Multi-Objective Optimization of PLA Biopolymer FDM 3D Printing for Improved Impact Strength, Surface Quality and Production Efficiency via Grey Relational Analysis

This study investigates the influence of layer height, infill density, and the number of perimeters on the FDM 3D printing performance of PLA, a biodegradable and renewable biopolymer. The primary objective is to identify parameter settings that simultaneously maximize impact strength and production efficiency, quantified through filament usage and printing time. In addition, 3D surface profilometry was employed as a non-destructive characterization method to evaluate surface roughness, assess its dependence on process parameters, and establish correlations with destructive impact strength testing. Experimental work was conducted using a Taguchi L9 orthogonal array, and regression-based mathematical models were developed to quantify the effects of individual parameters on the analysed responses. Finally, Grey Relational Analysis (GRA) was applied to perform multi-objective optimization and determine parameter combinations that jointly enhance mechanical durability, surface quality, and production efficiency. The results provide a clear set of manufacturing parameter settings that satisfy both destructive and non-destructive performance criteria while ensuring resource-efficient production.