Reinforcement Learning in der Produktionssteuerung/Reinforcement Learning for production control

Inhaltsverzeichnis

Bibliographische Infos

Cover der Ausgabe: wt Werkstattstechnik online Jahrgang 115 (2025), Heft 11-12
Open Access Vollzugriff

wt Werkstattstechnik online

Jahrgang 115 (2025), Heft 11-12

Autor:innen:
Verlag
VDI fachmedien, Düsseldorf
Copyrightjahr
2025
ISSN-Online
1436-4980
ISSN-Print
1436-4980

Kapitelinformationen

Open Access Vollzugriff

Jahrgang 115 (2025), Heft 11-12

Reinforcement Learning in der Produktionssteuerung/Reinforcement Learning for production control

Autor:innen:
ISSN-Print
1436-4980
ISSN-Online
1436-4980
Kapitelvorschau:

Die Steuerung von Produktionsprozessen stellt aufgrund der hohen Prozesskomplexität eine zentrale Herausforderung für produzierende Unternehmen dar. Vor diesem Hintergrund gewinnt die Automatisierung von Planungs- und Steuerungsaufgaben durch Algorithmen zunehmend an Bedeutung. Methoden des Reinforcement Learning bieten vielversprechendes Potenzial, um diese Herausforderung zu adressieren. Dieser Beitrag vergleicht Methoden des Reinforcement Learning mit exakten und metaheuristischen Algorithmen, um die Einsatzgrenzen und die Konkurrenzfähigkeit lernbasierter Verfahren im aktuellen Entwicklungsstand zu bewerten.

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