Production Optimisation
In open-pit mining, some of the biggest productivity gains can come not from buying more trucks, but from loading the ones you have with greater precision.
In an era where emerging technologies promise to transform mining operations, from AI-driven optimisation to fully automated systems, the real challenge is not finding the next breakthrough.
At the sharp end of metallurgical decision-making, where feasibility meets financial risk, one recurring theme echoes loudest: if you don’t know your orebody, you don’t know your project.
In a mining landscape increasingly defined by lower ore grades, ESG scrutiny, and complex feedstocks, recovery performance has never been more critical.
In the drive to improve energy efficiency, recovery, and metallurgical precision, a global engineering company has released a quiet disruptor: a machine-learning-enabled sensor that’s helping mining operations monitor and optimise grind size with new levels of accuracy.
Western Australia’s listed companies have defied commodity headwinds to post a three point seven percent rise in collective market capitalisation, closing the 2025 financial year at A$362+ billion, according to the Deloitte WA Index Diggers & Dealers Special Edition.
From deserts to drill pads, remote exploration teams increasingly need to make informed, high-impact decisions without waiting weeks for lab results.
For decades, mine planning has leaned heavily on deterministic models - tools that simplify the earth into a single version of the truth.
When mining engineer Eddy Zhang took the stage at the 2025 AusIMM Underground Operators Conference in Adelaide, he was candid about the task at hand: “Today I’ll be presenting learnings from reorientating the Ernest Henry sublevel cave.
As ore grades decline and sustainability pressures rise, mining operations are being forced to find new ways to optimise resource extraction.
