IM April 2025 April 2025 | Page 75

PRE-CONCENTRATI ON AND ORE SORTING

generated through the HSI sensing.“ I am really excited about applying machine learning to this type of data and making observations that go beyond elemental analysis s, to look at a broader range of characteristics,” he said.

This exercise – and the data that has been received – has allowed Weir to move beyond copper, with the company confident it now has a viable ore characterisation proposition for the iron ore sector.“ We’ re focused on the same characteristics that the miners are after, so we feel the solution is in line with the industry’ s focus areas,” Carpenter said.

Having concluded the previous copper sensing trial, Carpenter says the company is close to finding a development partner with a test site that can help Weir go a stage further than the ore characterisation prototype it has run to a minimal viable product able to characterise the material accurately and effectively.

“ The sample testing we have been doing behind the curtain is allowing us to carry out the analysis and solution sharpening to move us into the next stages of commercialisation,” he said, explaining that this is likely to be a conveyorbased solution for the plant.

“ We’ re also engaged in the mechanical part of this equation – looking beyond the sensor and software – to where diversions might make most sense,” he says, implying an ore sorting solution is also not far away.

In terms of ongoing R & D, Weir is developing a customised HSI sensor solution that can work in the pit without the illumination drawbacks that come with current off-the-shelf solutions.

“ We have validated the system in the lab and are happy with the image response,” Carpenter

said.“ We are now testing the capabilities of the system when exposed to some of the more challenging environmental conditions that would be encountered in the pit.”

The first likely application for this customised HSI sensor will be on a shovel, according to Carpenter, an area Weir’ s ESCO division – through its GET expertise – and MOTION METRICS – through its ShovelMetrics™ solution – know well.

“ We believe the closer we can get to the face, the more value we can bring to the sorting equation.”

MineSense on diversions and data

MineSense continues to make waves across the pre-concentration and ore sorting space,

leveraging the front line data from its XRF-based ShovelSense ® units to make diversions in the pit, as well as influence downstream activities.

ShovelSense uses XRF-based sensing technology that is mounted directly to diggingg equipment such as wheel loaders and shovels to, MineSense says, accurately characterise and grade each bucket, and differentiate between

low-, medium- and high-grade mineralised material. With around 30 units in the field all generating valuable data, this shovel-bas sed information is cascading up- and down-stream for changes to block models in the former and processing parameters in the latter.

Adding on additional conveyor-based BeltSense ® units in strategic locations across the flowsheet is further paying off for companies, as

part of an offering that the Vancouver-based company calls Mine to Mill Powered by ShovelSense. This offering assists geologists in the pit with grade-based information, as well as provides the likes of porphyry or skarn mineralisation categorisation for stockpiles of material metallurgists can act on.

Jeff More, President and CEO of the company, says more companies are realising the value of this complementary offering, with both the Copper Mountain mine in British Columbia, Canada, and Collahuasi, in Chile, being early supporters.

“ Collahuasi is in the process of installing a fourth ShovelSense unit, which is primarily focused on improving recovery in the flotation circuit,” he told IM.“ This is in addition to the three shovels for diversions in the pit.” These are complemented by four BeltSense units within the processing plant.

More was confident that another two or three

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