| Learning quality characteristics for plastic injection molding processes using a combination of simulated and measured data F Finkeldey, J Volke, JC Zarges, HP Heim, P Wiederkehr Journal of Manufacturing Processes 60, 134–143, 2020 | 43 | 2020 |
| Stability prediction in milling processes using a simulation-based Machine Learning approach A Saadallah, F Finkeldey, K Morik, P Wiederkehr Procedia CIRP 72, 1493–1498, 2018 | 38 | 2018 |
| Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data F Finkeldey, A Saadallah, P Wiederkehr, K Morik Engineering Applications of Artificial Intelligence 94, 103753, 2020 | 33 | 2020 |
| Simulation and sensor data fusion for machine learning application A Saadallah, F Finkeldey, J Buß, K Morik, P Wiederkehr, W Rhode Advanced Engineering Informatics 52, 101600, 2022 | 16 | 2022 |
| Augmented semantic segmentation for the digitization of grinding tools based on deep learning P Wiederkehr, F Finkeldey, T Merhofe CIRP Annals 70 (1), 297–300, 2021 | 12 | 2021 |
| Simulation of surface structuring considering the acceleration behaviour by means of spindle control D Freiburg, F Finkeldey, M Hensel, P Wiederkehr, D Biermann International Journal of Mechatronics and Manufacturing Systems 11 (1), 67–86, 2018 | 9 | 2018 |
| Learning-Based Prediction of Pose-Dependent Dynamics F Finkeldey, A Wirtz, T Merhofe, P Wiederkehr Journal of Manufacturing and Materials Processing 4 (3), 85, 2020 | 8 | 2020 |
| Tool wear-dependent process analysis by means of a statistical online monitoring system F Finkeldey, S Hess, P Wiederkehr Production Engineering 11 (6), 677–686, 2017 | 8 | 2017 |
| Elaborated analysis of force model parameters in milling simulations with respect to tool state variations S Hess, F Finkeldey, P Wiederkehr Procedia CIRP 55, 83–88, 2016 | 5 | 2016 |
| Learning Ensembles in the Presence of Imbalanced Classes A Saadallah, N Piatkowski, F Finkeldey, P Wiederkehr, K Morik 8th International Conference on Pattern Recognition Applications and Methods, 2019 | 3 | 2019 |
| Reduction of experimental efforts for predicting milling stability affected by concept drift using transfer learning on multiple machine tools P Wiederkehr, F Finkeldey, T Siebrecht CIRP Annals 73 (1), 301–304, 2024 | | 2024 |
| Simulation and Machine Learning. P Wiederkehr, K Morik, A Saadallah, F Finkeldey Mach. Learn. under Resour. Constraints Vol. 3 (3), 157–179, 2022 | | 2022 |
| Quicker Evaluation of the Optimum Operating Point J Volke, F Finkeldey, JC Zarges, P Wiederkehr, HP Heim Kunststoffe international 3, 24–27, 2021 | | 2021 |
| Detection of unstable milling processes using wavelets F Finkeldey Technical report for Collaborative Research Center SFB 876 Providing …, 2020 | | 2020 |
| Synchronization of measured and simulated force signals of milling processes F Finkeldey Technical report for Collaborative Research Center SFB 876 Providing …, 2019 | | 2019 |
Petra Wiederkehr (née Kersting)TU Dortmund and Lamarr InstituteVerified email at tu-dortmund.de
