Abstract
With the growth of personalized demand and the development of Industry 4.0, the limitations of traditional printing technology are increasingly prominent, and people's requirements for printing quality are constantly improving. In this study, the existing 3D printing control system is first studied, and then an AI control system based on DNN is designed and implemented. The system can optimize printing parameters by learning historical printing data, and automatically adjust the printing process to improve printing quality and resource utilization. The experimental results show that the printing speed of the automatic control system of 3D printing based on DNN can reach 297 cm/s, the surface roughness can be as low as 2μm, and the resource utilization rate can reach 88%, which significantly reduces the energy consumption and material waste in the printing process, and improves the surface quality and structural integrity of printed materials.
Published Version
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