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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, using the Physics of Failure, thorough understanding of the (dynamic) system behaviour and advanced monitoring techniques. 

Expertise

Composite Materials
Monitoring
Skin
Structural Health Monitoring
Abrasives
Corrosion
Corrosion
Strain Energy

Ancillary Activities

  • Semiotic Labs BV
    Adviseur
  • Consultinga
    Incidenteel verzorgen van advies en cursussen
  • Nederlandse Defensie Academie
    Hoogleraar Life Cycle Management

Publications

Recent
Rijsdijk, C., & Tinga, T. (2018). Enhanced Data Driven Decision Support. In C. Kulkarni, & T. Tinga (Eds.), Proceedings of the European Conference of the PHM Society (1 ed., Vol. 4). [409] Utrecht: PHM society.
ten Zeldam, S., de Jong, A., Loendersloot, R., & Tinga, T. (2018). Automated Failure Diagnosis in Aviation Maintenance Using eXplainable Artificial Intelligence (XAI). In C. Kulkarni, & T. Tinga (Eds.), Proceedings of the European Conference of the PHM Society (1 ed., Vol. 4). [432] Utrecht: PHM society.
Tiddens, W. W., Braaksma, A. J. J., & Tinga, T. (2018). Selecting Suitable Candidates for Predictive Maintenance. International Journal of Prognostics and Health Management, 9(1), [020].
Peeters, J. F. W., Basten, R. J. I., & Tinga, T. (2018). Improving failure analysis efficiency by combining FTA and FMEA in a recursive manner. Reliability engineering & system safety, 172, 36-44. DOI: 10.1016/j.ress.2017.11.024
Homborg, A. M., & Tinga, T. (2017). Corrosion monitoring: passive detection. Marine Maintenance Technology International, 2017(2), 34-38.
Leijenaar, T., & Tinga, T. (2017). Van data naar de juiste onderhoudsstrategie. Langs de IJssel, 2017, 4-5.
Tran, V. T., Thobiani, F. A., Tinga, T., Ball, A. D., & Niu, G. (2017). Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network. Proceedings of the Institution of Mechanical Engineers. Part C: Journal of mechanical engineering science. DOI: 10.1177/0954406217740929
Tinga, T., Tiddens, W. W., Amoiralis, F., & Politis, M. (2017). Predictive maintenance of maritime systems: models and challenges. In M. Cepin, & R. Bris (Eds.), Safety & Reliability - Theory and Applications: Proceedings of the 27th European Safety and Reliability Conference (ESREL 2017) (pp. 421-429). [55] Taylor & Francis. DOI: 10.1201/9781315210469-56
Cordova, L., Campos, M., & Tinga, T. (2017). Assessment of Moisture Content and Its Influence on Laser Beam Melting Feedstock. Paper presented at Euro PM2017 Congress & Exhibition, Milan, Italy.

UT Research Information System

Contact Details

Visiting Address

University of Twente
Faculty of Engineering Technology
Horst - Ring (building no. 21), room N 125
De Horst 2
7522LW  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Engineering Technology
Horst - Ring  N 125
P.O. Box 217
7500 AE Enschede
The Netherlands