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An embedded self-adapting network service framework for networked manufacturing system

Author

Listed:
  • Dapeng Tan

    (Zhejiang University of Technology
    Huazhong University of Science and Technology)

  • Libin Zhang

    (Zhejiang University of Technology)

  • Qinglin Ai

    (Zhejiang University of Technology)

Abstract

To improve the self-adapting ability and real-time performance of client/server based networked manufacturing system (NMS), this paper introduces the universal plug and play (UPnP), an intelligent network middleware, into networked manufacturing area, and proposes an embedded self-adapting network framework and related service methods. Referring to small world model and scale-free principles, a complex network model oriented to digital manufacturing is set up. Based on the model, an improved entropy vector projection algorithm is proposed to evaluate the network complexity and reveal the evolution regulars. Then, the self-adapting services for NMS are performed by UPnP service-calling and inter-process communication methods. Finally, the case studies and industrial field experiments verify the effectiveness of the proposed service framework.

Suggested Citation

  • Dapeng Tan & Libin Zhang & Qinglin Ai, 2019. "An embedded self-adapting network service framework for networked manufacturing system," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 539-556, February.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:2:d:10.1007_s10845-016-1265-3
    DOI: 10.1007/s10845-016-1265-3
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    References listed on IDEAS

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    1. Hong Zheng & Yugang Niu & Gianfranco Ciardo, 2011. "Modelling and analysis of UPnP AV media player system based on Petri nets," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(9), pages 1573-1580.
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    3. Zhou, Guangye & Li, Chengren & Li, Tingting & Yang, Yi & Wang, Chen & He, Fangjun & Sun, Jingchang, 2016. "Outer synchronization investigation between WS and NW small-world networks with different node numbers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 506-513.
    4. Chen, Jiaoliao & Xu, Fang & Tan, Dapeng & Shen, Zheng & Zhang, Libin & Ai, Qinglin, 2015. "A control method for agricultural greenhouses heating based on computational fluid dynamics and energy prediction model," Applied Energy, Elsevier, vol. 141(C), pages 106-118.
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    Cited by:

    1. Jiaxing Wang & Sibin Gao & Zhejun Tang & Dapeng Tan & Bin Cao & Jing Fan, 2023. "A context-aware recommendation system for improving manufacturing process modeling," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1347-1368, March.

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