Copper 3D printing: Optimization of cold metal transfer Wire Arc Additive Manufacturing using advanced predictive models

The potential of additive manufacturing (AM) of metallic materials, especially Wire Arc Additive Manufacturing (WAAM), to produce complex geometries at low cost and high efficiency is promising. This study optimizes WAAM process parameters for depositing copper on duplex stainless steel (DSS) substrates using the Cold Metal Transfer (CMT) technique, which offers improved thermal management and weld stability. Despite copper’s superior thermal and electrical properties, its high thermal conductivity and reflectivity introduce challenges in WAAM, such as poor energy absorption, surface defects, and structural inconsistencies. This work addresses these limitations by developing and validating empirical models for surface roughness and heat input using Response Surface Methodology and ANOVA. The optimized process achieved a surface roughness of 49.6 µm and a heat input of 182.8 J/mm, demonstrating enhanced fabrication quality and contributing to the industrial applicability of copper-based additive manufacturing. This study uniquely demonstrates the optimization of copper deposition using the CMT-WAAM process, a combination that has been rarely investigated due to copper’s high thermal conductivity and reflectivity. The integration of Response Surface Methodology and ANOVA for predictive modeling under these complex thermal conditions represents a novel contribution toward high-efficiency, defect-minimized copper additive manufacturing. Unlike previous WAAM studies that focused primarily on aluminum or steel alloys, this work investigates the underexplored copper–DSS combination, addressing the complex thermal–metallurgical behavior unique to high-conductivity metals using a validated RSM–ANOVA optimization framework.