CMU Announces Machine Vision System for Classifying Metal Powders for 3D Printing Usage

Published by , June 9, 2017 2:11 pm

(3DPrintingIndustry)  Carnegie Mellon University’s (CMU) College of Engineering researchers have developed an autonomous system for classifying the metal powders used for 3D printing. Using machine vision technology, the system can identify specific microstructures in the additive manufacturing metal powders with an accuracy of greater than 95%.
Elizabeth Holm, professor of materials science and engineering at CMU explains,”Importantly, the machine vision approach is autonomous, objective, and repeatable. This type of standardization is necessary to advance quality assurance in the field.”

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