Resources

Selected Publications by Center Faculty

“A Requirements Driven Digital Twin Framework: Specification and Opportunities,” J. Moyne, Y. Qamsane, E. C. Balta, I. Kovalenko, J. Faris, K. Barton, and D. M. Tilbury, IEEE Access, 8:107781–107801, June 2020.

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.

“A Methodology to Develop and Implement Digital Twin Solutions for Manufacturing Systems,” Y. Qamsane, J. Moyne, M. Toothman, I. Kovalenko, E. C. Balta, J. Faris, D. M. Tilbury, and K. Barton, IEEE Access, 9(44247 – 44265), March 2021 

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

“Digital-Twin based Cyber-Attack Detection Framework for Cyber-Physical Manufacturing Systems,” E. C. Balta, M. Pease, J. Moyne, K. Barton, and D. M. Tilbury, IEEE Transactions on Automation Science and Engineering,” to appear, 2023 

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