This $493,637 federal Project Grant award, funded by the National Science Foundation (NSF) Engineering program (CFDA 47.041), aims to advance simulation-based manufacturing process digital twin (DT) technologies. The key research goals are to: 1) develop a self-organizing DT framework that continuously validates and calibrates the simulator, 2) create optimal control algorithms for contingency scenarios, and 3) leverage parallel computing for rapid optimization. The research will establish...
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...
This $499,889 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research to develop a real-time digital twin of dynamic construction sites using multi-robot systems equipped with 5G radios and advanced perception capabilities. The key objectives are to (a) enhance worker safety by identifying potential hazards and (b) improve construction efficiency by monitoring and optimizing resource utilization. The research will leverage techniques...
This National Science Foundation (NSF) Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) provides $269,979 in funding to the Santa Fe Institute of Science to conduct collaborative research on improving the generalization capabilities of digital twins - advanced computer models that emulate complex systems like human health, aircraft, and weather patterns. The overarching goal is to develop novel hybrid digital twin architectures that can better predict system...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal grant award provides $174,980 to the Rochester Institute of Technology (RIT) to develop techniques and a framework for enabling "live 3D digital twins" - real-time digital representations of 3D physical objects. The project aims to create adaptive digital twin pipelines that can maintain low latency and high accuracy across varying network and compute resources, with applications...
This National Science Foundation (NSF) Integrative Activities (CFDA 47.083) Project Grant award of $259,969 aims to develop immersive training environments that enhance skill acquisition, knowledge transfer, and workplace safety in smart manufacturing. Specifically, the project will integrate mixed reality (MR) and digital twin (DT) technologies to transform traditional training methods and provide workers with practical, self-guided modules to acquire essential skills for Industry 4.0. The...
This National Science Foundation Project Grant of $283,099 will support the development of new stochastic optimization methods to calibrate digital twins using large datasets. Awarded under the Engineering program (CFDA 47.041), the grant will fund research at the University of Michigan from January 2023 through December 2025. Specifically, the university researchers will develop computational approaches using statistical theories to guide simulation experiments and identify optimal subsets of...
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...
The National Science Foundation (NSF) Directorate for Engineering's "Engineering" program (CFDA 47.041) awarded a $735,872 Project Grant to the University of Pittsburgh to develop a novel digital twin modeling framework for evaluating and minimizing greenhouse gas emissions associated with vertical infrastructure operations. The grant will support research to create high-fidelity 3D digital representations of buildings augmented with real-time sensor data, enabling the analysis of...
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 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research to automate the creation of digital twins (DTs) for manufacturing systems using computer vision and deep learning. The $199,066 award to Miami University aims to develop a novel framework for fully automated DT generation by: 1) creating a dataset of manufacturing shop floor videos with annotated observational elements, 2) developing a neural radiance field (NeRF) model to reconstruct the 3D shop environment, and 3) implementing a 3D convolutional neural network to automatically identify and classify observational elements within the NeRF-generated space. The project also plans to integrate unmanned aerial vehicles (UAVs) with confidence-aware pathing algorithms to optimize video capture and enhance DT fidelity. This research intends to significantly advance the scalability, accuracy, and interoperability of manufacturing DTs while providing students with hands-on experience in AI-driven manufacturing research. The award period is from July 1, 2025 to June 30, 2027.