Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung
This work aims to develop a method that can reschedule the matrix production in the case of a disruption. For this purpose, different artificial intelligence methods are combined in a novel way. The developed method is validated on a theoretical and a real scheduling case.
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| Format: | Electronic Book Chapter |
| Published: |
KIT Scientific Publishing
2023
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| Series: | Reihe Informationsmanagement im Engineering Karlsruhe
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| Subjects: | |
| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 245 | 1 | 0 | |a Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung |
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| 520 | |a This work aims to develop a method that can reschedule the matrix production in the case of a disruption. For this purpose, different artificial intelligence methods are combined in a novel way. The developed method is validated on a theoretical and a real scheduling case. | ||
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| 546 | |a German | ||
| 650 | 7 | |a Mechanical engineering & materials |2 bicssc | |
| 653 | |a Produktionssteuerung; Reinforcement Learning; Künstliche Intelligenz; Terminierung; Production control; artificial intelligence; scheduling | ||
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