Q-Learning for Inventory Management: an application case

The recent applications of 4.0 technologies are gradually leading to the introduction and development of artificial intelligence in production systems. This study discusses the assessment of a Machine Learning model, based on Reinforcement Learning, that may allow the optimization of the inventory level at the machine level, thus improving the ordering system and inventory management. The model is applied to a real industrial case and the results, compared with those obtained by using the traditional optimization techniques, show an appreciable performance. It can be concluded that the model of Machine Learning developed can be successfully used for improving the order cycle of an enterprise.