Mine hoists are vital for efficiently transporting materials and personnel between surface and underground mining operations, making their safety and reliability paramount. However, conventional monitoring approaches, which rely on distributed sensors or video surveillance, are limited in their ability to capture the global dynamics of the system, leading to suboptimal decision-making and potential safety risks. This research introduces the integration of digital twin technology into the monitoring and management of mine hoists to address these challenges. This study uses Unity-based modeling to create a virtual system capable of real-time synchronization with its physical counterpart. The digital twin simulates dynamic load changes, predicts potential faults, and optimizes operational parameters through intelligent algorithms. A robust monitoring framework was developed, consisting of a multi-layered architecture that integrates physical systems, real-time data collection, and virtual simulations. Field tests on a multi-rope friction hoist verified the system’s performance, with results demonstrating improved stability, accuracy, and predictive capabilities. A health evaluation model further enhances safety by categorizing the hoist’s operational state into health levels such as ‘healthy,’ ‘sub-healthy,’ ‘warning,’ and ‘fault.’ This model identifies critical risks, such as wire rope tension anomalies, and provides early warnings, ensuring timely interventions.
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