This research focuses on developing an efficient learning platform for maintenance workers. Recognizing the challenges maintenance workers face, such as difficulties in identifying faulty components and disassembling unnecessary parts, this project aims to address these issues by integrating the Metaverse and Machine Learning. By leveraging machine learning models that accurately detect faults, maintenance workers can access a robust, immersive learning environment that empowers them to make informed decisions and avoid unnecessary tasks. This approach enhances learning efficiency, reduces downtime, and cultivates practical problem-solving skills among maintenance workers. The outcomes of this research contribute significantly to the advancement of integrating virtual reality technologies and machine learning within Industrial Metaverse settings, paving the way for improved maintenance processes and more efficient learning experiences.