Multi-Response Optimization of Fused Deposition Modeling Parameters Using an Integrated Taguchi–MRSN–TOPSIS Approach for Product Quality Improvement

Abstract

Fused Deposition Modeling (FDM) is one of the most widely used Additive Manufacturing technologies; however, product quality is strongly influenced by complex and inherently multi-response process parameter combinations. This study aims to optimize FDM process parameters by considering three quality responses, namely tensile strength, flexural strength, and surface roughness. The proposed approach integrates the Taguchi method, Multi-Response Signal-to-Noise Ratio (MRSN), and the multicriteria decision-making technique Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Seven FDM process parameters were investigated at two levels using PLA material and a predefined FDM system configuration. The results indicate that the parameter combination A2 B2 C2 D2 E2 F2 G2—representing a layer thickness of 0.4 mm, printing temperature of 220 °C, four wall lines, hexagonal infill pattern, 80% infill density, printing speed of 80 mm/s, and nozzle diameter of 0.4 mm—constitutes the most optimal compromise configuration. This configuration yields a tensile strength of 41.865 MPa (an increase of 25.005 MPa), a flexural strength of 87.321 MPa (an increase of 38.3 MPa), and a surface roughness of 1.688 μm (a reduction of 18.73 μm). The TOPSIS ranking consistently places this alternative at the highest position. Sensitivity analysis of the criteria weights demonstrates that the recommended parameter configuration remains relatively stable within the tested preference ranges, confirming that the integration of Taguchi–MRSN–TOPSIS provides an effective, transparent, and reproducible multi-response optimization framework.