Data is one of the most valuable assets that mining companies have today. Yet for many, its management is a rapidly growing source of risk.
By 2025, Statista predicts that the total amount of data created, captured, copied, and consumed globally will exceed 181 zettabytes (a 33% increase from 120 zettabytes in 2023, and a 448% increase from 33 zettabytes in 2018).
Instrumented, smart mining operations generate colossal amounts of data. For example, in 2018, Rio Tinto’s Pilbara operations, which include 16 mines, 1500km of rail, three ports, and more, were reported to create 2.4 terabytes (TB) of data every minute – a number which, considering the growth rates cited by Statista, will have increased exponentially in the ensuing years.
When supported by modern management systems and practices, more data can mean safer, more efficient, and agile mines with more value-generation opportunities.
Still, more data can also mean more risks. These are often perceived to be mainly corporate; for instance, errors created through manual data handling that are picked up during a standards audit and must be time-consumingly traced back to the source. Even more worrying are the physical health and safety dangers that poor data management practices pose.
More data, more safety risks
One function where these impacts are becoming increasingly clear is mine planning. Historically, mine planning, like most tasks, was handled on paper. Later, engineers adopted programs like AutoCAD and Microsoft Excel, but the two were not linked. The onus was on the engineers to transfer information between the two systems and keep the plan and spreadsheet up-to-date.
Today, 3D CAD models with attributed data are used, alongside a Gantt chart scheduler. The two programs are connected so that when a change is made in one it is reflected in the other. Whereas in the past it might have taken a month or more to create a life-of-mine (LOM) plan for a caving operation, now, dozens of scenarios can be run to find the optimal design in just a few hours.
Today, mine planning is informed by hundreds of data streams, from orebody knowledge which evolves with drilling and development of a deposit, to live production data from ore sorting and mineral processing; it is a function that is constantly moving in response to dynamic datasets.
In turn, each iteration of a plan generates its own data, and the level of detail increases as the time horizon narrows. For example, a long-range, LOM plan will include significantly less detail than a short-term plan which informs daily work.
As we move across time horizons, each plan has more data associated with it. For execution, detailed designs are produced for every cut or blast round in different areas of the mine. These are often created in different programs and stored in something like a Windows-based file-management system.
This is a preview of an article that was originally published in the April 2025 issue of Global Mining Review.
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