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

Mingzhou Liu, Jing Ma (mj_hfut@163.com), Ling Lin, Maogen Ge, Qiang Wang and Conghu Liu
Additional contact information
Mingzhou Liu: Hefei University of Technology
Jing Ma: Hefei University of Technology
Ling Lin: Hefei University of Technology
Maogen Ge: Hefei University of Technology
Qiang Wang: Hefei University of Technology
Conghu Liu: Hefei University of Technology

Journal of Intelligent Manufacturing, 2017, vol. 28, issue 2, No 2, 299 pages

Abstract: 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.

Keywords: Intelligent assembly system; Internet of things; Dynamic self-adaptive optimization; Information interaction technology; Intelligent assembly agent (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s10845-014-0976-6

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