Multi-objective optimization of 3D printing process parameters using gray-based taguchi for composite PLA parts

Abstract

This study investigates the additive manufacturing (AM) process of 30% ceramic-reinforced composite PLA material using the fused deposition modeling (FDM) technique. The effects of various printing parameters on tensile strength, build time, and material consumption are comprehensively analyzed through a combination of the Taguchi method, analysis of variance (ANOVA), and gray relational analysis (GRA). Experimental design parameters include nozzle diameter, infill density, infill pattern, wall line count, print speed, and layer height. Statistical analyses reveal significant contributions of these parameters to mechanical properties and production efficiency. Single and multi-objective optimizations of the responses were performed. The single optimization resulted in a significant increase in tensile strength from 39.9 to 48.10 MPa. Production time was reduced from 16 to 9 min; material consumption decreased from 4.95 to 2.43 g for tensile test specimens. The use of GRA in multi-objective optimization has led to a significant improvement of 8.31% in the gray relational grade (GRG) when compared to the initial parameter settings. These findings provide valuable insights for optimizing FDM processes in the fabrication of composite PLA materials. This contributes towards the advancement of additive manufacturing technology and its applications across various industries. and its applications across various industries.