Project Grant 2517645
- This federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $185,000.00 to the Regents of the University of Michigan, doing business as University of Michigan-Dearborn, to conduct collaborative research on improving zero-shot learning of manufacturing anomalies. The goal is to develop an intelligent system that leverages existing engineering knowledge embedded in texts and images to detect new and unforeseen anomalies in advanced...
- 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 $887,740 Project Grant award from the National Science Foundation's Integrative Activities program (CFDA 47.083) supports the development of a real-time monitoring and structural validation system for continuous fiber printing, an advanced additive manufacturing technique. The key products and services to be delivered include: Modeling techniques to determine how defects affect the structural performance of printed parts Deep learning models to process multi-modal sensor data (e.g.,...
- The National Science Foundation (NSF) awarded a $679,973 Project Grant under the Engineering program (CFDA 47.041) to the University of Oklahoma to develop an artificial intelligence-assisted product design and production planning system that improves efficiencies in manufacturing. The research focuses on integrating deep learning into product functional analysis, component design integration, and constraint-aware production planning to help small manufacturers leverage intelligent automation...
- 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 $300,001 Project Grant awarded by the National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation under the NSF Directorate for Engineering (CFDA 47.041) supports research at Virginia Polytechnic Institute & State University (Virginia Tech) to define, evaluate, and improve data quality for effective artificial intelligence (AI) deployment in manufacturing. The key products and services to be delivered under this 3-year award include: Developing...
- This federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $281,589 to the University of Florida to conduct research on aligning artificial intelligence (AI) models with real-world operational goals in predictive maintenance for manufacturing systems. The research project aims to design machine learning models that explicitly incorporate maintenance cost and operational constraints into predictive modeling, enabling more effective and...
- This $400,000 federal Project Grant award from the National Science Foundation's (NSF) Division of Civil, Mechanical, and Manufacturing Innovation (CMMI) program (CFDA 47.041, Engineering) aims to revolutionize the design and manufacturing of advanced nanocomposite materials using artificial intelligence (AI). The research focus is on understanding and controlling amorphous-crystalline interfaces within these materials, which can enhance their strength, durability, and reliability. The award...
- 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 Project Grant award of $500,000 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) is focused on establishing a coherent knowledge representation and reasoning framework to enable concurrent optimization in hybrid remanufacturing systems. The key objectives are to: Create new cognitive encoders to unify multi-modal data from remanufacturing workflows into knowledge graphs, integrating them as retrievable memory. Advance knowledge fusion through cognitive operations...
This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $315,000 to Florida State University (FSU) to develop an intelligent system that leverages existing engineering knowledge embedded in texts and images to detect manufacturing anomalies in zero-shot settings. The goal is to create a scalable and automated approach that combines technical documents with machine learning to identify unexpected deviations from normal manufacturing process behavior, which can lead to defective products or production disruptions. The key products and services to be delivered through this 3-year award include:
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $315.0k | 8/26/25 |