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Cloud automatic mechanical equipment based on D–T fuzzy control and internet of things

Author

Listed:
  • Jie Yao

    (Hunan Mechanical And Electrical Polytechnic)

  • Feng Wu

    (Hunan Mechanical And Electrical Polytechnic)

Abstract

With the emerging development of the automatic systems and the cloud platforms, the proper combination is the developing trend. Hence, design and innovation of automatic mechanical equipment based on the D–T fuzzy control system considering Internet of Things is demonstrated in this paper. In the process of R&D and manufacturing of modern automated machinery and equipment, we must also pay attention to the improvement of the overall quality of operators. Through incentive measures, the initiative and enthusiasm of the work are continuously improved, and finally the sustainable development of the machinery manufacturing industry is promoted. This paper gives the novel perspectives of enhancing basic model. We integrate the D–T fuzzy model to replace the kernel support vector machines to serve as the general flowchart for the model, the cloud system is implemented with the Internet of Things to serve as the support of the hardware. We compare the proposed model with the other platforms, the experimental results have shown that the designed system is robust and efficient.

Suggested Citation

  • Jie Yao & Feng Wu, 2022. "Cloud automatic mechanical equipment based on D–T fuzzy control and internet of things," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(4), pages 1696-1704, August.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:4:d:10.1007_s13198-021-01525-w
    DOI: 10.1007/s13198-021-01525-w
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    References listed on IDEAS

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    1. Matteo Barbieri & Khan T. P. Nguyen & Roberto Diversi & Kamal Medjaher & Andrea Tilli, 2021. "RUL prediction for automatic machines: a mixed edge-cloud solution based on model-of-signals and particle filtering techniques," Journal of Intelligent Manufacturing, Springer, vol. 32(5), pages 1421-1440, June.
    2. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu, 2021. "Fuzzy Control System for Smart Energy Management in Residential Buildings Based on Environmental Data," Energies, MDPI, vol. 14(3), pages 1-18, February.
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