11 Publikationen
2024 | Dissertation | FH-PUB-ID: 4392 | 
F. Grumbach, Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse mit Techniken des maschinellen Lernens [kumulative Dissertation]. Bernburg: Universitäts- und Landesbibliothek Sachsen-Anhalt, 2024.
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2024 | Konferenzbeitrag | FH-PUB-ID: 5467
A. Müller, F. Grumbach, and M. Sabatelli, “Smaller Batches, Bigger Gains? Investigating the Impact of Batch Sizes on Reinforcement Learning Based Real-World Production Scheduling,” in 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), Padova, Italy , 2024, pp. 01–08.
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2024 | Artikel | FH-PUB-ID: 5470 |
D. Fischer, H. M. Hüsener, F. Grumbach, L. Vollenkemper, A. Müller, and P. Reusch, “Demystifying Reinforcement Learning in Production Scheduling via Explainable AI,” arXiv, 2024.
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2024 | Artikel | FH-PUB-ID: 5472 |
L. Döring, F. Grumbach, and P. Reusch, “Optimizing Sales Forecasts through Automated Integration of Market Indicators,” arXiv, 2024.
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2024 | Konferenzbeitrag | FH-PUB-ID: 4567
F. Grumbach, A. Müller, and L. Vollenkemper, “Robust Human-Centered Assembly Line Scheduling with Reinforcement Learning,” in Dynamics in Logistics. Proceedings of the 9th International Conference LDIC 2024, Bremen, Germany, Bremen , 2024, pp. 223–234.
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2024 | Artikel | FH-PUB-ID: 4283 |
A. Müller, F. Grumbach, and F. Kattenstroth, “Reinforcement Learning for Two-Stage Permutation Flow Shop Scheduling—A Real-World Application in Household Appliance Production,” IEEE Access, vol. 12, pp. 11388–11399, 2024.
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2023 | Konferenzbeitrag | FH-PUB-ID: 4394 |
A. Müller and F. Grumbach, “Predicting processing times in high mix low volume job shops,” in 16th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management, Magdeburg, 2023.
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2023 | Artikel | FH-PUB-ID: 3766 |
F. Grumbach, N. E. A. Badr, P. Reusch, and S. Trojahn, “A Memetic Algorithm With Reinforcement Learning for Sociotechnical Production Scheduling,” IEEE Access, vol. 11, pp. 68760–68775, 2023.
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2023 | Artikel | FH-PUB-ID: 2849 |
L. Vollenkemper, F. Grumbach, M. Kohlhase, and P. Reusch, “Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops,” wt Werkstattstechnik online, vol. 113, no. 04, pp. 158–163, 2023.
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2023 | Artikel | FH-PUB-ID: 2848 |
F. Grumbach, A. Müller, P. Reusch, and S. Trojahn, “Robustness Prediction in Dynamic Production Processes—A New Surrogate Measure Based on Regression Machine Learning,” Processes, vol. 11, no. 4, 2023.
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2022 | Artikel | FH-PUB-ID: 2295 |
F. Grumbach, A. Müller, P. Reusch, and S. Trojahn, “Robust-stable scheduling in dynamic flow shops based on deep reinforcement learning,” Journal of Intelligent Manufacturing, 2022.
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11 Publikationen
2024 | Dissertation | FH-PUB-ID: 4392 |
F. Grumbach, Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse mit Techniken des maschinellen Lernens [kumulative Dissertation]. Bernburg: Universitäts- und Landesbibliothek Sachsen-Anhalt, 2024.
HSBI-PUB
| Dateien verfügbar
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 5467
A. Müller, F. Grumbach, and M. Sabatelli, “Smaller Batches, Bigger Gains? Investigating the Impact of Batch Sizes on Reinforcement Learning Based Real-World Production Scheduling,” in 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), Padova, Italy , 2024, pp. 01–08.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 5470 |
D. Fischer, H. M. Hüsener, F. Grumbach, L. Vollenkemper, A. Müller, and P. Reusch, “Demystifying Reinforcement Learning in Production Scheduling via Explainable AI,” arXiv, 2024.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Artikel | FH-PUB-ID: 5472 |
L. Döring, F. Grumbach, and P. Reusch, “Optimizing Sales Forecasts through Automated Integration of Market Indicators,” arXiv, 2024.
HSBI-PUB
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 4567
F. Grumbach, A. Müller, and L. Vollenkemper, “Robust Human-Centered Assembly Line Scheduling with Reinforcement Learning,” in Dynamics in Logistics. Proceedings of the 9th International Conference LDIC 2024, Bremen, Germany, Bremen , 2024, pp. 223–234.
HSBI-PUB
| DOI
2024 | Artikel | FH-PUB-ID: 4283 |
A. Müller, F. Grumbach, and F. Kattenstroth, “Reinforcement Learning for Two-Stage Permutation Flow Shop Scheduling—A Real-World Application in Household Appliance Production,” IEEE Access, vol. 12, pp. 11388–11399, 2024.
HSBI-PUB
| Dateien verfügbar
| DOI
| Download (ext.)
2023 | Konferenzbeitrag | FH-PUB-ID: 4394 |
A. Müller and F. Grumbach, “Predicting processing times in high mix low volume job shops,” in 16th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management, Magdeburg, 2023.
HSBI-PUB
| DOI
| Download (ext.)
2023 | Artikel | FH-PUB-ID: 3766 |
F. Grumbach, N. E. A. Badr, P. Reusch, and S. Trojahn, “A Memetic Algorithm With Reinforcement Learning for Sociotechnical Production Scheduling,” IEEE Access, vol. 11, pp. 68760–68775, 2023.
HSBI-PUB
| Dateien verfügbar
| DOI
| Download (ext.)
2023 | Artikel | FH-PUB-ID: 2849 |
L. Vollenkemper, F. Grumbach, M. Kohlhase, and P. Reusch, “Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops,” wt Werkstattstechnik online, vol. 113, no. 04, pp. 158–163, 2023.
HSBI-PUB
| DOI
| Download (ext.)
2023 | Artikel | FH-PUB-ID: 2848 |
F. Grumbach, A. Müller, P. Reusch, and S. Trojahn, “Robustness Prediction in Dynamic Production Processes—A New Surrogate Measure Based on Regression Machine Learning,” Processes, vol. 11, no. 4, 2023.
HSBI-PUB
| DOI
| Download (ext.)
2022 | Artikel | FH-PUB-ID: 2295 |
F. Grumbach, A. Müller, P. Reusch, and S. Trojahn, “Robust-stable scheduling in dynamic flow shops based on deep reinforcement learning,” Journal of Intelligent Manufacturing, 2022.
HSBI-PUB
| DOI
| Download (ext.)