The Gold Fields Austmine Smart Mining event took place this week in Perth where MICROMINE took the opportunity to showcase its soon to be released machine learning functionality for Pitram. The event was attended by representatives from across the mining equipment, technology and services (METS) sector.
MICROMINE was the platinum sponsor of the event, where Chief Technology Officer Ivan Zelina presented to attendees Pitram’s new underground mining precision software which is set to refine and enhance loading and haulage processes.
This new offering will see the introduction of Artificial intelligence, utilising the processes of computer vision and deep machine learning, on-board cameras are placed on loaders to track variables such as loading time, hauling time, dumping time and travelling empty time. The video feed is processed on the Pitram vehicle computer edge device, the extracted information is then transferred to Pitram servers for processing and analyses.
The solution intelligently considers the information gathered to pinpoint areas of potential improvement that could bolster machinery efficiency and safety.
Attendees at the event were shown videos of the technology being used in a real-world underground environment at a Pitram client’s site.
More information on Pitram’s machine learning functionality can be found here.
Gold Fields Unit Manager of Projects Michael Place delivered the key note address for the night providing his insights on achieving operational excellence through leadership. Michael discussed the priorities for Granny Smith Gold Mine Projects over the next 12 months and explored the technologies and innovations he believes will create the next wave of disruption to our industry.
Michael emphasised the important role the METS sector plays in the industry and how these companies are assisting to advance Granny Smith’s operations and improve production performance.
Granny Smith site has been using market leading fleet management and mine control solution Pitram since 2012 for capturing data related to equipment, personnel and materials, providing an overall view of the current mine status and therefore enabling improved control over operations.
