The use of AM technologies to produce small batches of highly customized, complex parts, in a reduced development cycle results extremely attractive. Unfortunately, there is a disconnect between the final mechanical response of the printed parts, and the underlying process indicators that arise during fabrication – such as extrusion speed and required filament force. The end goal of this project is having the framework necessary to predict the mechanical response of FFF parts based on process variables measured during a print using machine learning techniques and an FFF printer modified with sensors.
Contact: zliu892@wisc.edu
Figure 1
Sensor setup