Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung

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https://oapen-dev.siscern.org/bitstream/20.500.12657/62536/1/entwicklung-einer-methode-zum-einsatz-von-reinforcement-learning-fur-die-dynamische-fertigungsdurchlaufsteuerung.pdf
Author(s)
Lohse, Oliver
Collection
AG Universitätsverlage
Language
German
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Abstract
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.
URI
https://doab-dev.siscern.org/handle/20.500.12854/151868
Keywords
Produktionssteuerung; Reinforcement Learning; Künstliche Intelligenz; Terminierung; Production control; artificial intelligence; scheduling
DOI
10.5445/KSP/1000156002
ISBN
9783731512820
Publisher
KIT Scientific Publishing
Publisher website
http://www.ksp.kit.edu/
Publication date and place
2023
Series
Reihe Informationsmanagement im Engineering Karlsruhe,
Classification
Mechanical engineering and materials
Pages
208
Review type
Full text
Anonymity
All identities known
Reviewer type
Editorial board member; External peer reviewer
Review stage
Pre-publication
Open review
No
Publish responsibility
Books or series editor
Rights
https://creativecommons.org/licenses/by-sa/4.0/
open access
Except where otherwise noted, this item's license is described as open access