Additive manufacturing (AM) is revolutionizing the fabrication of metallic components, offering significant potential to compete with or complement traditional casting, forging, and machining processes, and enabling the production of complex functional components. Recent advancements in AM technology have facilitated the processing of shape memory alloys (SMAs) with functional properties comparable to those of conventionally processed alloys. However, the AM of NiTi SMAs remains underexplored due to the extreme complexity of the process, high melting point, and reactivity with oxygen. This study investigates the impact of AM processing on the shape memory properties of NiTi alloys using the Micro Wire and Arc Directed Energy Deposition (μ-WA-DED) technique in short circuit mode with a pioneering 0.3 mm pre-alloyed wire, focusing on increasing precision and control in the deposition process. The macroscopic morphology, microstructure, phase composition, phase-transformation temperatures, and mechanical properties of each deposited layer were analyzed. Results indicated austenite (B2) as the predominant phase, with retained martensite (B19′) and a reversible martensitic transformation (B2 ⇌ B19′) in the second layer. Mechanical characterization revealed variations in hardness (H) and elastic modulus (E) due to microstructural heterogeneity and composition. The first layer exhibited H = 3.8 GPa and E = 70 GPa, associated with the B2-NiTi phase, while higher values were obtained in the second layer, i.e., E = 100 GPa and H = 7 GPa. This study establishes for the first time the feasibility of NiTi alloy deposition with a 0.3 mm wire, setting a new standard for future research and applications in AM using μ-WA-DED.

This paper introduces DED-IM¹, a novel image-based mapping and tool-path planning method for Wire Arc Directed Energy Deposition (WA-DED). The method automatically segments 3D models into distinct regions such as thin walls, contours, bottlenecks, and large internal areas by processing binary images. These segments enable precise, geometry-tailored toolpath generation, significantly improving control over material deposition and reducing arc interruptions. Key innovations include the application of medial axis transforms to accurately map thin walls, the introduction of oscillatory paths for bottleneck areas, and an adaptive weaving pattern that minimizes voids while enhancing geometric precision. The method also integrates user-defined parameters, offering flexibility in region mapping and filling strategies to address specific manufacturing requirements. Experimental results demonstrate the efficacy of DED-IM, showing substantial reductions in common defects such as voids, insufficient material filling, and arc interruptions. This project, provides a flexible and scalable foundation baseline for automated WA-DED processes, enabling the integration of diverse path-planning techniques, fostering innovation and customization in tool-path generation for different manufacturing requirements.