Investigation on geometric, dimensional accuracy and surface roughness for 3D printed PLA via fused deposition modelling (FDM) process

Fused deposition modeling (FDM) is an advanced additive manufacturing technique known for its precision and repeatability, extensively applied in producing automotive and industrial components. This study employs the Taguchi L 9 orthogonal array (OA) approach to optimize process parameters for minimizing dimensional inaccuracies, geometric deviations, and surface roughness (Ra) in polylactic acid (PLA) specimens fabricated as per ASTM D638 Type V standards. Four critical printing parameters: extrusion temperature (ET), infill pattern (Ip), print rate (Rp), and layer height (LH) are investigated, focusing on specimen thickness (Ts), width of the grip section (Wgs), overall length (OL), circularity (Circ), cylindricity (Cyl), surface roughness (Ra), and waviness (Wa). Signal-to-noise (S/N) ratio analysis identified optimal parameter combinations, revealing that Ip, ET, and Rp significantly influence circularity by 39.24%, 37.34%, and 15.19%, respectively. One of the important factors that affect the degree of inaccuracy in cylindricity is the Ip. Gyroid pattern generated the least amount of inaccuracy out of all the patterns that were tested. Layer height (LH) at 0.1 mm was the most critical factor affecting Ra and Wa, while an extrusion temperature of 215°C predominantly influenced Ts. The Ip has the most affected the grip section width. In contrast to expectation, the triangle Ip achieved the minimum width error that was 0.3384%. The Rp of 40 mm/s has the highest impact on the OL deviations. Out of all the other patterns, the Tri-Hexagon (Ip) has made the least contribution to the OL deviations. Rp exhibited a lower contribution to Ra (2.35%) and Wa (12.45%). The results demonstrate the effectiveness of the Taguchi approach in identifying optimal process setups for enhancing the precision, geometric accuracy, and surface quality of 3D-printed specimens.