Dr L.C.E. (Leo) Huberts
- Roetersstraat 11
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Postbus 15867
1001 NJ Amsterdam
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My defense - April 22, 2021
Statistical and Predictive Process Monitoring. How to Monitor Complex Processes in the Age of Big Data?
In this thesis, we investigate the possibilities of the increase in the size and frequency of data for both statistical and predictive process monitoring. This includes adjusting statistical process monitoring techniques based on large samples using the Central Limit Theorem and updating parameter estimates to increase the flexibility for high-frequency data. Furthermore, combining the increase in data with advances in modeling techniques paves the way for predictive monitoring. Signaling as early as possible can be imperative in taking preventive measures in sectors such as healthcare, education, manufacturing, maintenance, and more. It can be vital to ensure the quality of products and services.
Promotor: Prof. dr. R.J.M.M. Does (UvA)
Co-promotor: Dr. M. Schoonhoven (UvA)Practical information
Defense date: April 22, 2021 (start: 13:00)
Updated information can be found at the promotiekalender (find the link below).
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Publications
2025
- von Stackelberg, P. B., Goedhart, R., Huberts, L. C. E., Lokkerbol, J., & Birbil, S. I. (2025). Prediction of Depression Relapse Using Machine Learning With Administrative Data: Balancing Complexity and Simplicity. Quality and Reliability Engineering International. Advance online publication. https://doi.org/10.1002/qre.70139
von Stackelberg, P., Huberts, L. C. E., Goedhart, R., & Does, R. J. M. M. (2025). Multilevel model versus recurrent neural network: A case study to predict student success or failure revisited. Journal of Quality Technology, 57(2), 161-180. https://doi.org/10.1080/00224065.2024.2435870 [details]
2022
- Huberts, L. C. E., Does, R. J. M. M., Ravesteijn, B., & Lokkerbol, J. (2022). Predictive monitoring using machine learning algorithms and a real-life example on schizophrenia. Quality and Reliability Engineering International, 38(3), 1302-1317. https://doi.org/10.1002/qre.2957 [details]
- Huberts, L. C. E., Goedhart, R., & Does, R. J. M. M. (2022). Improved control chart performance using cautious parameter learning. Computers & Industrial Engineering, 169, Article 108185. https://doi.org/10.1016/j.cie.2022.108185 [details]
- Huberts, L. C. E., Schoonhoven, M., & Does, R. J. M. M. (2022). Monitoring student progress: A case study to predict student success or failure. Journal of Quality Technology, 54(2), 127-143. https://doi.org/10.1080/00224065.2020.1828008 [details]
2019
- Huberts, L. C. E., Schoonhoven, M., & Does, R. J. M. M. (2019). The effect of continuously updating control chart limits on control chart performance. Quality and Reliability Engineering International, 35(4), 1117-1128. https://doi.org/10.1002/qre.2448 [details]
2018
- Bun, M. J. G., & Huberts, L. C. E. (2018). The Impact of Higher Fixed Pay and Lower Bonuses on Productivity. Journal of Labor Research, 39(1), 1-21. https://doi.org/10.1007/s12122-017-9260-9 [details]
- Huberts, L. C. E., Schoonhoven, M., Goedhart, R., Diko, M. D., & Does, R. J. M. M. (2018). The performance of X̄ control charts for large non-normally distributed datasets. Quality and Reliability Engineering International, 34(6), 979-996. https://doi.org/10.1002/qre.2287 [details]
2020
- Huberts, L. C. E., Schoonhoven, M., & Does, R. J. M. M. (2020). Corrigendum to: The effect of continuously updating control chart limits on control chart performance (Quality and Reliability Engineering International, (2019), 35, 4, (1117-1128), 10.1002/qre.2448). Quality and Reliability Engineering International, 36(6), 2202. https://doi.org/10.1002/qre.2741
This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list. -
Ancillary activities
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Zelfstandige
Ik werk als zelfstandige aan meerdere projecten.
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Zelfstandige
von Stackelberg, P., Huberts, L. C. E., Goedhart, R., & Does, R. J. M. M. (2025). Multilevel model versus recurrent neural network: A case study to predict student success or failure revisited. Journal of Quality Technology, 57(2), 161-180.