prof.dr.ir. T. Tinga (Tiedo)

Full Professor Dynamics based Maintenance

About Me

Tiedo Tinga (1973) is a professor in Dynamics based Maintenance at the faculty of Engineering Technology, with a background in Materials Science and Mechanical Engineering. His research focuses on the detection and prediction of failures in systems, with the aim of developing smart maintenance concepts, like Predictive Maintenance. The is achieved by combining the Physics of Failure, thorough understanding of the (dynamic) system behaviour and advanced (condition) monitoring techniques, as well as data science and artificial intelligence. 


Engineering & Materials Science
Fatigue Damage
Predictive Maintenance
Structural Health Monitoring
Physics & Astronomy

Ancillary Activities

  • Consultinga
    Incidenteel verzorgen van advies en cursussen
  • Nederlandse Defensie Academie
    Professor Life Cycle Management
  • NLR (Netherlands Aerospace Center)
    Adviescommissie Aerospace Vehicles NLR


Ribeiro Marinho, N. , Loendersloot, R. , Tinga, T., Grooteman, F., & Wiegman, J. W. (2023). A Comparison of Optical Sensing Systems with Piezo-Electric Sensors for Impact Identification of Composite Plates. In S. Farhangdoust, A. Guemes, & F-K. Chang (Eds.), Proceedings of the 14th International Workshop on Structural Health Monitoring 2023: Designing SHM for Sustainability, Maintainability, and Reliability (pp. 1127-1133). DEStech Publications, Inc.
Tinga, T., Homborg, A. M. , & Rijsdijk, C. (2023). Data-driven maintenance of military systems: Potential and challenges. In P. B. M. J. Pijpers, M. Voskuijl, & R. Beeres (Eds.), Towards a data-driven military: A multidisciplinary perspective (pp. 73-96). Leiden University Press. https://doi.org/10.24415/9789087284084
Jimenez-Roa, L. A., Heskes, T. , Tinga, T. , & Stoelinga, M. I. A. (2023). Automatic inference of fault tree models via multi-objective evolutionary algorithms. IEEE transactions on dependable and secure computing, 20(4), 3317-3327. Advance online publication. https://doi.org/10.1109/TDSC.2022.3203805
Meghoe, A. A. , Loendersloot, R. , & Tinga, T. (2022). Uncertainty propagation in rail wear prediction using an analytical method and field observations. Paper presented at Fifth international conference on railway technology, Montpellier, France.
Ribeiro Marinho, N. R. M. , Loendersloot, R. , Tinga, T., & Grooteman, F. (2022). Impact identification method for composite structures: A structured approach for a full-scale aircraft component. Poster session presented at 25th Engineering Mechanics Symposium, EM 2022, Arnhem, Netherlands.

UT Research Information System

Contact Details

Visiting Address

University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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Mailing Address

University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands