| Abstract Scope |
While the development and use of additive manufacturing (AM) technologies has advanced significantly in the past decade, barriers persist that limit the ability to qualify and certify AM components for use. This, in turn, limits the adoption of AM technologies by manufacturers at a time when supply chains require additional options. To address these challenges, AI tools have been developed and applied across the entire AM workflow to enable better understanding and control of the manufacture of AM components. The use of machine learning, AI, surrogate modeling and digital twins to accelerate the time for part design, material development, process optimization, and ultimately qualification and certification, will be discussed. |