• TECHNOLOGY
AUTOMATED TECH COMES TO AFRICAN DEEP-LEVEL SHAFTS
In the deep-level mining environments that characterise much of the South African gold and platinum sectors, the mine shaft is the jugular vein of the operation, carrying men, material and ore. Yet, for decades, the inspection of this vital infrastructure has remained a perilous, time-consuming, and largely analogue affair, writes Dr Nicolaas C Steenkamp.
Background image supplied by Dr Nicolaas C Stenkamp
Enter Canadian deep-tech developer Point Laz and its strategic African partner, Dwyka Mining Services. Together, they are deploying the Lazaruss automated mine shaft scanner, a technology that promises to provide precise, predictive digital twinning.
The partnership to bring this proprietary technology to the African market represents more than just a distribution agreement; it is a signal that the region’ s " Mining 4.0 " adoption is accelerating, moving from experimental pilots to critical infrastructure management.
High costs To understand the value the scanner brings, one must first confront the reality of traditional shaft inspection. For generations, shaft examinations have required highly skilled personnel to physically descend into the shaft, often on the roof of a cage, moving at a snail’ s pace.
It is a process fraught with danger. The hostile environment – wet, dark and slippery – compounds the risk of working at height. Furthermore, the data collected is often subjective. A crack noted by one inspector might be deemed insignificant by another.
Perhaps most critically for the bottom line, these inspections are slow. Mandatory weekly shaft inspections can consume up to 6 % of production time. For a deep-level operator, this downtime translates into staggering financial losses, estimated between USD0.3-million and USD2-million per week, depending on the mine ' s output.
The Lazaruss The scanner is not merely a camera; it is a ruggedised, autonomous data acquisition unit designed specifically for the conditions of a mine shaft.
The partnership to bring this proprietary technology to the African market represents more than just a distribution agreement; it is a signal that the region’ s ' Mining 4.0 ' adoption is accelerating, moving from experimental pilots to critical infrastructure management.
At its core, the device utilises a sensor fusion approach. It is equipped with two survey-grade LiDAR scanners capable of capturing 640 000 points per second with 15mm accuracy. This allows the unit to build a sub-centimetre accurate 3D point cloud of the shaft barrel, guides, buntons and services.
Complementing the LiDAR is a visual array of seven highresolution CMOS sensors. However, cameras in a mine shaft are useless without light. The scanner solves this with its Real-Time Environment Adaptive Lighting system, a battery of seven lights producing a combined 70 000 lumens. This massive illumination capability ensures that photogrammetry is crisp and clear, turning the pitch-black void of the shaft into a fully visible, daylightequivalent environment for the sensors.
What sets this product apart from generic scanning payloads is its operational design. It is built to IP-67 standards, featuring a waterproof and dustproof aluminium casing with stainless steel components to resist the corrosive, humid air typical of return air shafts.
Operationally, it is designed for speed and autonomy. The unit clamps onto the conveyance( fitting all cable sizes) in less than ten minutes. Once activated, it requires no telemetry link or operator monitoring. It relies on onboard processing and standalone, swappable batteries that provide 2 – 3 hours of autonomy. This allows the cage to descend at speeds of up to 1 metre per second, meaning a 3km-deep shaft can be fully scanned in under an hour, a fraction of the time required for a manual visual inspection.
Reactive to predictive While the hardware is impressive, the true value proposition lies in the data processing. Point Laz has moved beyond simple data capture to automated analytics.
Once the scanner returns to the surface, the data is processed to generate automated PDF reports. These are not just raw images but interpreted datasets. The software performs cloud-to-cloud change detection, automatically identifying deviations between the current scan and previous baselines.
If a guide rail has moved, or if a bunton has deformed, the system highlights these changes in red on a generated heatmap. This " traffic light " system allows engineers to focus immediately on problem areas rather than sifting through hours of video footage.
18 • African Mining • March 2026 www. africanmining. co. za