A novel approach for data-driven process and condition monitoring systems on the example of mill-turn centers. - Dominik Kißkalt; Hans Fleischmann; Sven Kreitlein; Manuel Knott 001; Jörg Franke (Prod. Eng., 2018)

Evaluation of Deep Learning for Semantic Image Segmentation in Tool Condition Monitoring. - Benjamin Lutz; Dominik Kißkalt; Daniel Regulin; Raven Reisch; Andreas Schiffler; Jörg Franke (ICMLA, 2019)

Multi-Agent Reinforcement Learning for the Energy Optimization of Cyber-Physical Production Systems. - Jupiter Bakakeu; Dominik Kißkalt; Jörg Franke; Shirin Baer; Hans-Henning Klos; Jörn Peschke (CCECE, 2020)

Automated Domain Adaptation in Tool Condition Monitoring using Generative Adversarial Networks. - Benjamin Lutz; Dominik Kißkalt; Daniel Regulin; Burak Aybar; Jörg Franke (CASE, 2021)

Semantic Segmentation of Multi-Channel Polycrystalline Structure Micrographs Using Convolutional Neural Networks. - Andreas Selmaier; Benjamin Lutz; Dominik Kißkalt; Simon Börnicke; Jens Fürst; Jörg Franke (ICMLA, 2021)

Material Identification for Smart Manufacturing Systems: A Review. - Benjamin Lutz; Dominik Kißkalt; Daniel Regulin; Tobias Hauser; Jörg Franke (ICPS, 2021)

In-situ identification of material batches using machine learning for machining operations. - Benjamin Lutz; Dominik Kißkalt; Andreas Mayr; Daniel Regulin; Matteo Pantano; Jörg Franke (J. Intell. Manuf., 2021)

Artificial Intelligence-Based Assistance System for Visual Inspection of X-ray Scatter Grids. - Andreas Selmaier; David Kunz; Dominik Kißkalt; Mohamed Benaziz; Jens Fürst; Jörg Franke (Sensors, 2022)