Real-time material extrusion volume control system for 3D food printers

Abstract To achieve high-quality printing with a 3D printer, it is important to set optimal printing parameters. In our research, we have advanced the development of a 3D food printer capable of rendering a variety of food products. Notably, the rheological properties of food-based inks are influenced by the constituent ingredients, ambient conditions such as temperature and humidity, and the specific recipe utilized, which significantly affects the precision of the printed models with the 3D food printers more than with conventional FDM (Fused Deposition Modeling) 3D printers. Given the necessity to modify printing parameters in real-time in response to fluctuations in temperature and material consistency, the process of food printing necessitates ongoing monitoring.An automatic control system is essential for accurate printing. We devised a monitoring system within the 3D food printer to calibrate extrusion volume accurately.Leveraging machine learning techniques with a dataset comprising food substances of diverse characteristics and colors, we have successfully automated the control of extrusion volumes within the 3D food printer. The time it takes to achieve good printing conditions is similar to users who are new to 3D food printing. Additionally, it automatically handles fluctuations in extrusion rate during printing, such as those caused by room temperature. This function will let 3D food printing user-friendly and lead more active development of 3D food printing products.