular safety function deployment

This study addresses the hazards and potential damage from using electric overhead traveling (EOT) cranes in industrial environments. It aims to implement and evaluate effective measures to control and mitigate these risks. A novel approach integrates virtual reality (VR), double upper approximated rough number (DUARN), safety function deployment (SFD) and analytic hierarchy process (AHP) principles to assess the effectiveness of risk control systems (RCSs). A three-dimensional VR environment is developed to enhance the effectiveness of safety training for EOT crane operators in a steel manufacturing plant. The study presents a granulated SFD (GSFD) approach that utilizes granular computing to precisely model the uncertainties arising from experts' opinions, particularly EOT crane operators. The uncertainties pertain to hazards, initiating mechanisms (IMs) and associated RCSs identified after VR-based training. The proposed model is a three-stage granular house of safety (HoS) that aims to clarify the connections between hazards, IMs and RCSs. The results show that standard operating procedures (SOPs) are the top intervention, ensuring consistent and safe crane operations, and VR-based safety training (VRST) is crucial for immersive, risk-free hazard recognition. Interlocked protective devices and smart wearable technology can also enhance safety by preventing accidents and monitoring worker health in real-time. This comprehensive approach shows the potential for significant improvements in operational safety, providing an adequate framework for various industrial applications.