Integrated Taguchi-Based Optimization of Key FDM Parameters to Improve both Mechanical Performance and Surface Finish for PLA Material

Abstract Enhancing the mechanical properties and surface finish of components fabricated via Fused Deposition Modeling (FDM) is essential to ensuring structural integrity and reliability in engineering applications. This study proposes an optimization methodology to identify the optimal FDM process parameters for polylactic acid (PLA) material that simultaneously improve mechanical performance and surface quality. The effects of three key FDM parameters—layer height, infill density, and nozzle temperature—on the tensile strength and surface roughness of printed samples were systematically investigated. Using the Taguchi method combined with Grey Relational Analysis (GRA), the optimal settings were determined to be a 0.15 mm layer height, 70% infill density, and a nozzle temperature of 210 °C. Under these conditions, the fabricated samples achieved a tensile strength of 37.12 MPa and a surface roughness of 5.23 µm, demonstrating significant improvements in both strength and surface finish. By integrating rigorous experimentation with robust statistical analysis, the proposed framework contributes to advancing additive manufacturing practices and provides a reliable approach for enhancing the quality of PLA-based FDM components.