Hofmann, Johannes ; Becker, Marco ; Kubik, Christian ; Groche, Peter (2024)
Machine learning based operator assistance in roll forming.
In: Production Engineering, Research and Development
doi: 10.1007/s11740-024-01311-0
Artikel, Bibliographie

Kubik, Christian (2024)
Zuverlässige maschinelle Lernmodelle zur Zustandsdiagnose von Fertigungsprozessen am Beispiel des Stanzens.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00027831
Dissertation, Erstveröffentlichung, Verlagsversion

Kubik, Christian ; Groche, Peter (2024)
Force-based inline detection of wear evolution during blanking of cold rolled steels.
In: Production Engineering, 18
doi: 10.1007/s11740-023-01238-y
Artikel, Bibliographie

Molitor, Dirk Alexander ; Arne, Viktor ; Kubik, Christian ; Noemark, Gabriel ; Groche, Peter (2024)
Inline closed-loop control of bending angles with machine learning supported springback compensation.
In: International Journal of Material Forming, 17
doi: 10.1007/s12289-023-01802-y
Artikel, Bibliographie

Schlegel, Clemens ; Molitor, Dirk Alexander ; Kubik, Christian ; Martin, Daniel M. ; Groche, Peter (2024)
Tool wear segmentation in blanking processes with fully convolutional networks based digital image processing.
In: Journal of Materials Processing Technology, 324
doi: 10.1016/j.jmatprotec.2023.118270
Artikel, Bibliographie

Kubik, Christian ; Molitor, Dirk Alexander ; Rojahn, Marvin ; Groche, Peter (2023)
Deep learning-based domain adaptation for a generalized detection of wear phenomena during blanking.
In: Manufacturing Letters, 35
doi: 10.1016/j.mfglet.2023.08.005
Artikel, Bibliographie

Kubik, Christian ; Molitor, Dirk Alexander ; Varchmin, Sven ; Leininger, Dominik Sebastian ; Ohrenberg, Joost ; Groche, Peter (2023)
Image-based feature extraction for inline quality assurance and wear classification in high-speed blanking processes.
In: International Journal of Advanced Manufacturing Technology
doi: 10.1007/s00170-023-12653-x
Artikel, Bibliographie

Martin, Daniel M. ; Kubik, Christian ; Krüger, Martin ; Groche, Peter
Hrsg.: Lukasz Madej, Mateusz Sitko ; Perzynski, Konrad (2023)
Influence of process parameters on mechanical properties of lamination stacks produced by interlocking.
26th International Conference on Material Forming (ESAFORM 2023). Kraków, Poland (19.04.2023-21.04.2023)
doi: 10.21741/9781644902479-121
Konferenzveröffentlichung, Bibliographie

Kubik, Christian ; Martin, Daniel M. ; Ebertz, Fabian ; Groche, Peter (2023)
Simulation-based data augmentation for an inline wear state detection during blanking.
14th International Conference on the Technology of Plasticity (ICTP 2023). Mandelieu-La Napoule, France (24.09.2023-29.09.2023)
doi: 10.1007/978-3-031-42093-1_3
Konferenzveröffentlichung, Bibliographie

Martin, Daniel M. ; Bäcker, Frederic ; Deusinger, Björn ; Kubik, Christian ; Gehringer, Philipp ; Schröder, Joana ; Groche, Peter (2022)
Design Guidelines for interlocked stator cores made of CoFe sheets.
In: IOP Conference Series: Materials Science and Engineering, 1238
doi: 10.1088/1757-899X/1238/1/012036
Artikel, Bibliographie

Kubik, Christian ; Becker, Marco (2022)
Machine-Learning-Modelle in der umformtechnischen Praxis.
In: VDW-Branchenreport
Artikel, Bibliographie

Liewald, Mathias ; Bergs, Thomas ; Groche, Peter ; Behrens, Bernd-Arno ; Briesenick, David ; Müller, Martina ; Niemietz, Philipp ; Kubik, Christian ; Müller, Felix (2022)
Perspectives on data-driven models and its potentials in metal forming and blanking technologies.
In: Production Engineering : Research and Development, 7 (5)
doi: 10.1007/s11740-022-01115-0
Artikel, Bibliographie

Schumann, Philipp ; Martin, Daniel M. ; Kubik, Christian ; Groche, Peter
Hrsg.: Inal, Levesque (2022)
Analysis and Evaluation of the Clamping Force on the Tool Surface during the Blanking Process.
doi: 10.1007/978-3-031-06212-4_60
Konferenzveröffentlichung, Bibliographie

Kubik, Christian ; Molitor, Dirk Alexander ; Becker, Marco ; Groche, Peter (2022)
Knowledge discovery from time series in engineering applications using machine learning techniques.
In: Journal of Manufacturing Science and Engineering, 144 (9)
doi: 10.1115/1.4054158
Artikel, Bibliographie

