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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From cost exposure to cost control: Using energy flexibility to protect margins
Electricity price volatility is reshaping the cost base of Australian manufacturing, challenging long-held assumptions that energy can be treated as a stable operational input.
