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A Novel Multi-Agent-Based Collaborative Virtual Manufacturing Environment Integrated with Edge Computing Technique

Author

Listed:
  • Xiaohui Zhang

    (School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China)

  • Shufeng Tang

    (School of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)

  • Xinhua Liu

    (School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China)

  • Reza Malekian

    (Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa)

  • Zhixiong Li

    (School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong NSW 2522, Australia)

Abstract

This paper proposes a multi-agent-based collaborative virtual manufacturing environment (VME) to save energy consumption and improve efficiency in the manufacturing process. In order to achieve the high autonomy of the manufacturing system, a multi-agent system (MAS) is designed to build a collaborative VME. In this new VME environment, edge computing is embedded to strengthen the cyber resource utilization and system economy. Moreover, an efficient communication channel between networks is proposed. The subsequent cooperation and collaboration protocols among agents are designed to ensure flexible and process-oriented operations. Furthermore, the fuzzy resolution algorithm is employed to resolve the competition conflicts among function-similar MASs in the distributed manufacturing scenario. Lastly, a simulation and case study are performed to evaluate the performance of the proposed VME in Internet of Things (IoT)-based manufacturing. The analysis results have demonstrated the feasibility and effectiveness of the proposed VME system.

Suggested Citation

  • Xiaohui Zhang & Shufeng Tang & Xinhua Liu & Reza Malekian & Zhixiong Li, 2019. "A Novel Multi-Agent-Based Collaborative Virtual Manufacturing Environment Integrated with Edge Computing Technique," Energies, MDPI, vol. 12(14), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2815-:d:250557
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    References listed on IDEAS

    as
    1. Yuqiuge Hao & Ahm Shamsuzzoha & Petri Helo, 2015. "Cloud-based Data Storage for Data Management in the Virtual Factory," Palgrave Macmillan Books, in: Fawzy Soliman (ed.), Cloud Systems in Supply Chains, chapter 16, pages 280-299, Palgrave Macmillan.
    2. Chen, Chen-Tung & Lin, Ching-Torng & Huang, Sue-Fn, 2006. "A fuzzy approach for supplier evaluation and selection in supply chain management," International Journal of Production Economics, Elsevier, vol. 102(2), pages 289-301, August.
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