Optimization of Properties for 3D Printed PLA Material Using Taguchi, ANOVA and Multi-Objective Methodologies

Abstract

In recent years, there has been an increasing interest in 3D printing technology. Fused deposition modeling (FDM) is the most popular 3D printing technology on the market. Selecting the best possible level for process parameters is one of the greatest challenges. Therefore, this research work aims to provide insights on the influence of process parameters of FDM on mechanical properties of printed parts using design of experiments (DOE) methods. In order to investigate the effect of process parameters on the tensile characteristics of 3D printed Polylactic Acid (PLA) material, some input design parameters including infill density, extrusion temperature, raster angle, and layer thickness are considered as variable. Using the Taguchi optimization methodology and ANOVA the dependency of mechanical properties (such as ultimate tensile stress, yield strength, modulus of elasticity, toughness, and elongation at break) on the process parameters is studied. Finally, the investigated mechanical properties were optimized and the suitable levels of printing process parameters were proposed by regression equations and mathematical modeling. According to the performed optimization method, for the tensile strength and toughness values, the optimum 3D printing input parameters were obtained at infill density of 60 %, extrusion temperature of 200oC, raster angle of 45/-45, and layer thickness of 0.2mm. Similarly, the optimum input parameters for maximizing the other investigated strength properties were obtained at 60%, 220oC, 0/90, and 0.1mm, respectively. furthermore, since optimized process parameters of the toughness and ultimate tensile strength indexes were obtained at different input variable levels, a multi-objective optimization method was performed to obtain Pareto front in which suggests input variables that provide optimize values of toughness and strength simultaneously.