• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2025, Vol. 61 ›› Issue (13): 265-281.doi: 10.3901/JME.2025.13.265

Previous Articles    

Task Production Progress Prediction Approach in Distributed Cooperative Manufacturing Based on Cloud-edge Collaboration

ZHU Haihua1, WANG Jianjie1, LI Fei2, LIU Changchun1, CAI Qixiang1, TANG Dunbing1   

  1. 1. College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;
    2. Beijing Institute of Electronic System Engineering, Beijing 100854
  • Received:2024-07-08 Revised:2024-12-22 Published:2025-08-09

Abstract: The high-end equipment manufacturing industrial chain involves multiple enterprises, various professional categories, and wide geographic distribution. The product order is broken down into several sub-tasks, and these sub-tasks are distributed to different manufacturing workshops for cross-enterprise manufacturing. This manufacturing mode has typical characteristics of distributed manufacturing. In the current environment where business processes and manufacturing systems are increasingly complex and unstable, accurate prediction of each sub-task production progress allows for the timely detection of production schedule fluctuations, and helps enterprises avoid long-term stagnation of the overall project, ensuring orderly progress and delivery of the project. In response to the problem that traditional data analysis methods are not suitable for complex manufacturing environment and the ability of enterprises to utilize distributed resources is weak, a task production progress prediction approach in distributed cooperative manufacturing based on Cloud-Edge collaboration is proposed. A distributed collaborative manufacturing platform architecture with high freedom and easy management is realized based on multi-workshop production situation and service demand. Based on the platform architecture, two key collaboration mechanisms of cloud-edge data collaboration and model collaboration are proposed. According to the demand of production progress prediction, three key approaches of workshop data transmission and integration, manufacturing data preprocessing and distributed collaborative manufacturing task production progress prediction are proposed. Finally, a case of distributed manufacturing is used to verify the feasibility and effectiveness of the proposed approach.

Key words: high-end equipment manufacturing, distributed cooperative manufacturing, production progress, cloud-edge collaboration, manufacturing service

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