A team of researchers from Argonne National Laboratory and Texas A&M University have developed an innovative new approach to defect detection in 3D printed parts. Using real-time temperature data, together with machine learning algorithms, the scientists were able to make correlative links between thermal history and the formation of subsurface defects during the laser powder […]
from 3D Printing Industry https://bit.ly/2DPCjZd