Carnegie Mellon engineers sort metal 3D printing powders with 95% accuracy using new machine vision tech

Researchers from Carnegie Mellon University's College of Engineering have developed machine vision technology that can autonomously identify and sort different kinds of metal 3D printing powders with an accuracy of more than 95 percent. The technology could be commonplace within five years. Those in the business of manufacturing know that all metal parts, 3D printed or otherwise, need to undergo rigorous testing to ensure their quality and usability.

from 3ders.org - http://www.3ders.org