The National Science Foundation (NSF) awarded a $300,001 Project Grant under the Engineering program (CFDA 47.041) to the University of Southern California (USC) Department of Contracts and Grants Division. This 3-year collaborative research project, titled "PROCESS-INFORMED LATENT SPACE REPRESENTATION, LEARNING, AND MONITORING FOR SMART PERSONALIZED MANUFACTURING," aims to develop methodologies for reducing complexity in data representation, learning, and quality control for personalized manufacturing of high-variety, low-volume products. The project will establish a new latent space monitoring approach based on process-informed dimension reduction of the shape space for geometric quality control in smart personalized manufacturing, with a focus on metal-based wire-arc and polymer-based additive manufacturing processes. The research outcomes are expected to enable the adoption of cost-effective personalized manufacturing technologies through improved product quality and simplified supply chains. No subawards are planned for this grant.
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