Membership Agreement
Operations Manual - for approval
Bylaws - for approval
(note: Bylaws will be approved by the Members once the Center is operational)
Center Workshop Resources (July 23, 2025)
(note: slides for each session are included as links)
A set of requirements for a Digital Twin (DT) framework has been derived from analysis of DT definitions, DTs in use today, expected DT applications in the near future, and longer-term DT trends and the DT vision in Smart Manufacturing. These requirements include elements of re-usability, interoperability, interchangeability, maintainability, extensibility, and autonomy across the entire DT lifecycle. Case studies using and extending the baseline framework illustrate its advantages in supporting DT solutions and trends in SM.
This paper introduces a Digital Twin (DT) solution development methodology as a generic procedure for analyzing and developing DTs for manufacturing systems. A case study illustrates the advantages of the proposed methodology in supporting manufacturing DT solutions.
“An Adaptive, State-Based Framework for Fault Prediction in Rotating Equipment,” M. Toothman, B. Braun, S. J. Bury, J. Moyne, D. M. Tilbury, K. Barton, in Proceedings of the IEEE Conference on Automation Science and Engineering, Auckland, NZ, August 2023
Joint work with Dow
“A Digital Twin Framework for Mechanical System Health State Estimation,” M. Toothman, B. Braun, S. J. Bury, M. Dessauer, K. Henderson, S. Phillips, Y. Yixin, D. M. Tilbury, J. Moyne, K. Barton, Modeling, Estimation, and Control Conference (MECC), Austin, TX, October 2021
Joint work with Dow
Joint work with NIST
“Full Stack Virtual Commissioning: Requirements Framework to Bridge Gaps in Current Virtual Commissioning Process,” J. B. Sim, K. N. Shah, M. Saez, J. Abell, Y. Zhou, J. Faris, D. M. Tilbury, and K. Barton, in Proceedings of the Manufacturing Science and Engineering Conference, Rutgers, New Jersey, June 2023
Joint work with General Motors
“An Integrated Framework for Dynamic Manufacturing Planning to Obtain New Line Configurations,” L. Poudel, I. Kovalenko, R. Geng, M. Takaharu, Y. Nonaka, N. Takahiro, U. Shota, D. M. Tilbury, and K. Barton, in Proceedings of the IEEE Conference on Automation Science and Engineering, Mexico City, August 2022
Joint work with Hitachi
“A Digital Twin Framework for Performance Monitoring and Anomaly Detection in Fused Deposition Modeling,” E. Balta, D. Tilbury, and K. Barton, Proceedings of the IEEE Conference on Automation Science and Engineering (CASE), Vancouver, August 2019.
“Real-time manufacturing machine and system performance monitoring using Internet of Things,” Miguel Saez, Francisco Maturana, Kira Barton, and Dawn Tilbury, IEEE Transactions on Automation Science and Engineering, 15(4):1735–1748, October 2018
Joint work with Rockwell Automation
“Digital Twin Framework for Reconfiguration Management: Concept & Evaluation,” B. Caesar, K. Barton, D. M. Tilbury, A. Fay, in IEEE Access, vol. 11, pp. 127364-127387, 2023
Keynote conference presentation (31 slides)
Report (draft) on AI and DT (8 pages)
May 2022 Workshop Report (4 pages)
October 2024 Advanced Process Control - Smart Mfg presentation (33 slides)
Artificial Intelligence to Advance High-Mix Production: A Roadmap for the Semiconductor Industry (141 pages)