Digital twins paving way to safer underground mining

Digital twins represent a “pivotal technological advancement” in underground mining, offering innovative solutions for safety, operational efficiency and environmental sustainability, says business intelligence and analytics company In2IT Technologies technology services group VP and MD Amritesh Anand.

A digital twin is a virtual replica of an operation that integrates real-time data from various sources to simulate, monitor and enhance the mining environment, operations and equipment for enhanced safety, efficiency and sustainability.

With the model’s role set to expand further, strengthening its ability to simulate complex scenarios, monitor real-time data and integrate geological information, it is an “indispensable tool” for modern mining operations.

Anand adds that collaboration among mining companies, technology providers and regulatory bodies will be crucial in driving the adoption and development of digital twins.

The integration of advanced technologies, including artificial intelligence, machine learning and augmented reality, will enhance the capabilities of digital twins, he says, noting that these technologies will allow for more sophisticated data analysis, predictive modelling and immersive training experiences, further improving safety, efficiency and sustainability.

As mining companies, technology providers and regulatory bodies work together to overcome technical and operational challenges, digital twins will become an integral part of the mining industry's future, paving the way for smarter, safer and more sustainable underground mining operations.

However, underground mining faces inherent challenges, including complex geological structures, hazardous working conditions and the imperative for environmental stewardship, he adds.

Anand says digital twins are, therefore, considered a powerful tool to navigate these challenges by creating accurate virtual models of mine environments.

These models allow for the simulation of various scenarios, such as equipment failures and structural collapses or hazardous gas emissions, consequently enabling mining companies to prepare and respond effectively.

Through integrating sensors and Internet-ofThings devices, digital twins offer a granular view of the mining operation in real time. This capability extends to equipment monitoring, where variables, such as temperature, pressure and wear, are tracked continuously.

By predicting maintenance needs and identifying potential failures before they occur, digital twins can significantly reduce downtime.

“By simulating different operational scenarios, digital twins help identify the most efficient workflows, reducing waste and improving overall productivity. This optimisation extends to logistical aspects, where they can streamline the movement of personnel and materials, minimising delays and maximising resource use.”

Anand adds that the integration of geological data within digital twins transforms the way mining companies understand and exploit underground resources.

By combining three-dimensional modelling with geological surveys and data analysis, digital twins offer a level of insight into ore quality, distribution and accessibility. This enhanced understanding supports more informed decision-making, from exploration to extraction, ensuring that mining operations are sustainable and profitable.

Safety is a paramount concern in underground mining, where the risk of accidents and emergencies is ever present. In this regard, digital twins contribute significantly to safety improvements by simulating emergency situations and monitoring environmental conditions in real time.

Anand explains that this proactive approach enables mining companies to implement safety measures and emergency responses more effectively, protecting the lives of miners and the integrity of the mining operation.