Research Review on Workshop Scheduling for Intelligent Manufacturing: Digital Twin Modeling, Optimization Algorithm, and System Architecture

Digital twin, as a new generation of industrial intelligent technology, has become a key technology for achieving virtual-physical interaction and real-time optimization in intelligent manufacturing systems due to its capability for high-fidelity virtual mapping of physical systems. Production scheduling, as the core link in the operation of intelligent workshops, faces challenges such as frequent dynamic disturbances, rendering traditional static scheduling approaches inadequate to meet the real-time and flexibility requirements of backdrop operations. In this context, the significant potential of the deep integration of digital twin technology and workshop scheduling in enhancing scheduling real-time performance, agility, and robustness has increasingly been highlighted. This paper reviews the research progress in workshop digital twin scheduling technology over the past five years, focusing on the development paths and technical characteristics of typical workshop digital twin modeling techniques, intelligent scheduling algorithms, and system frameworks. Based on this, the paper proposes a conceptual framework for digital twin scheduling in complex manufacturing scenarios, providing theoretical references for developing highly real-time and robust intelligent manufacturing scheduling systems, and highlights future research directions and developmental trends.