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An experimental study on the application of reinforcement learning in injection molding in the spirit of Industry 4.0

Párizs, Richárd Dominik and Török, Dániel (2024) An experimental study on the application of reinforcement learning in injection molding in the spirit of Industry 4.0. APPLIED SOFT COMPUTING, 167. No.-112236. ISSN 1568-4946

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Abstract

The use of reinforcement learning in the injection molding process is a little-researched area in the era of Industry 4.0. The use of a smart decision-making algorithm is necessary for such a complex production method. Therefore, our research aims to extend the knowledge of the practical use of reinforcement learning in injection molding. In our study, we examined the effect of the parameters of the Actor-Critic algorithm to give a broader picture of the learning process. In addition, we show how to use simulation data, as prior knowledge, to set up the injection molding process for the production of an unknown part.

Item Type: Article
Uncontrolled Keywords: Injection molding, Reinforcement learning, Actor-critic algorithm, Industry 4.0, Self-adjustment
Subjects: T Technology / alkalmazott, műszaki tudományok > TJ Mechanical engineering and machinery / gépészmérnöki tudományok
Depositing User: Dr. Tamás Tábi
Date Deposited: 29 Sep 2024 17:17
Last Modified: 29 Sep 2024 17:17
URI: https://real.mtak.hu/id/eprint/206381

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