This image shows André Jaquemod

André Jaquemod

M. Sc.

Akademischer Mitarbeiter
Institut für Werkzeugmaschinen
Prozessüberwachung und -regelung

Contact

+49 711 685 84194
 +49 711 685 70040

Holzgartenstr. 17
70174 Stuttgart
Deutschland
Room: U1.109

Publikationen:

  1. 2025

    1. Jaquemod, A., Reuter, M., Palalic, M., & Möhring, H.-C. (2025). AI-Supported Process Monitoring in Machining / In-Process Quality Assurance of Inhomogeneous Materials Using Feature- Based Machine Learning Methods. In ZWF - Zeitschrift für Wirtschaftlichen Fabrikbetrieb: Vol. KI in Engineering und Produktion (pp. 263–268). Walter de Gruyter. https://doi.org/10.1515/zwf.2024-0136

  2. 2024

    1. Derbas, M., Jaquemod, A., Frömel-Frybort, S., Güzel, K., Moehring, H.-C., & Riegler, M. (2024). A Machine Learning Approach to Predict Properties of Wood Products during Milling. Forest Products Journal, 74, Article 2. https://doi.org/10.13073/fpj-d-24-00012
    2. Dünn, C., Kneifel, J., Roj, R., Jaquemod, A., Güzel, K., Pelshenke, C., Theiß, R., Möhring, H.-C., & Dültgen, P. (2024). AI-based Real-Time Analysis of Sawing Processes for the Identification of Materials. In G. G. zur Förderung angewandter Informatik e.V. (Ed.), AI4EA - Berlin Workshop on Artificial Intelligence for Engineering Applications. https://www.gfai.de/fileadmin/Downloads/Tagungsband/gfai-tagungsband-2024.pdf
    3. Palalić, M., Jaquemod, A., Güzel, K., & Möhring, H.-C. (2024). In-Process Monitoring of Inhomogeneous Material Characteristics Based on Machine Learning for Future Application in Additive Manufacturing. Journal of Machine Engineering. https://doi.org/10.36897/jme/187872

  3. 2023

    1. Jaquemod, A. (2023). Minimalmengenschmierung: Ein neuer Ansatz zur Produktivitätssteigerung in der Holzbearbeitung.
    2. Riegler, M., Derbas, M., Jaquemod, A., Frömel-Frybort, S., Güzel, K., & Möhring, H.-C. (2023). Machine Learning for Predicting Wood Properties during Milling.
    3. Jaquemod, A., Güzel, K., & Möhring, H.-C. (2023). The influence of high cutting speeds on cutting forces, surface roughness and tool wearin the milling process of wood.
    4. Derbas, M., Jaquemod, A., Frömel-Frybort, S., Güzel, K., Möhring, H.-C., & Riegler, M. (2023). Multisensor data fusion and machine learning to classify wood products and predict workpiece characteristics during milling. CIRP Journal of Manufacturing Science and Technology, 47, 103–115. https://doi.org/10.1016/j.cirpj.2023.09.003
    5. Jaquemod, A., Güzel, K., & Möhring, H.-C. (2023). Influence of Minimum Quantity Lubrication on Tool Temperature and Wear in Wood Machining. https://doi.org/10.1007/978-3-031-47394-4

  4. 2022

    1. Güzel, K., Jaquemod, A., Stehle, T., & Möhring, H.-C. (2022). Influence of minimum quantity lubrication on surface quality during circular sawing of wood (No. 1/2). 112, Article 1/2. https://doi.org/doi.org/10.37544/1436-4980-2022-01-02
    2. Jaquemod, A., Güzel, K., & Möhring, H.-C. (2022). Investigation of the Effect of Minimum Quantity Lubrication on the Machining of Wood. In LectureNotes in Production Engineering. German Academic Association for Production Technology (WGP).
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