Research on Optimizing Forming Accuracy in Food 3D Printing Based on Temperature–Pressure Dual Closed-Loop Control

In this paper, a new 3D printing system based on temperature-pressure double closed-loop collaborative control is proposed to solve the problem of 3D printing accuracy of starch food. The rapid and accurate adjustment of the nozzle temperature is realized by the hybrid control of Bang-Bang and PID, and the extrusion pressure is optimized in real time by combining the adaptive fuzzy PID algorithm, which effectively reduces the influence from the change of material rheological properties and external interference. The experimental results show that the printing accuracy of the system is up to 98% at 40 °C, the pressure fluctuation is reduced by 80%, and the molding accuracy of complex structures is improved to 97%, which significantly improves the over-extrusion and under-extrusion, and provides an effective solution for stable and high-precision printing of high-viscosity food materials.

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Publication Details

Journal
Micromachines
Published
2025-10-12
DOI
https://doi.org/10.3390/mi16101156
Citations
1
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
0.68
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article

Research on Optimizing Forming Accuracy in Food 3D Printing Based on Temperature–Pressure Dual Closed-Loop Control

Jing Shen, Xu Duan, Yanwei Xu, Hao Cao et al.
1 citations
Micromachines
Additive Manufacturing and 3D Printing Technologies
0.68
article

Research on Optimizing Forming Accuracy in Food 3D Printing Based on Temperature–Pressure Dual Closed-Loop Control

Jing Shen, Xu Duan, Yanwei Xu, Hao Cao, Tancheng Xie, Junhua Wang, Ruijie Gu
article en
1 citations

Abstract

In this paper, a new 3D printing system based on temperature-pressure double closed-loop collaborative control is proposed to solve the problem of 3D printing accuracy of starch food. The rapid and accurate adjustment of the nozzle temperature is realized by the hybrid control of Bang-Bang and PID, and the extrusion pressure is optimized in real time by combining the adaptive fuzzy PID algorithm, which effectively reduces the influence from the change of material rheological properties and external interference. The experimental results show that the printing accuracy of the system is up to 98% at 40 °C, the pressure fluctuation is reduced by 80%, and the molding accuracy of complex structures is improved to 97%, which significantly improves the over-extrusion and under-extrusion, and provides an effective solution for stable and high-precision printing of high-viscosity food materials.

MicromachinesVol. 16(10)
Henan University of Science and Technology (CN)
Openalex Percentile: Top 24%
Additive Manufacturing and 3D Printing Technologies
0.68
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