Abstract: Argonne National Laboratory is well known as a center of fundamental materials expertise and exceptional user facilities. A complementary expertise is that of materials manufacturing, where researchers aim to bring new materials capabilities to the market. The Materials Engineering Research Facility at Argonne is a locus of that effort and houses diverse manufacturing capabilities. Many of these processes are highly instrumented, resulting in a wealth of information that is currently underutilized. There is an opportunity to leverage this near-real-time feedback to accelerate process optimization and result in better material outcomes. This seminar presents suitable artificial intelligence techniques to tackle this problem and demonstrates their application to two Argonne manufacturing capabilities: atomic layer deposition and flame spray pyrolysis.