Project Grant 2452666
Award Date
5/1/25
Completion Date
4/30/28
Dollars Obligated
$680K
Federal Agency
Division of Civil, Mechanical, and Manufacturing Innovation
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Norman, OK 73019, USA
Similar Awards
The National Science Foundation (NSF) awarded a $300,000 Early-concept Grant for Exploratory Research (EAGER) under the Engineering program (CFDA 47.041) to The Pennsylvania State University, doing business as Penn State, to conduct research on expanding the use of artificial intelligence (AI) in manufacturing. The project focuses on developing deep clustering and generative modeling techniques to identify geometric similarities between new part designs and existing designs to improve...
This Project Grant award, funded by the National Science Foundation (NSF) Engineering program (CFDA 47.041), supports research to develop methodologies for monitoring and improving personalized manufacturing processes, particularly for one-of-a-kind parts produced using additive manufacturing. The award, totaling $129,624 and spanning from June 1, 2024, to May 31, 2027, will enable researchers at the University of Oklahoma to establish a novel latent space monitoring approach based on...
This $283,965 project grant award from the National Science Foundation's Engineering program (CFDA 47.041) to Case Western Reserve University aims to develop a machine learning framework to enable the deployment of artificial intelligence solutions in manufacturing plants. The key objectives are to: Create a generic model for characterizing massive unlabeled plant data to learn similarities, and Establish a model that can efficiently adapt to new manufacturing scenarios with limited tuning....
The National Science Foundation (NSF) awarded a $271,362 Project Grant to the University of Washington under the Engineering program (CFDA 47.041) with a performance period from January 1, 2024 to June 30, 2025. The grant will fund the development of efficient surrogate modeling methods to predict discontinuous design performance in complex engineering systems, such as smart factories and autonomous material handling systems. The research aims to facilitate the solution of challenging...
This National Science Foundation (NSF) Engineering program award supports research to develop an AI-powered smart database system called G-Forge for additive manufacturing. The $200,000 two-year project, awarded on February 1, 2024, will enable G-Forge to provide capabilities such as verifying, debugging, and indexing G-code files that drive 3D printers. The goal is to reduce errors and delays in the manufacturing process. The project will also integrate these capabilities into educational...
This Project Grant award of $281,589 from the National Science Foundation's Engineering program (CFDA 47.041) supports research to align artificial intelligence (AI) models with real-world operational goals in predictive maintenance for manufacturing systems. The research project at the University of Florida aims to: (i) design machine learning models that incorporate maintenance cost and operational constraints into predictive modeling; (ii) extend unit-level prognostics to fleet-level...
The University of Oklahoma will provide research services under a $406,062 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041). Specifically, the university will develop an artificial intelligence and data mining decision support tool to improve flexible reservoir system modeling enabled by subseasonal-to-seasonal hydroclimatological forecasts. Researchers will leverage deep learning models to correct spatial and temporal errors in precipitation forecasts...
The National Science Foundation (NSF) awarded a $183,420 Project Grant under the Engineering program (CFDA 47.041) to the University of Texas at Arlington (UTA) Office of Research Administration Division. The grant will fund a collaborative research project to develop an integrated materials-manufacturing-controls framework for enhancing the efficiency and resilience of manufacturing systems. Key objectives include: 1) quantifying the effects of raw ingredients on feedstock properties, 2)...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award, totaling $596,285, was provided to Arizona State University (ASU) to develop a systematic and generalizable methodology for integrating vision-language models and robotics to fully automate manufacturing assembly operations. The key products and services to be delivered include: Interpreting product manufacturing information and process instructions to derive high-level task sequences from various input...
This National Science Foundation (NSF) Engineering (CFDA 47.041) Project Grant award totaling $150,000 is funding a two-year exploratory research project (August 1, 2024 to July 31, 2026) led by the University of Iowa. The project aims to address fundamental challenges in translating on-ground manufacturing systems to reliable in-space production by developing a real-time heterogeneous transfer active learning framework. This framework will leverage knowledge from well-studied, data-rich...