Digital twin integration in metalworking: enhancing efficiency and predictive maintenance - Villegas-Ch, William; Gutierrez, Rommel; Govea, Jaime (Frontiers in Mechanical Engineering, 2025)
In the era of Industry 4.0, the integration of advanced technologies such as digital twins represents a strategic opportunity for process optimization in the metalworking industry. Although their potential has been widely acknowledged, many companies face significant challenges in implementation, particularly in terms of operational efficiency, predictive maintenance, and economic feasibility. This study addresses how a digital twin can be effectively deployed within metalworking operations to solve concrete production issues, enhance decision-making, and optimize resource utilization. The proposed system models critical processes, such as milling, welding, and material flow, and integrates real-time data to enable continuous improvement. Through a longitudinal evaluation, the implementation of the digital twin resulted in a 30% reduction in material waste, a 40% decrease in the rejection rate of milled parts, and a return on investment of 233% over 5 years. These results provide empirical evidence of the digital twin’s capacity to drive both operational excellence and economic return. This work contributes to the existing literature by offering a robust quantitative assessment of digital twin deployment in metalworking, emphasizing its practical benefits and strategic relevance.