Kokozinski, Andre ; Kubik, Christian ; Groche, Peter (2022)
Komplexität mehrstufiger Umformprozesse beherrschen.
In: wt Werkstattstechnik online, 112 (10)
doi: 10.37544/1436-4980-2022-10-66
Artikel, Bibliographie

Molitor, Dirk Alexander ; Kubik, Christian ; Becker, Marco ; Hetfleisch, Ruben ; Lyu, F. ; Groche, Peter (2022)
Towards High Performance Deep Learning Models in Tool Wear Classification with Generative Adversarial Networks.
In: Journal of Materials Processing Technology, 302
doi: 10.1016/j.jmatprotec.2021.117484
Artikel, Bibliographie

Kubik, Christian ; Molitor, Dirk Alexander ; Rojahn, M. ; Groche, Peter (2022)
Towards a real-time tool state detection in sheet metal forming processes validated by wear classification during blanking.
In: IOP Conference Series: Materials Science and Engineering, 1238
doi: 10.1088/1757-899X/1238/1/012067
Artikel, Bibliographie

Kubik, Christian ; Becker, Marco ; Molitor, Dirk Alexander ; Groche, Peter (2022)
Towards a systematical approach for wear detection in sheet metal forming using machine learning.
In: Production Engineering - Research and Development
doi: 10.1007/s11740-022-01150-x
Artikel, Bibliographie

Molitor, Dirk Alexander ; Kubik, Christian ; Hetfleisch, Ruben ; Groche, Peter (2022)
Workpiece image-based tool wear classification in blanking processes using deep convolutional neural networks.
In: Production Engineering: Research and Development
doi: 10.1007/s11740-022-01113-2
Artikel, Bibliographie

Molitor, Dirk Alexander ; Kubik, Christian ; Knoll, Maximilian ; Becker, Marco ; Groche, Peter (2021)
Ableitung eines Vorgehensmodells zur systematischen Wissensgenerierung aus Sensordaten.
In: Zeitschrift für Wirtschaftlichen Fabrikbetrieb : ZWF, 116 (5)
doi: 10.1515/zwf-2021-0066
Artikel, Bibliographie

Kubik, Christian ; Knauer, Sebastian Michael ; Groche, Peter (2021)
Smart sheet metal forming : importance of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine for predicting wear states during blanking.
In: Journal of Intelligent Manufacturing, 23 (5)
doi: 10.1007/s10845-021-01789-w
Artikel, Bibliographie

Kubik, Christian ; Hohmann, Johannes ; Groche, Peter (2021)
Exploitation of force displacement curves in blanking—feature engineering beyond defect detection.
In: The International Journal of Advanced Manufacturing Technology, 113 (1-2)
doi: 10.1007/s00170-020-06450-z
Artikel, Bibliographie

Kubik, Christian ; Hohmann, Johannes ; Groche, Peter (2021)
Exploitation of force displacement curves in blanking – Feature Engineering beyond defect detection.
In: The International Journal of Advanced Manufacturing Technology, 113
doi: 10.1007/s00170-020-06450-z
Artikel, Bibliographie

Germann, Thiemo ; Martin, Daniel M. ; Kubik, Christian ; Groche, Peter
Hrsg.: Pelz, Peter F. ; Groche, Peter (2021)
Mastering Uncertain Operating Conditions in the Development of Complex Machine Elements by Validation Under Dynamic Superimposed Operating Conditions.
doi: 10.1007/978-3-030-77256-7
Konferenzveröffentlichung, Bibliographie

Kubik, Christian (2021)
Potenzial von Machine Learning in der umformtechnischen Produktion.
In: Technik und Mensch, 2
Artikel, Bibliographie

Molitor, Dirk Alexander ; Kubik, Christian ; Hetfleisch, Ruben ; Groche, Peter (2021)
Was Bauteile über den Verschleiß genutzter Stanzwerkzeuge verraten.
In: Zeitschrift für Wirtschaftlichen Fabrikbetrieb : ZWF, 116 (12)
doi: 10.1515/zwf-2021-0163
Artikel, Bibliographie

Kubik, Christian ; Kessler, Thomas ; Huttel, Dominic ; Groche, Peter (2020)
Profilbiegen – Industrie 4.0-Ansätze für die Qualitätskontrolle.
In: Mittelstand-Digital Magazin WISSENSCHAFT TRIFFT PRAXIS, 13
Artikel, Bibliographie

Hoppe, Florian ; Hohmann, Johannes ; Knoll, Maximilian ; Kubik, Christian ; Groche, Peter (2019)
Feature-based Supervision of Shear Cutting Processes on the Basis of Force Measurements: Evaluation of Feature Engineering and Feature Extraction.
In: Procedia Manufacturing, 34
doi: 10.1016/j.promfg.2019.06.164
Artikel, Bibliographie