Reinforcement learning and digital twin-driven optimization of production scheduling with the digital model playground

Reinforcement learning and digital twin-driven optimization of production scheduling with the digital model playground

Abstract The significance of digital technologies in the context of digitizing production processes, such as Artificial Intelligence (AI) and Digital Twins, is on the rise. A promising avenue of research is the optimization of digital twins through Reinforcement Learning (RL). This necessitates a si...

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Bibliographic Details
Main Authors: Arne Seipolt, Ralf Buschermöhle, Vladislav Haag, Wilhelm Hasselbring, Maximilian Höfinghoff, Marcel Schumacher, Henrik Wilbers
Format: Article
Language:English
Published: Springer 2024-12-01
Series:Discover Internet of Things
Subjects:
Hybrid simulation
Discrete event simulation
Reinforcement learning
Digital twins
Production scheduling
Online Access:https://doi.org/10.1007/s43926-024-00087-0
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https://doi.org/10.1007/s43926-024-00087-0

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