Authors: Seth Leavitt
Mentors: Nathan Crane
Insitution: Brigham Young University
One common form of 3D printing is Fused filament fabrication (FFF). In this process, a plastic filament is melted and extruded one line at a time to form a 3D shape. FFF often has problems that arise during printing that can cause the rest of the print to fall apart or otherwise fail. We assessed the feasibility of classifying 3D printing errors in prints using Thermography and data processing. We did this by taking constant thermal video of a specially designed printer to collect our temperature data. Then, using a constant travel speed on the printhead and using the distance traveled, we calculated the speed at which the cooling occurs. We collected cooling data on both control prints as well as parts with simulated defects (gaps in the print substrate). By analyzing the differences between the two sets of data, we determined that is feasible to identify anomalies in the printed part. This is a first step towards improving the quality of 3D-printed parts.