Knowledge-Based Creation of Industrial VR Training Scenarios

Abstract

The application of virtual reality (VR) for building training systems has grown in popularity across diverse fields. This trend is particularly prevalent in Industry 4.0, where many real-world training scenarios can be expensive or pose potential dangers to trainees. The most important aspect of professional training is domain-specific knowledge, which can be expressed using the semantic web approach. This approach facilitates complex queries and reasoning against the representation of training scenarios, which can be useful for educational purposes. However, current methods and tools for creating VR training systems do not utilize semantic knowledge representation, making it difficult for domain experts without IT expertise to create, modify, and manage training scenarios. To address this issue, we propose an ontology-based representation and a method of modeling VR training scenarios. We demonstrate our approach by modeling VR training scenarios for Industry 4.0 in the field of the production of household equipment. The domain knowledge used represents training activities, potential errors, and equipment failures in a way comprehensible to domain experts.