Tag: Kamel Fezzaa
Argonne researchers develop AI approach to detect flaws of 3D-printed parts
A research team led by the US Department of Energy’s (DOE) Argonne National Laboratory and the University of Virginia (UVA) has developed various imaging and machine-learning techniques to detect and predict the formation of pores in 3D-printed metals in real time with near-perfect accuracy.
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Manufacturers should do this sooner rather than later, says precision engineer
Australian precision engineering and industrial instrumentation company CENMAC implemented ERP software when it was still a one-man operation. “I couldn’t imagine us growing to this size without MRPeasy,” says Jason Ford, Founder.
