Revolutionizing mine ventilation with real-time digital twin technology
Revolutionizing mine ventilation with real-time digital twin technology
Publish Date: 2026-07-16 04:32:00
Source Domain: africanminingmarket.com
Christo Visagie
The concept of digital twins can sound abstract, but in mine ventilation, it has already become a practical tool. When detailed simulation models are paired with live sensor data, operators gain a reliable, real‑time picture of underground conditions, such as airflow shifting, temperatures changing, contaminants moving, and equipment relocating. Instead of snapshots or intuition, they see how the mine behaves moment to moment, with a clear view of expected versus actual performance.
This visibility sharpens decision‑making, as anomalies surface earlier, scenarios can be tested before anything is physically adjusted, and emergency responses become faster and more informed. Fan and cooling settings, schedules, and maintenance windows move from educated guesswork to model‑supported, data-driven choices.
Critically, a digital twin delivers a reliable, real‑time view of what the ventilation system is actually delivering underground, rather than isolated sensor readings or a static model. It blends a calibrated simulation with live measurements of airflow, temperature, and air quality, allowing engineers to compare expected and actual performance and understand the impact of any adjustment before it is implemented.
Beyond optimisation
In a Ventilation-on-Demand (VoD) environment, the value of a digital twin extends beyond optimisation. It supports active ventilation management by helping to optimise the supply, routing, and distribution of air within safe limits, rather than forcing primary fans to chase a theoretical “optimal” setpoint continuously.
A common early detected anomaly is an unexpected shift in the ventilation balance, caused by a fan trip, a door left open, or a fan starting or stopping elsewhere in the network. Manual VoD, set once at the start of a shift, will not detect this quickly, but real‑time monitoring flags the deviation immediately, enabling faster intervention.
Beyond sudden shifts, slow-burning risks also demand…
