A virtual twin framework for robotic CMT-WAAM of SS317L steel: Unveiling process-structure-property correlations

This study presents a virtual-twin framework for robotic CMT-WAAM of SS317L stainless steel, aimed at improving process reliability and mechanical performance. The work introduces a novel combination of process-parameter optimization, digital fabrication planning, and microstructural-mechanical characterization. Optimal hatch-spacing and inter-layer dwell time were identified to minimize surface waviness. These parameters were implemented through a virtual-twin-based offline program to fabricate industry-relevant WAAM components. Post-deposition microstructural analysis showed heterogeneous microstructures, strong grain texture, elemental segregation, and high GND density, which together led to anisotropic tensile behaviour in as-built components. Controlled heat treatments altered the as-built microstructure, with low-temperature annealing partially relieving stresses, while high-temperature annealing induced recrystallization and homogenization, thereby substantially increasing ductility with minimal trade-off in strength. These results align with strengthening predictions and validate the proposed strengthening model. Overall, the framework enables the manufacturing of SS317L WAAM components with wrought-like properties, demonstrating the potential of CMT-WAAM for high-performance stainless-steel applications. • Virtual twin architecture enabled integrated process planning and manufacturing control for robotic CMT-WAAM systems. • Optimized CMT-WAAM parameters achieved low waviness, ±2 mm accuracy, while complex curvature requires machining allowances. • As-built SS317L showed heterogeneous microstructures, strong texture, and elemental segregation, causing anisotropic high-strength, low-ductility behavior. • 1050°C heat treatment recrystallized and homogenized microstructures, reduced anisotropy, enhanced ductility, meeting industry mechanical standards.