| On the reliability of machine learning applications in manufacturing environments N Jourdan, S Sen, EJ Husom, E Garcia-Ceja, T Biegel, J Metternich arXiv preprint arXiv:2112.06986, 2021 | 11 | 2021 |
| A computer vision system for saw blade condition monitoring N Jourdan, T Biegel, V Knauthe, M von Buelow, S Guthe, J Metternich Procedia CIRP 104, 1107-1112, 2021 | 10 | 2021 |
| Machine learning for intelligent maintenance and quality control: A review of existing datasets and corresponding use cases N Jourdan, L Longard, T Biegel, J Metternich ESSN: 2701-6277, 2021 | 9 | 2021 |
| Deep learning for multivariate statistical in-process control in discrete manufacturing: A case study in a sheet metal forming process T Biegel, N Jourdan, C Hernandez, A Cviko, J Metternich Procedia CIRP 107, 422-427, 2022 | 7 | 2022 |
| Künstliche Intelligenz zur Umsetzung von Industrie 4.0 im Mittelstand: Expertise des Forschungsbeirats der Plattform Industrie 4.0 J Metternich, T Biegel, BB Cassoli, F Hoffmann, N Jourdan, J Rosemeyer, ... acatech-Deutsche Akademie der Technikwissenschaften, 2021 | 6 | 2021 |
| Combining process monitoring with text mining for anomaly detection in discrete manufacturing T Biegel, N Jourdan, T Madreiter, L Kohl, S Fahle, F Ansari, ... Proceedings of the 12th Conference on Learning Factories (CLF 2022), 2022 | 5 | 2022 |
| An AI Management Model for the Manufacturing Industry-AIMM T Biegel, B Bretones Cassoli, F Hoffmann, N Jourdan, J Metternich | 5 | 2021 |
| Data driven production–application fields, solutions and benefits E Sarikaya, B Brockhaus, A Fertig, H Ranzau, P Stanula, J Walther | 3 | 2021 |
| Künstliche Intelligenz zur Umsetzung von Industrie 4.0 im Mittelstand: Leitfaden zur Expertise des Forschungsbeirats der Plattform Industrie 4.0 J Metternich, T Biegel, BB Cassoli, F Hoffmann, N Jourdan, J Rosemeyer, ... acatech-Deutsche Akademie der Technikwissenschaften, 2021 | 2 | 2021 |
| SSMSPC: self-supervised multivariate statistical in-process control in discrete manufacturing processes T Biegel, P Helm, N Jourdan, J Metternich Journal of Intelligent Manufacturing, 1-28, 2023 | 1 | 2023 |
| Toward the Sustainable Development of Machine Learning Applications in Industry 4.0 S Ellenrieder, N Jourdan, T Biegel, BB Cassoli, J Metternich, P Buxmann | 1 | 2023 |
| Handling concept drift in deep learning applications for process monitoring N Jourdan, T Bayer, T Biegel, J Metternich Procedia CIRP 120, 33-38, 2023 | | 2023 |
| A self-supervised learning approach for multivariate statistical in-process control in discrete manufacturing processes T Biegel Technische Universität Darmstadt, 2023 | | 2023 |
