Digital Twin-driven Multi-objective Optimization Production Scheduling with Restraint Tool Resources

In recent years, digital twin has become a key technology for intelligent transformation of manufacturing industry, providing a new paradigm of smart manufacturing. The scheduling planning of traditional workshops is mostly based on unlimited resource conditions because the remaining useful lifetime of manufacturing resources such as cutting tools cannot be obtained in real time. In this paper, a digital twin-driven production scheduling framework is proposed that integrated the problems of equipment predictive maintenance and production scheduling. Under this framework, an improved NSGA-II algorithm is proposed to combine cutting tool predictive maintenance and production scheduling tasks, and experimental results show that the algorithm has better performance.