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 |
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KIT Scientific Publishing
2023
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Series: | Reihe Informationsmanagement im Engineering Karlsruhe
25 |
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Online Access: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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490 | 1 | |a Reihe Informationsmanagement im Engineering Karlsruhe |v 25 | |
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
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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