• Learning based clustering of streamed process data for the efficient modelling and prediction of characteristics in milling processes based on the integration of domain knowledge – ClusterSim

Finkeldey, F.; Wöste, F.; Werner, D.; Schönecker, R.I.E.; Biermann, D.; Wiederkehr, P.
Cluster-based prediction of chatter vibrations in milling operations
20th CIRP Conference on Modeling of Machining Operations 133 (2025): 388–393
https://doi.org/10.1016/j.procir.2025.02.067

Schönecker, R.I.E.; Baumann, J.; Garcia Carballo, R.; Biermann, D.
Fundamental Investigation of the Application Behavior and Stabilization Potential of Milling Tools with Structured Flank Faces on the Minor Cutting Edges
Journal of Manufacturing and Material Processing 8 (2024) 2, S. 174, https://doi.org/10.3390/jmmp8040174

Finkeldey, F.; Wöste, F.; Werner, D.; Schönecker, R.I.E.; Biermann, D.; Wiederkehr, P.
Cluster-based prediction of chatter vibrations in milling operations
20th CIRP Conference on Modeling of Machining Operations, 22.-23.05.2025, Mons, Belgien

Finkeldey, F.; Schönecker, R.; Biermann, D.; Wiederkehr, P.
Clustering approach for improving model-based analyses of milling operations
18th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 10.-12.7.2024, Gulf of Naples, Italy

Schönecker, R.I.E.; Baumann, J.; Garcia Carballo, R.; Biermann, D.
Fundamental Investigation of the Application Behavior and Stabilization Potential of Milling Tools with Structured Flank Faces on the Minor Cutting Edges
20th International Conference on Machine Design and Production – UMTIK 2024, 14.–17.8.2024, Ankara, Turkey