Research on multiple regression linear prediction model of 3D printing process parameters

Lianghua Zeng; Wenxiong Wu; Zhen Li

doi:10.1117/12.2679759

18 July 2023 Research on multiple regression linear prediction model of 3D printing process parameters

Lianghua Zeng, Wenxiong Wu, Zhen Li

Proceedings Volume 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023); 127224Q (2023) https://doi.org/10.1117/12.2679759
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 2023, Hangzhou, China

Abstract

The process parameters of 3D printing have a great influence on the printing accuracy, and the printing process parameters of different models are quite different. The specific quantitative relationship between the process parameters and printing accuracy of different models has not been built, and no prediction model for printing accuracy has been established. Therefore, on the basis of using the orthogonal test method to carry out the 3D printing experiment of the semi-cylindrical model, the paper studies the quantitative relationship between four process parameters and the two dimensions of cross-sectional profile and printing height, such as layer thickness, printing speed, nozzle temperature and hot bed temperature. This paper also establishes a multiple regression linear prediction model. At the same time, the paper carries out the linear regression analysis, and obtains the reliability, linearity of the multiple regression equation and the priority of the influence of the process parameters. The study finds that the printing accuracy on the contour and height of the 3D printed part is jointly controlled by multiple process parameter levels; the reliability and linearity of the model's multiple regression equation on the height are better than the model's multiple regression on the contour; the influence of layer thickness on model printing accuracy is the most significant. The research can provide some reference for the effective control and prediction of printing accuracy.

Citation Download Citation

Lianghua Zeng, Wenxiong Wu, and Zhen Li "Research on multiple regression linear prediction model of 3D printing process parameters", Proc. SPIE 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 127224Q (18 July 2023); https://doi.org/10.1117/12.2679759

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KEYWORDS

Printing

3D modeling

3D printing

Contour modeling

Fused deposition modeling

Nozzles

Matrices

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