Multi-Objective Optimization of the Mechanical Properties of 3D-Printed PLA: An Integrated Taguchi and NSGA-II Approach

Fused deposition modeling (FDM) of polylactic acid (PLA) is widely used, yet most parameter studies tune one mechanical property at a time and leave the conflicts between properties unresolved. This work treats three responses of FDM PLA together: ultimate tensile strength, flexural strength, and Shore D hardness. A Taguchi L9 orthogonal array varied infill density, raster angle, and layer thickness; signal-to-noise ratios and analysis of variance ranked the factors, linear regression linked the parameters to each response, and the NSGA-II algorithm mapped the trade-off surface between them. Layer thickness proved the leading factor for tensile and flexural strength, while hardness answered mainly to infill density; raster angle stayed weak for every response. The Pareto front showed that low infill favors tensile strength while high infill favors flexural strength and hardness, all at the finest layer setting, and these trends were converted into parameter guidelines for tensile-led, flexure-led, and balanced parts. The statistical limits of the screening design are stated openly, the flexural and hardness campaigns are flagged as provisional, and a replicated, standard-compliant confirmation study is set out as the next step.