VR-based digital twin for remote monitoring of mining equipment: Architecture and a case study

Abstract

BackgroundTraditional methods for monitoring mining equipment rely primarily on visual inspections, which are time-consuming, inefficient, and hazardous. This article introduces a novel approach to monitoring mission-critical systems and services in the mining industry by integrating virtual reality (VR) and digital twin (DT) technologies. VR-based DTs enable remote equipment monitoring, advanced analysis of machine health, enhanced visualization, and improved decision making. MethodsThis article presents an architecture for VR-based DT development, including the developmental stages, activities, and stakeholders involved. A case study on the condition monitoring of a conveyor belt using real-time synthetic vibration sensor data was conducted using the proposed methodology. The study demonstrated the application of the methodology in remote monitoring and identified the need for further development for implementation in active mining operations. The article also discusses interdisciplinarity, choice of tools, computational resources, time and cost, human involvement, user acceptance, frequency of inspection, multiuser environment, potential risks, and applications beyond the mining industry. ResultsThe findings of this study provide a foundation for future research in the domain of VR-based DTs for remote equipment monitoring and a novel application area for VR in mining.