• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2018, Vol. 54 ›› Issue (16): 34-44.doi: 10.3901/JME.2018.16.034

Previous Articles     Next Articles

Self-organizing Production Technology for Discrete Workshop Scheduling Driven by Internet of Things

ZHANG Zequn1, TANG Dunbing1, JING Yongqiao2, ZHANG Haitao1   

  1. 1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;
    2. Shanghai Spaceflight Precision Machinery Institute, Shanghai 201600
  • Received:2017-08-07 Revised:2018-03-29 Online:2018-08-20 Published:2018-08-20

Abstract: With the increasing requirement for personalized customization service, discrete workshop as a unit in manufacturing system will first have to deal with this challenge which is caused by the personalized customization service. Personalized customization task is stochastic, and the status of shop floor is uncertain before the order arrival. Therefore, it is difficult to establish the traditional scheduling model, and an automated production method is needed. Based on the manufacturing technology of internet of things and the theory of completely dynamic scheduling, the method of self-organization production in job shop layer and real-time dynamic scheduling without scheduling model are studied. The discrete workshop is selected for the study, and the instrumented environment based on Radio Frequency Identification for real-time manufacturing process is constructed. On this basis, the individual intelligent of physical resource oriented is established, and the goal is to make the device becoming an intelligent unit with the capacity of communication, analysis and decision-making. In addition, due to the fact that a system supervisor intelligent individual is introduced, the weakness that the global performance of the scheduling mechanism is difficult to raise in traditional fully dynamic scheduling can be overcome. Finally, the proposed approaches are applied to a micro-factories in a laboratory, the result show that the self-organizing production of individual orders can be carried out and it can effectively integrate production resources.

Key words: dynamic scheduling, individual intelligent, personalized customization, self-organizing

CLC Number: