From the Mines Newsroom: Mines faculty teaching robots how to think, share information. Many manufacturing processes today rely on 3D-printed methods and machine learning to produce high-quality products at a faster rate. This requires machines that can evolve and improve over time through learned experience. But getting machines to share knowledge is easier said than done. Xiaoli Zhang, associate professor of mechanical engineering explains when 3D printing a part or product, most of the quality control, such as determining the hardness of the printed material, is completed after the part has been completely manufactured. But Zhang is developing process-structure-property (PSP) machine learning-based models to identify defects in real time to avoid failures and save time and money.