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International Journal of Frontiers in Engineering Technology, 2021, 3(8); doi: 10.25236/IJFET.2021.030806.

Modeling and Key Technologies of Intelligent Assembly System for Mechanical Products


Hui Chen1, Gang Wang2

Corresponding Author:
Gang Wang

1Taizhou Shenzhou Transmission Technology Co., Ltd., Taizhou, Jiangsu, China

2Taizhou Institute of Science and Technology, Nanjing University of Science and Technology, Taizhou, Jiangsu, China


Manufacturing is country's pillar industries and the core driving force of national economic development. Among them, the machinery manufacturing industry provides technical equipment for the development of the whole country, which plays a decisive function of the development of the national economy and the progress of science and technology. As the increased competition in the global market, the machinery manufacturing industry is facing unprecedented severe challenges. Assembly has a great impact on product quality and the characteristics of complex operating processes, as it is the last part of the mechanical product manufacturing process and therefore often determines the level of mechanically manufactured products. The purpose of this paper is to improve the intelligence level of assembly systems through the development and application of Internet of Things technology. Take the mechanical product assembly system as the research object, the research methods are as follows: First, on the basis of analyzing the connotation and characteristics of manufacturing associations, proposed the manufacturing environment of the Internet of Things. Then, constructed the overall operation framework, network physical environment and topology structure are of the system, and refined the key technologies of system modeling. Object-oriented Petri nets and VisObjNet simulation techniques are used for abstract modeling and simulation systems. Finally, developed the prototype of the intelligent assembly system of mechanical products under the Internet of Things background, and further verified the feasibility and effectiveness of the method proposed in this paper. The research results show that the prediction accuracy of the online monitoring system can reach 98.8% by collecting acceleration and noise in real time. The efficient and green processing parameter optimization system greatly optimizes the original processing efficiency. The method proposed in this paper effectively improves the transparency of the mechanical product assembly process. It provides a reference model and implementation path for building a smart assembly system for mechanical products under the IoT environment.


Mechanical Products, Assembly Systems, Model Building, Internet of Things

Cite This Paper

Hui Chen, Gang Wang. Modeling and Key Technologies of Intelligent Assembly System for Mechanical Products. International Journal of Frontiers in Engineering Technology (2021), Vol. 3, Issue 8: 39-49. https://doi.org/10.25236/IJFET.2021.030806.


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