A study on digital twin technology of Human-machine integration cross-belt Sorting System

Abstract

So far nearly 110 billion pieces of express items have been handled by Chinese express delivery industry, with an average annual growth of 200%. Cross-belt sorting system serves as the most important express item sorting system and most of the sorting work has been automated fulfilled. However, operators are still needed and working pressure arisen with the growth of express items. Under the context of the industry 5.0, new technologies should be utilized to enhance both welfare of the workers and working efficiency of the cross-belt system. However, it’s hard to strike a good balance between express item handling efficiency and the happiness of operators. Digital twin technology bring new solution to this problem. Based on the ascertained human-machine features of the distribution center, the human-machine integration digital twin frame, consisting of physical space, virtual space, twin data center and supporting & application services, were proposed. The closed-loop interactions among biological human body, virtual human body, virtual equipment and physical equipment were achieved. The express item distribution center operation system was established based on the digital twin technologies. Besides, the physical-level data collection and storage, the human body fatigue efficiency conversion process on services levels and the virtual-level predication & decision-making were elaborated. Finally, methods to establish the cross-belt sorting system for the express item distribution center based on digital twin technologies were proposed. Feasibility of the aforesaid methods was verified by a simulation case study.

Research on the Algorithm of Position Correction for High-Speed Moving Express Packages Based on Traditional Vision and AI Vision

“…With the exponential growth of the e-commerce sector, logistics companies are encountering a significant surge in order volumes and an intensified demand for sorting tasks [1][2][3][4]. Currently, conventional manual sorting methods are inadequate to manage these escalated sorting demands.…”