Prototyping machine-learning-supported lead time prediction using AutoML J Bender, J Ovtcharova Procedia Computer Science 180, 649-655, 2021 | 31 | 2021 |
Benchmarking AutoML-supported lead time prediction J Bender, M Trat, J Ovtcharova Procedia Computer Science 200, 482-494, 2022 | 26 | 2022 |
Towards a B2B integration framework for smart services in Industry 4.0 V Schubert, S Kuehner, T Krauss, M Trat, J Bender Procedia Computer Science 217, 1649-1659, 2023 | 14 | 2023 |
A comparison of agent-based coordination architecture variants for automotive product change management J Bender, S Kehl, JP Müller Multiagent System Technologies: 13th German Conference, MATES 2015, Cottbus …, 2015 | 9 | 2015 |
Energy-flexible job-shop scheduling using deep reinforcement learning M Felder, D Steiner, P Busch, M Trat, C Sun, J Bender, J Ovtcharova ESSN: 2701-6277, 353-362, 2023 | 8 | 2023 |
Artificial-intelligence-enabled dynamic demand response system for maximizing the use of renewable electricity in production processes H Wicaksono, M Trat, A Bashyal, T Boroukhian, M Felder, M Ahrens, ... The International Journal of Advanced Manufacturing Technology, 1-25, 2024 | 5 | 2024 |
Unsupervised Anomaly Detection and Root Cause Analysis for an Industrial Press Machine based on Skip-Connected Autoencoder C Sun, M Trat, J Bender, J Ovtcharova, G Jeppesen, J Bär 2022 21st IEEE International Conference on Machine Learning and Applications …, 2022 | 2 | 2022 |
Towards dynamic Visualization of Digital Twins in Engineering M Jaenicke, J Bender, J Ovtcharova Procedia Computer Science 253, 297-306, 2025 | | 2025 |
AutoML-Supported Lead Time Prediction Enabling Smart Job Scheduling in Make-To-Order Production J Bender | | 2024 |
Sensitivity-Based Optimization of Unsupervised Drift Detection for Categorical Data Streams M Trat, J Bender, J Ovtcharova Karlsruher Institut für Technologie (KIT), 2022 | | 2022 |
Forschungsprojekt: A Comparison of Agent-Based Coordination Architecture Variants for Automotive Product Change Management J Bender | | |