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 novel machine learning framework to transform lab-developed models into manufacturing plant-ready solutions for in-process quality prediction. The key objectives are to: 1) create a generic model to effectively learn similarities in massive unlabeled plant data through self-supervised contrastive learning, 2) build one-to-one mapping...
This three-year, $349,999 National Science Foundation project grant supports research at Case Western Reserve University to develop specific energy-based prognosis models for machining surface integrity through integration of process physics and machine learning. Funded under the NSF Directorate for Engineering's Engineering Grants program (CFDA 47.041), the research aims to foster innovation in engineering by improving prediction of machined surface conditions to enable more efficient...
The National Science Foundation (NSF) awarded a $350,000 Project Grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to Case Western Reserve University (CWRU) for the development of affordable and generalizable predictive maintenance (PM) solutions for small and medium manufacturers (SMMs). The key objectives of this 2-year project are to: (1) design a self-powered edge device integrating sensors, energy harvesting, and machine learning algorithms for real-time...
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) Project Grant award under CFDA 47.041 (Engineering) provides $679,973 to the University of Oklahoma to develop an artificial intelligence-assisted product design and production planning system. The key objectives are to: (i) accelerate product design through structured representation learning; (ii) implement a knowledge-augmented framework to dynamically cluster product families and refine scheduling strategies; and (iii) create a hybrid AI-assisted...
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...
This $398,786 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at North Carolina State University to develop a privacy-preserving collaborative condition monitoring and decision-making methodology for distributed manufacturing systems. The project aims to enable multiple geographically distributed manufacturing facilities to collectively utilize their data to construct more effective monitoring and decision-making models, while...
This Project Grant award from the National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation aims to develop data-driven methodologies for efficient monitoring and operation of multistage manufacturing systems. The $300,442 award to the University of Wisconsin System will establish an integrated mathematical framework to model the spatial interactions between machines and the temporal degradation of each machine in a multistage manufacturing process. The...
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 National Science Foundation (NSF) Engineering program (CFDA 47.041) award provides $100,000 to The Pennsylvania State University (Penn State) to establish rigorous foundational artificial intelligence and network science strategies for representing data, building search mechanisms, and facilitating collaboration among small and medium-sized manufacturing enterprises (SMEs). The award aims to help enhance the U.S. manufacturing base, promote national security and self-sufficiency, and create...