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

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.