25–26 May 2023
Europe/Berlin timezone

Digital Twins and Engineering for Performance

26 May 2023, 08:00
Building 101A, Meeting Room 1 (Copenhagen)

Building 101A, Meeting Room 1


DTU Lyngby campus Anker Engelunds Vej 1 2800 Kgs. Lyngby


Prof. Ron Kenett (KPA Ltd.)


Advancements in technology and data access are followed by significant changes in the scope of engineering work. In Industry 4.0, sensor technologies enable improved monitoring, diagnostic, prognostic and prescriptive analytic capabilities. Systems and processes are now paired with digital twins, a digital asset that parallels the physical assets. This evolution triggers a shift from engineering of design to engineering for performance integrating mathematical models driven by physics, with statistical and analytic data driven models. The talk will review the background of digital twins and sketch future pathways emphasizing engineering for performance, in contrast to engineering of design. A case study from the Israeli railway system will be presented.

• Chinesta F., Cueto, E. Abisset-Chavanne, E., Duval, J.and el Khaldi, F. (2020) Virtual, Digital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data, Archives of Computational Methods in Engineering, 27()1, pp. 105–134.
• Dattner, I., Bortman, J., Kenett, R.S. and Chinesta, F. (2021) Learning Dynamical Systems: Optimal Integration of Mathematical Models with Machine Learning and Artificial Intelligence, https://mmldt.eng.ucsd.edu/
• Kenett, R.S., Zonnenshain, A. and Fortuna, G. (2018) A road map for applied data sciences supporting sustainability in advanced manufacturing: The information quality dimensions, Procedia Manufacturing, 21, pp. 141–148.
• Kenett, R.S. and Zacks, S. (2021) Modern Industrial Statistics: With Applications in R, MINITAB, and JMP, 3rd Edition, John Wiley and Sons.
• Kenett, R.S. and Bortman, J. (2022) The digital twin in Industry 4.0: a wide-angle perspective, Quality and Reliability Engineering, 38(3), pp. 1357-1366.
• Kenett, R.S., Zacks, S. and Gedeck, P. (2022) Modern Statistics: A Computer-Based Approach with Python, SITE series, Springer/
• Kenett, R.S., Zacks, S. and Gedeck, P. (2023) Industrial Statistics: A Computer-Based Approach with Python, SITE series, Springer.

Primary author

Prof. Ron Kenett (KPA Ltd.)

Presentation materials