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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

  • Physics

    • Rail
    • Model
    • Wear
    • Maintenance
  • Computer Science

    • Models
    • Application
    • Prediction Model
  • Engineering

    • Prediction

Organisations

Publications

2024

Quantifying the suitability and feasibility of predictive maintenance approaches (2024)Computers & industrial engineering, 194. Article 110342. Alves da Silveira, N. N., Meghoe, A. A. & Tinga, T.https://doi.org/10.1016/j.cie.2024.110342

2023

Integration of multiple failure mechanisms in a life assessment method for centrifugal pump impellers (2023)Advances in mechanical engineering, 15(6). Alves da Silveira, N. N., Meghoe, A. A. & Tinga, T.https://doi.org/10.1177/16878132231175755Selection of a suitable wear model for implementation in a generic rail damage function (2023)[Contribution to conference › Paper] Railway Engineering 2023. Meghoe, A. A., Loendersloot, R. & Tinga, T.Validation of a physics-based prognostic model with incomplete data: a rail wear case study (2023)International Journal of Prognostics and Health Management, 14(1), 1-16. Article 3283. Meghoe, A. A., Loendersloot, R. & Tinga, T.https://doi.org/10.36001/ijphm.2023.v14i1.3283

2022

Uncertainty propagation in rail wear prediction using an analytical method and field observations (2022)[Contribution to conference › Paper] Fifth international conference on railway technology. Meghoe, A. A., Loendersloot, R. & Tinga, T.

2021

A hybrid predictive methodology for head checks in railway infrastructure (2021)Proceedings of the Institution of Mechanical Engineers. Part F: Journal of rail and rapid transit, 235(10), 1312-1322. Meghoe, A. A., Jamshidi, A., Loendersloot, R. & Tinga, T.https://doi.org/10.1177/0954409721993611Data Selection Criteria for the Application of Predictive Maintenance to Centrifugal Pumps (2021)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). PHM Society. Silveira, N. N. A., Loendersloot, R., Meghoe, A. A. & Tinga, T.https://doi.org/10.36001/phme.2021.v6i1.2839

2020

Rail wear and remaining life prediction using meta-models (2020)International Journal of Rail Transportation, 8(1), 1-26. Meghoe, A., Loendersloot, R. & Tinga, T.https://doi.org/10.1080/23248378.2019.1621780

Research profiles

Address

University of Twente

Horst Complex (building no. 20), room N126
De Horst 2
7522 LW Enschede
Netherlands

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