University of Toronto researchers introduce machine learning framework to optimize metal 3D printing
Researchers at the University of Toronto have unveiled a machine learning-based framework designed to accelerate and refine the optimization of laser-based metal additive manufacturing. Named AIDED (Accurate Inverse process optimization framework in laser Directed Energy Deposition), the system allows users to predict and inversely determine optimal printing parameters for Laser Directed Energy Deposition (L-DED) processes, […]
Researchers at the University of Toronto have unveiled a machine learning-based framework designed to accelerate and refine the optimization of laser-based metal additive manufacturing. Named AIDED (Accurate Inverse process optimization framework in laser Directed Energy Deposition), the system allows users to predict and inversely determine optimal printing parameters for Laser Directed Energy Deposition (L-DED) processes, […]
