Interpreting the effect of critical control settings on the quality metrics of thermoplastic polyimide in extrusion based additive manufacturing

In Fused Filament Fabrication (FFF) 3D printing, surface quality, dimensional accuracy, and porosity are often reasons for negative criticism affecting the quality of 3D printed parts. These parameters affect the mechanical performance of the parts, too. This is more intense for high-performance polymers (HPPs), such as polyimide (PI), owing to their high cost and demanding operating conditions, in addition to their printing challenges. In this study, a Taguchi L16 orthogonal array was formed to evaluate the influence of nozzle temperature, printing speed, Raster Orientation (RO), infill density, and Strand Width (SW) on these quality responses. The aim of this study was to determine the optimal set of parameters. All metrics were notably improved (porosity was reduced by approximately 60%). RO was ranked first for all responses, whereas SW did not have much of an impact. The reduced quadratic regression and quadratic regression models were examined, and the first was selected to process the data. The correlation Coefficients (R²) were high for the geometrical deviation and porosity metrics (68% to 92%), and medium for the surface quality metrics. However, the deviation in the two additional runs performed to confirm the validity of the prediction functions was excellent (less than 10% for all metrics), verifying their accuracy. This work provides valuable insight into the effect of process parameters on the quality of FFF 3D printed parts with PI HPP, improving their applicability and performance.