Digital Twin Technology of Human–Machine Integration in Cross-Belt Sorting System
Yanbo Qu, Ning Zhao, Haojue Zhang
Abstract
Abstract The Chinese express delivery industry processes nearly 110 billion items in 2022, averaging an annual growth rate of 200%. Among the various types of sorting systems used for handling express items, cross-belt sorting systems stand out as the most crucial. However, despite their high degree of automation, the workload for operators has intensified owing to the surging volume of express items. In the era of Industry 5.0, it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems. Striking a balance between efficiency in handling express items and operator well-being is challenging. Digital twin technology offers a promising solution in this respect. A realization method of a human–machine integrated digital twin is proposed in this study, enabling the interaction of biological human bodies, virtual human bodies, virtual equipment, and logistics equipment in a closed loop, thus setting an operating framework. Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources, construction of the relationship between operator fatigue and operation efficiency based on physiological measurements, virtual model construction, and an online optimization module based on real-time simulation. The feasibility of the proposed method was verified in an express distribution center.