| Competences |
- Machine tools: concepts, technologies, autonomy
- Industry 4.0 and 5.0: digitalization, connectivity, IoT, smart factory
- Data-driven and hybrid modeling approaches
- Alternative materials in mechanical engineering (e.g., mineral casting)
- Human–machine interaction
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| Publications |
- Maier, M., Zwicker, R., Akbari, M., Rupenyan, A., & Wegener, K. (2019). Bayesian optimization for autonomous process set-up in turning. CIRP Journal of Manufacturing Science and Technology, 26, 81-87. https://doi.org/10.1016/j.cirpj.2019.04.005
- Maier, M., Rupenyan, A., Bobst, C., & Wegener, K. (2020). Self-optimizing grinding machines using Gaussian process models and constrained Bayesian optimization. The International Journal of Advanced Manufacturing Technology, 108(1), 539-552. https://doi.org/10.1007/s00170-020-05369-9
- Maier, M., Kunstmann, H., Zwicker, R., Rupenyan, A., Wegener, K., (2022). Autonomous and data-efficient optimization of turning processes using expert knowledge and transfer learning. Journal of Materials Processing Technology, 303, 117540. https://doi.org/10.1016/j.jmatprotec.2022.117540
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