Abstract
Submerged arc additive manufacturing (SAAM) enables high-rate fabrication of large Inconel 718 components; however, process optimization is constrained by complex thermal–microstructural interactions. This study presents an integrated experimental–numerical–optimization framework combining Taguchi design of experiments, transient thermal simulation, and evolutionary multi-objective optimization to identify robust SAAM processing windows. A Taguchi L25 orthogonal array was employed to evaluate the effects of arc voltage, wire feed rate, and carriage speed on deposition behavior. Transient finite-element simulations using a calibrated Goldak double-ellipsoid heat source captured melt pool evolution, thermal gradients, and interpass reheating effects. Gray Wolf Optimizer-based Pareto optimization was then applied to simultaneously maximize deposition rate and minimize heat input. The Pareto front revealed an optimal regime characterized by a high wire feed rate of 3.5 m min−1 and a carriage speed of 0.6 m min−1, with arc voltage governing the productivity—thermal trade-off. Microstructural characterization revealed predominantly columnar dendritic γ-grains with epitaxial growth along the build direction, localized columnar-to-equiaxed transitions due to interpass reheating, and Nb-rich Laves phase segregation in interdendritic regions. Vickers microhardness values ranged from 195 to 259 HV, with higher hardness observed in regions exhibiting finer dendritic arm spacing due to rapid cooling near the substrate, while reduced hardness in upper layers was attributed to reheating-induced dendrite coarsening and increased solute segregation. The integrated optimization framework establishes a direct correlation between SAAM process parameters, thermal history, microstructural evolution, and mechanical response, demonstrating the potential of SAAM for high-productivity fabrication of Inconel 718 components.
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