Bin Hu

In response to the agility demands of Industry 5.0, this study pioneers a laboratory-based prototype of a DAO-powered, cyber-physical-social system (CPSS) employing intelligent collaborative robots for parallel manufacturing and management. We introduce the concept of Parallel Triplets, integrating the microphysical dimension into the existing digital and physical realms of the digital twin, enabling faster prototype realization and simultaneous execution of production tasks. This facilitates a decentralized DAO framework where intelligent agents, guided by parallel triplets data, make real-time production decisions and optimize resource allocation, leading to dynamic, collaborative, and autonomous manufacturing. Our empirical research demonstrates the success of this approach, achieving enhanced production efficiency, reduced defect rates, and empowered worker autonomy. This paper contributes to the advancement of Parallel Triplets technology and showcases the transformative potential of DAOs in driving agile, intelligent, and collaborative manufacturing within Industry 5.0.

This article proposes a parallel flexible manufacturing system (FMS), which is divided into three subparallel systems, including a parallel manufacturing system, a parallel inspection system, and a parallel loading–unloading system. By building a chess parallel manufacturing production line, the lightweight practice of a parallel FMS is completed. Based on the parallel system ACP idea, the parallel FMS can realize the agility advantage of flexible manufacturing to quickly respond to diverse needs; realize the ability to quickly correct defective products; and predict and optimize the production process through the analysis and modeling of production data, reducing the product quality defect rate. This article also proposes the concept of parallel flexible manufacturing triplets, adding a microphysical world to the artificial world and the physical world, highlighting the rapid iteration characteristics of flexible manufacturing.

At present, there are many challenges for robotic systems to grasp in a dynamic and unstructured environment. The competition of Robotic Grasping and Manipulation Challenges (RGMC) aims to promote researchers to focus on these challenges. The solution proposed in this paper participated in the 2019&2020 RGMC and achieved the first prize and the second prize. The solution designed a new type of composite gripper to complete the task of making milk tea in the competition. This solution is based on Rethinks Sawyer robot, using the ability of machine vision and force control, complete the precise identification and dexterous control of dynamic objects in the competition task.