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Intelligent assembly system for mechanical products and key technology based on internet of things

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Abstract

The Internet of Things (IoT) has a significant effect on the development of manufacturing technology. Therefore, according to the analysis of the challenges and opportunities faced by manufacturing industry, this study uses the assembly process of mechanical products as the research object and analyzes the characteristics of IoT-based manufacturing systems. To improve the interconnection, perception, efficiency, and intelligence of the assembly system, this study proposes the concept of IoT-enabled intelligent assembly system for mechanical products (IIASMP). The IIASMP framework, which is based on advanced techniques such as information and communication technology, sensor network, and radio-frequency identification, is then presented. Key technologies under this framework, including assembly resources identification, information interaction technology, multi-source data perception and fusion, intelligent assembly agent, and value-added data and dynamic self-adaptive optimization, are described. Finally, the current results of IIASMP are described in the case study. The proposed framework and methods aims to have an important reference value for applying the key technologies and be used widely in the intelligent manufacturing field.

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Acknowledgments

The authors would like to acknowledge the financial support of the National Science Foundation of China (51375134) and National Basic Research Program of China (973 Program #2011CB013406).

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Authors and Affiliations

  1. School of Mechanical and Automotive Engineering, Hefei University of Technology, 193 Tunxi Road, Hefei, 23009, Anhui, China

    Mingzhou Liu, Jing Ma, Ling Lin, Maogen Ge, Qiang Wang & Conghu Liu

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  1. Mingzhou Liu
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  2. Jing Ma
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  3. Ling Lin
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  5. Qiang Wang
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Correspondence to Jing Ma.

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Liu, M., Ma, J., Lin, L. et al. Intelligent assembly system for mechanical products and key technology based on internet of things. J Intell Manuf 28, 271–299 (2017). https://doi.org/10.1007/s10845-014-0976-6

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