Tag: UVA
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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Building resilience as manufacturing requirements become more complex
The industrial machinery and heavy equipment manufacturing sector is critical not only for its direct outputs, machines, and equipment that pave the way for construction, agriculture and manufacturing but also for its crucial role in economic development and innovation.
