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Dominik Kißkalt
Dominik Kißkalt
Institute for Factory Automation and Production Systems (FAPS), Friedrich-Alexander University Erlangen-Nuremberg (FAU)
Verified email at faps.fau.de
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Cited by
Cited by
Year
Machine learning in production–potentials, challenges and exemplary applications
A Mayr, D Kißkalt, M Meiners, B Lutz, F Schäfer, R Seidel, A Selmaier, ...
Procedia CIRP 86, 49-54, 2019
802019
Evaluation of machine learning for quality monitoring of laser welding using the example of the contacting of hairpin windings
A Mayr, B Lutz, M Weigelt, T Gläßel, D Kißkalt, M Masuch, A Riedel, ...
2018 8th International Electric Drives Production Conference (EDPC), 1-7, 2018
562018
Evaluation of deep learning for semantic image segmentation in tool condition monitoring
B Lutz, D Kisskalt, D Regulin, R Reisch, A Schiffler, J Franke
2019 18th IEEE international conference on machine learning and applications …, 2019
272019
Distributed condition monitoring systems in electric drives manufacturing
H Fleischmann, S Spreng, J Kohl, D Kißkalt, J Franke
2016 6th international electric drives production conference (EDPC), 52-57, 2016
232016
Streamlining the development of data-driven industrial applications by automated machine learning
D Kißkalt, A Mayr, B Lutz, A Rögele, J Franke
Procedia CIRP 93, 401-406, 2020
182020
A novel approach for data-driven process and condition monitoring systems on the example of mill-turn centers
D Kißkalt, H Fleischmann, S Kreitlein, M Knott, J Franke
Production Engineering 12, 525-533, 2018
182018
Towards an intelligent linear winding process through sensor integration and machine learning techniques
A Mayr, D Kißkalt, A Lomakin, K Graichen, J Franke
Procedia CIRP 96, 80-85, 2021
142021
Towards a data-driven process monitoring for machining operations using the example of electric drive production
D Kißkalt, A Mayr, J von Lindenfels, J Franke
2018 8th International electric drives production conference (EDPC), 1-6, 2018
142018
Multi-agent reinforcement learning for the energy optimization of cyber-physical production systems
J Bakakeu, S Baer, HH Klos, J Peschke, M Brossog, J Franke
Artificial Intelligence in Industry 4.0: A Collection of Innovative Research …, 2021
132021
Towards a smart electronics production using machine learning techniques
R Seidel, A Mayr, F Schäfer, D Kißkalt, J Franke
2019 42nd international spring seminar on electronics technology (isse), 1-6, 2019
132019
In-situ identification of material batches using machine learning for machining operations
B Lutz, D Kisskalt, A Mayr, D Regulin, M Pantano, J Franke
Journal of Intelligent Manufacturing 32, 1485-1495, 2021
122021
Benchmark of automated machine learning with state-of-the-art image segmentation algorithms for tool condition monitoring
B Lutz, R Reisch, D Kisskalt, B Avci, D Regulin, A Knoll, J Franke
Procedia Manufacturing 51, 215-221, 2020
112020
Towards “design for interoperability” in the context of systems engineering
M Sjarov, D Kißkalt, T Lechler, A Selmaier, J Franke
Procedia CIRP 96, 145-150, 2021
102021
Machine learning in electric motor production-potentials, challenges and exemplary applications
A Mayr, J Seefried, M Ziegler, M Masuch, A Mahr, J Lindenfels, M Meiners, ...
2019 9th international electric drives production conference (EDPC), 1-10, 2019
92019
Artificial Intelligence-Based Assistance System for Visual Inspection of X-ray Scatter Grids
A Selmaier, D Kunz, D Kisskalt, M Benaziz, J Fürst, J Franke
Sensors 22 (3), 811, 2022
42022
Automated domain adaptation in tool condition monitoring using generative adversarial networks
B Lutz, D Kisskalt, D Regulin, B Aybar, J Franke
2021 IEEE 17th International Conference on Automation Science and …, 2021
42021
Ai-based approach for predicting the machinability under consideration of material batch deviations in turning processes
B Lutz, D Kisskalt, D Regulin, J Franke
Procedia CIRP 93, 1382-1387, 2020
42020
Material Identification for Smart Manufacturing Systems: A Review
B Lutz, D Kisskalt, D Regulin, T Hauser, J Franke
2021 4th IEEE International Conference on Industrial Cyber-Physical Systems …, 2021
32021
Elektromotorenproduktion 4.0
A Mayr, B Lutz, M Weigelt, T Gläßel, J Seefried, D Kißkalt, J Franke
Zeitschrift für wirtschaftlichen Fabrikbetrieb 114 (3), 145-149, 2019
32019
Interactive image segmentation using superpixels and deep metric learning for tool condition monitoring
B Lutz, L Janisch, D Kisskalt, D Regulin, J Franke
Procedia CIRP 118, 459-464, 2023
22023
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