Statistical Optimization of Wire Arc Additive Manufacturing Parameters Using Taguchi Methodology

Wire Arc Additive Manufacturing (WAAM) is an emerging metal additive manufacturing process known for its high deposition rates and cost-effectiveness in fabricating large-scale components. However, the quality of the final build is highly sensitive to process parameters such as wire feed rate, travel speed, voltage, and current. In this study, the Taguchi method is employed to statistically optimize key WAAM process parameters with the aim of improving surface finish and mechanical integrity of the deposited parts. An L9 orthogonal array was used to design experiments, and signal-to-noise (S/N) ratios were analyzed to identify optimal parameter settings. Analysis of variance (ANOVA) was performed to determine the significance of each factor on the selected output responses. The results demonstrated that specific combinations of process parameters can significantly reduce surface roughness and enhance bead geometry. The optimized settings obtained through the Taguchi approach provide a robust foundation for producing high-quality WAAM components with minimal post-processing requirements.