iz

Additive Manufacturing (AM) is regarded as an incredibly convenient manufacturing technique because it allows the construction of 3D artifacts. One of the most popular AM processes for creating functioning prototypes and components is fused deposition modeling (FDM). In FDM, the quality of printed components is greatly influenced by printing parameters settings. Studying the effect of FDM printing parameters on output responses is crucial in ensuring the quality of printed items. Therefore, this study investigates experimentally the influence of FDM printing parameters, i.e. print speed, flow rate, and extrusion temperature, on 3D printed Polylactic Acid (PLA) parts, considering surface roughness, dimensional accuracy, tensile strength, hardness, and impact strength. Dog-bone samples and impact test samples conforming to ASTM D638 type IV and ASTM D256 respectively were chosen for experimental testing. Taguchi’s L9 orthogonal array method was utilized to design the experimental runs. Analysis of Variance (ANOVA) was employed to assess the statistical significance of FDM printing parameters. For single response optimization, the Taguchi-based Signal-to-Noise (S/N) ratios were utilized. To optimize multiple responses, a combination of Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) and Criteria Importance through Inter-criteria Correlation (CRITIC), along with Taguchi-based S/N ratios, was applied. Based on the ANOVA results, flow rate was found to be the most significant parameter affecting all the measured responses, whereas extrusion temperature was found to be insignificant for all measured responses. However, print speed was found to be significant only for surface roughness. The optimized 3D printing process parameters obtained for multi responses were flow rate = 100% (level 2), print speed = 90 mm/s (level 3), and extrusion temperature = 210 (level 2).

Keywords: Additive Manufacturing, Analysis of Variance (ANOVA), Fused Deposition Modeling (FDM), Multi-Objective Optimization based on Ratio Analysis (MOORA), Criteria Importance through Inter-criteria Correlation (CRITIC), Taguchi Analysis.