Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung
| dc.contributor.author | Lohse, Oliver | |
| dc.date.accessioned | 2023-04-26T04:00:52Z | |
| dc.date.available | 2023-04-26T04:00:52Z | |
| dc.date.issued | 2023 | |
| dc.date.submitted | 2023-04-24T11:23:57Z | |
| dc.identifier | https://library.oapen.org/handle/20.500.12657/62536 | |
| dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/99534 | |
| dc.description.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. | |
| dc.language | German | |
| dc.relation.ispartofseries | Reihe Informationsmanagement im Engineering Karlsruhe | |
| dc.rights | open access | |
| dc.subject.other | Produktionssteuerung; Reinforcement Learning; Künstliche Intelligenz; Terminierung; Production control; artificial intelligence; scheduling | |
| dc.subject.other | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials | |
| dc.title | Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung | |
| dc.type | book | |
| oapen.identifier.doi | 10.5445/KSP/1000156002 | |
| oapen.relation.isPublishedBy | 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 | |
| oapen.pages | 208 | |
| dc.seriesnumber | 25 |
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