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dr.ir. A.A. Meghoe (Annemieke)

Assistant Professor

About Me

Dr.ir. A.A. Meghoe (Annemieke) is an assistant professor at the University of Twente in the Netherlands

Her background is in mechanical engineering; she has pursued her bachelor's degree at the Anton de Kom University of Suriname (AdeKUS). After that, she continued with her master's and PhD in mechanical engineering at the University of Twente.

Her research topic is focused on predictive maintenance of the rail infrastructure, which is an indisputable subject when it comes to the most sustainable transport system for both people and goods, as it aims to reduce unexpected delays and disruptions during operation.

She proposes reduced models based on first principles and big data to predict the failure or lifetime of rail components using co-existing failure mechanisms and by acquiring field data such as data from the trains, data from the track and environmental data. Hence, the holistic solution she is looking for is a combination of models and a variety of data sources – all of which need to be developed and tuned to each other. This fundamental issue does not only apply to the railway sector; therefore, she also studies this approach in other application fields.

On the bachelor's level, she teaches Dynamics, and on the master's level, the course Failure Mechanism and Life Prediction, which complements her research line perfectly as the first step is to understand the wheel-rail dynamics and how the failure mechanisms work before understanding how they interact with each other and how they propagate further in the system to be able to make a statement on predictive maintenance. She also supervises bachelor's, master's, PDEng and PhD students who focus on prognostics, failure mechanisms and predictive maintenance. 

Expertise

Engineering & Materials Science
Centrifugal Pumps
Defects
Predictive Maintenance
Rails
Wear Of Materials
Business & Economics
Metamodel
Prediction
Rail

Publications

Recent
Meghoe, A. A. , Loendersloot, R. , & Tinga, T. (2023). Selection of a suitable wear model for implementation in a generic rail damage function. 1-16. Paper presented at Railway Engineering 2023, Edinburgh, United Kingdom.
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.
Silveira, N. N. A. , Loendersloot, R. , Meghoe, A. A. , & Tinga, T. (2021). Data Selection Criteria for the Application of Predictive Maintenance to Centrifugal Pumps. In Proceedings of the 6th European Conference of the Prognostics and Health Management Societ (pp. 372-380). (Archives of the PHM Society European Conference; Vol. 6, No. 1). PHM Society. https://doi.org/10.36001/phme.2021.v6i1.2839
Meghoe, A. A., Jamshidi, A. , Loendersloot, R. , & Tinga, T. (2021). A hybrid predictive methodology for head checks in railway infrastructure. Proceedings of the Institution of Mechanical Engineers. Part F: Journal of rail and rapid transit, 235(10), 1312-1322. https://doi.org/10.1177/0954409721993611
Meghoe, A. A. (2019). Physical Model-Based Predictive Maintenance for Rail Infrastructure. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036548786
Meghoe, A., Jamshidi, A. , Loendersloot, R. , & Tinga, T. (2019). Towards the development of a hybrid methodology of head checks in railway infrastructure. In Railway Engineering 2019: 15th International Conference & Exhibition (pp. 1-12). UKRRIN.

UT Research Information System

Contact Details

Visiting Address

University of Twente
Faculty of Engineering Technology
Horst Complex (building no. 20), room N126
De Horst 2
7522LW  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Engineering Technology
Horst Complex  N126
P.O. Box 217
7500 AE Enschede
The Netherlands

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