A Digital Twin for the Bulk Materials Industry
R&D teams today increasingly turn to system-level digital twins to develop, improve, and analyze their equipment and processes — especially in structural, fluid and electromagnetic domains.
But the mining industry has not had such opportunity concerning bulk flow applications, even though it faces similar mandates: Reduce downtime, better predict maintenance, tweak efficiency, increase output, and improve safety. Until now.
ANSYS and Rocky DEM software companies have developed a way to leverage mechanical, design-of-experiment, and discrete element modeling (DEM) tools to create a digital twin for the mining, bulk material and process industries.
This solution uses reduced-order models (ROMs) that minimize compute cost/time yet are accurate in predicting real-world operation.
Beyond financial and efficiency benefits, digital twins offer the industry an opportunity to improve its safety record.
With automation, companies can reduce risk to bulk material handlers; minimal equipment breakage (a result of better maintenance scheduling) means that fewer workers get hurt.
How a Digital Twin Works
For computational efficiency, a physics-based digital twin starts with ROMs based on full 3-D physics. These are connected to a real, on-site asset via an internet of things (IOT) platform that inputs sensor data.
The resulting digital twin provides additional data that cannot be measured.
There is no need to refer to or rely on historical data. Digital twins have been used to accelerate product R&D by simulating product components, to identify and troubleshoot potential process issues, and to predict/improve product performance.
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