Workflow Management
Unlocking up to 70 per cent faster mine planning cycles and millions in additional project value is now within reach for operations that combine centralised data systems, virtual twins and advanced optimisation engines.
The future of mining is already here - and it’s being shaped by AI systems that can think, act and integrate seamlessly with the tools you already use.
When Bengalla Mining Company lost tyre fitter Quinten Moore in 2018, the tragedy forced a deep reckoning: could leadership and supervision be strengthened to ensure safer outcomes? For Bengalla, the answer was not only yes, but essential.
It’s not every day you hear about two massive shafts being sunk side by side in Australian coal country, each with its own design, equipment, and risks.
Even with control plans, take-fives, and risk assessments stacked high, mining engineers admit incidents still happen because the real world never plays out as neatly as the documents.
The future of underground mining could mean no one sets foot underground at all - a zero-entry mine powered by autonomy, interoperability, and constantly updated digital twins.
As mining companies increasingly operate from hundreds, sometimes thousands, of kilometres away from the pit or plant, one challenge has remained constant – how to give remote teams the same operational context, detail, and situational awareness they’d have if they were standing on site.
Every hour of downtime costs a mine tens of thousands of dollars, and Professor Amir Gandomi told the NSW Resources Regulator’s Mechanical Engineering Safety Seminar how artificial intelligence is now cutting those losses by predicting failures and optimising operations in seconds.
What do Formula 1 racing and tailings storage have in common? More than you’d think - especially when AI joins the engineering crew.
For years, exploration teams have wrestled with data chaos in the field.
