The National Science Foundation (NSF) Engineering program (CFDA 47.041) awarded a $300,001 Project Grant to the University of Southern California (USC) for the project "COLLABORATIVE RESEARCH: PROCESS-INFORMED LATENT SPACE REPRESENTATION, LEARNING, AND MONITORING FOR SMART PERSONALIZED MANUFACTURING." This 3-year award, effective June 1, 2024, will develop novel methodologies to enable process monitoring and geometric quality control for personalized manufacturing of one-of-a-kind...
This National Science Foundation Project Grant of $728,684 supports research at The Pennsylvania State University to develop new machine learning and mathematical methods for quality control in manufacturing. Funded under the Engineering program (CFDA 47.041), the award runs from June 1, 2022 to May 31, 2025. Specifically, the university will first create improved algorithms for identifying a subset of key process variables in continuous manufacturing that best indicate overall plant control,...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $496,138 supports research to uncover relationships between optimal laser scan sequences, temperature distribution, distortion, and residual stress in laser powder bed fusion (LPBF) additive manufacturing. The project aims to mathematically, numerically, and experimentally investigate advanced thermal and thermomechanical modeling approaches to determine optimal scan sequences that can reduce...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research at The Pennsylvania State University (Penn State) to develop "Intelligent Products for Mass Individualization in Manufacturing Systems." The $688,574 award, effective August 1, 2025 through July 31, 2030, focuses on integrating "intelligent products" into the manufacturing process to enable more customized and individualized production. The project aims...
This $1.02 million National Science Foundation Project Grant, funded under the Engineering program (CFDA 47.041), supports the development of computation-informed deep learning approaches to enable real-time prognosis of melt pool dynamics for additive manufacturing. Over the three-year period from July 2022 to June 2025, the awardee, Rutgers University, will create an integrated model using computational fluid dynamics simulations and deep learning to predict melt pool overheating during...
The $148,060 Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation under the Engineering program (CFDA 47.041) will fund research at Carnegie Mellon University investigating machine learning approaches to support engineering designers in digital manufacturing. The university will mine part designs from open online repositories and curated datasets developed through in-class challenges. A machine learning pipeline will extract design...
The National Science Foundation awarded North Carolina State University a two-year $400,000 Project Grant under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to develop process monitoring methods for improving product quality in electron beam powder bed fusion additive manufacturing. The university will research an in-situ quality control framework using real-time sensing data to monitor product quality during manufacturing and adaptively adjust process...
The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Engineering program (CFDA 47.041) to the University of Pittsburgh to support collaborative research on optimizing scan sequences for laser powder bed fusion (LPBF) additive manufacturing. The objective is to mathematically, numerically, and experimentally determine the relationships between optimal scan sequences, temperature distribution, distortion, and residual stress in LPBF to enable 3D printing of complex...
This $219,900 federal Project Grant, awarded by the National Science Foundation (NSF) under the Integrative Activities program (CFDA 47.083), will acquire an advanced metal additive manufacturing (AM) system to support interdisciplinary research, education, and industrial advancement. The acquired equipment will enhance the structural performance of AM parts, develop sustainable energy solutions, and improve engineering education through hands-on experiences with advanced technologies. The...
This National Science Foundation (NSF) Project Grant award, under the Engineering program (CFDA 47.041), provides $650,000 in funding to Carnegie Mellon University (CMU) from June 1, 2024 to May 31, 2027. The project aims to fully understand the mechanisms controlling shape distortion in additive manufacturing (AM) processes, particularly during the sintering of nano/microparticles. The research involves integrated experimental and theoretical work to identify critical AM process parameters that...