This Project Grant award of $199,066.00 from the National Science Foundation's Engineering program (CFDA 47.041) supports research to automate the creation of digital twins for manufacturing systems. The key objectives are to: Develop a dataset of manufacturing shop floor videos annotated with ISO 23247-compliant labels of observable manufacturing elements (OMEs). Train a neural radiance field (NeRF) model to reconstruct the shop environment as a high-fidelity 3D model. Implement a 3D...
This Project Grant award of $200,000 from the National Science Foundation's Engineering program (CFDA 47.041) will support the establishment of the Industry-University Cooperative Research Center for Digital Twins in Manufacturing (IUCRC-DTM) at the University of Michigan. The center will conduct fundamental research to advance the development, deployment, maintenance, and evaluation of digital twins in manufacturing domains. Key focus areas include digital twin frameworks and standards, digital...
The National Science Foundation awarded a $100,000 Project Grant to Arizona State University (ASU) to establish the Industry-University Cooperative Research Center for Digital Twins in Manufacturing (IUCRC-DTM). This five-year grant, effective April 1, 2025, will support fundamental research to develop, deploy, maintain, update, and evaluate digital twin technology for manufacturing applications. The IUCRC-DTM will focus on three key thrust areas: (1) Digital Twin Frameworks and Standards, (2)...
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 $200,000 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will fund the development of advanced computational methods to create high-fidelity, fast-running digital twins of patient hearts and cardiovascular medical devices. The project aims to deliver: 1) novel machine learning algorithms for accurate digital twin geometry reconstruction from 3D medical images, 2) an efficient inverse method to identify in vivo...
This $444,562 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at Michigan State University to address the digital transformation of the facility management industry. The key objectives are to: Construct a digital twin ecosystem to enhance the role of facility managers through physical and cognitive assistance. Develop a multi-modal user interface to promote effective interaction within the digital ecosystem. Gauge facility...
This Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $269,979 to the Santa Fe Institute of Science to conduct collaborative research on developing robust digital twin models that can accurately predict the behavior of complex systems under unexpected conditions. The key objectives are to: Investigate the generalization abilities of digital twins by combining mathematical tools from nonlinear dynamics and machine...
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 of $499,715 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support the development of a digital twin (DT) for an intelligent electromagnetic (EM) sensor on a chip (IEM-SOC). The project aims to create a scalable DT architecture that can validate new designs and advance research and development in emerging memory technologies for edge sensor applications. Key objectives include producing a DT for real-time...
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 entire industrial process operations at the component level within 10% of current time and cost requirements. By combining physical scans with engineering documentation and relational probabilities, the awardee aims to establish the infrastructure necessary for widespread application of virtual and augmented reality in industrial workplaces in a manner that impacts worker health and safety, operational efficiencies, and environmental risk reduction.