Application of digital twins in the Metaverse for training in plastic injection.

Abstract One of the applications of the Metaverse is the creation of digital twins for training. In this study, we will analyze its application in plastic injection as a powerful educational tool that allows virtual replication of the entire manufacturing process, from mold preparation to final product. In technical and industrial training, we hypothesize that this technology will help improve practical learning and theoretical understanding without relying on expensive physical facilities or material waste. To this end, a 3D replica of a plastic injection machine has been created, where students can interact by adjusting parameters such as: Mold and material temperature, Injection speed, Pressure applied during the injection cycle, cooling and solidification time of the plastic, etc. This interaction will allow students to see the direct effects of these parameters on the final product without the need to use a physical machine. The result is a deep experiential learning, where students can test and see the results in real time. The configurable data presented on the virtual machine has previously been analyzed on site.Two types of materials and two different pieces have been analyzed. We intend for this study to serve to train students without risks, but also at the industrial level to help save costs and resources, and to improve problem diagnosis and defect analysis. Ultimately, digital twins represent a great opportunity to transform plastic injection training, providing an immersive, safe, and optimized educational experience. They prepare students for Industry 5.0, for the challenges of modern manufacturing, and for working with advanced technologies in smart factories.