Enhancing Labor Flexibility in Industry 5.0: Integrating Discrete Event Simulation and Digital Twin for Human-Centric Production Efficiency

This study investigates the integration of Discrete Event Simulation (DES) and Digital Twin (DT) to enhance labor flexibility (LF) in Industry 5.0 (I5.0) settings. I5.0 aims for a human-centered approach to manufacturing by combining advanced technologies with human adaptability, thus improving operational efficiency while emphasizing worker well-being. We propose a novel framework that enhances DES with real-time data, IoT sensor integration, and predictive analytics to facilitate the transition into a fully capable DT. This integration directly addresses the limitations of traditional LF models, which are typically based on static pre-simulation analyses. By transforming DES into a dynamic and proactive DT, we achieve a system capable of real-time responsiveness, advanced labor allocation, and predictive adaptability, aligning closely with I5.0 goals. Our findings demonstrate significant improvements in operational performance, including reduced idle-times, optimized workforce utilization, and enhanced throughput, all while ensuring a human-centric approach that minimizes worker disruption. This study contributes to the evolution of labor management in modern production environments, bridging the gap between static simulation models and realtime adaptive systems.