Optimization of Process Parameters and Material Properties in Additive Manufacturing with 3D Printing

Abstract

We investigated how adjusting process parameters and material characteristics can improve 3D-printed parts. We focused on Fused Deposition Modeling (FDM) with PLA polymer as a case study. Design of experiments (DOE) methods like Taguchi and response surface methodology were used to systematically vary factors such as layer thickness, print speed, and extrusion temperature. Specimens were built in different orientations and tested for density, surface finish, and mechanical strength. Results show that optimal settings significantly increase tensile strength and dimensional accuracy. For example, the best conditions reduced surface roughness by ~30% and improved tensile strength by ~20% over the baseline. A multi-objective optimization identified trade-offs between strength and print time, leading to a Pareto-optimal parameter set. Key improvements were confirmed with follow-up prints using the optimal settings. Our study contributes guidelines for selecting parameters to achieve desired build quality and material properties, bridging gaps in current AM practice.