Project Grant 2618913
- The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded the University of Florida $249,999 on September 1, 2026, to develop self-learning digital twins for robotic remanufacturing under uncertainty, under the NSF Engineering program (CFDA 47.041). The award funds research to establish scientific foundations for digital twins that model, predict, and adjust to uncertain manufacturing conditions in real time. The project develops a computational...
- The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded The Regents of the University of California at Riverside $249,957 on September 1, 2026, under the Engineering program (CFDA 47.041) to develop computational frameworks for self-learning digital twins in robotic remanufacturing. The research establishes scientific foundations for digital twins that model, predict, and adjust to uncertain manufacturing conditions in real time. The work addresses...
- This $199,066 Project Grant, awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041), supports research to automate the creation of digital twins for manufacturing systems using computer vision and deep learning. The key products and services to be delivered include: Developing a novel framework for fully automated digital twin generation through innovations in computer vision, deep learning, and data labeling. This will significantly reduce the manual effort...
- This four-year Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation provides $399,585 to the University of Florida for collaborative research titled "A Causal AI Digital Twin Framework to Transform Intensive Care Delivery." The award's stated purpose is to support investigator-initiated research and education under the Computer and Information Science and Engineering program (CFDA 47.070). Specifically, the University of...
- The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded The University of Central Florida Board of Trustees $304,307 on February 1, 2026, to develop a digital twin modeling framework for quantifying and reducing greenhouse gas emissions from vertical infrastructure operations. The recipient will create a high-fidelity three-dimensional digital twin augmented by live sensor data and real-time predictive models to design and operate buildings with...
- The National Science Foundation Division of Engineering Education and Centers awarded $452,933 to the University of Texas at El Paso on October 1, 2026, to establish a Research Experiences for Undergraduates (REU) Site focused on intelligent manufacturing, artificial intelligence, and digital twin technologies. The program immerses ten undergraduate students annually in ten weeks of faculty-mentored research integrating additive manufacturing, AI-driven design and process monitoring, and digital...
- The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded Florida State University $299,999 on January 1, 2027, under the Engineering program (CFDA 47.041) to develop knowledge-guided methods for correcting predictive manufacturing models trained on corrupted or mislabeled data. The project will integrate hierarchical knowledge graphs, semantic consistency analysis, and localized model correction to remove invalid learned relationships from manufacturing...
- This $256,000 National Science Foundation Engineering Directorate Project Grant supports the development of a digital twin composition method by Diamond Age Technology LLC. The awardee will develop techniques to efficiently combine disparate data sources describing industrial process facilities into a single digital representation with sub-centimeter accuracy. This digital twin can then be projected into spatial computing environments like virtual and augmented reality. The goal is to encode...
- The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded the University of North Florida $200,000 on July 1, 2026, under the Engineering Research Initiation program to develop a vision-simulation-driven in-situ quality-control system for laser powder bed fusion manufacturing. The project addresses defect-driven scrap and rework in metal additive manufacturing by creating a within-layer detect-predict-decide-act loop that couples real-time perception,...
- The National Science Foundation Division of Undergraduate Education awarded Drexel University $399,869 on October 1, 2026, under the STEM Education program (CFDA 47.076) to develop and implement curriculum pathways and laboratory experiences integrating artificial intelligence, digital twins, robotics, and simulation-driven manufacturing technologies into undergraduate engineering technology education. The project develops instructional modules, laboratory activities, and project-based...
The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded Florida International University $250,000 on September 1, 2026, to develop computational frameworks for self-learning digital twins in robotic remanufacturing under uncertainty. The project, funded under the Engineering assistance listing (CFDA 47.041), runs through August 31, 2029, and is performed in Miami, Florida. The research establishes scientific foundations for digital twins that model, predict, and adjust to uncertain manufacturing conditions in real time. The work pursues three interconnected objectives: development of a hybrid modeling framework combining physics-based models and data-driven surrogate models through Bayesian multi-fidelity fusion to balance computational cost and predictive accuracy; establishment of a hierarchical reinforcement learning framework linking strategic planning and operational decision-making; and integration of these capabilities to support autonomous robotic remanufacturing systems. The project addresses current digital twin limitations—extensive computational demands and difficulty adjusting to changing operating conditions—that restrict deployment in advanced manufacturing environments requiring flexibility and rapid decision-making. The research strengthens U.S. manufacturing competitiveness and sustainability by enabling practical recovery and reuse of products and materials, reducing waste, and supporting circular economy principles. The project includes interdisciplinary education and workforce development in artificial intelligence, robotics, manufacturing, and data science through student research experiences and outreach activities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 7/29/26 |