Data science and AI are enabling mine operators to identify trends in safety that have been historically invisible to humans, attendees heard today at autonomous solutions company Hexagon's HxGN LIVE event in Las Vegas.

Brazilian industrial engineering firm IHM Stefanini related at the event how they had harnessed machine learning to develop a solution that integrated a plethora of sensors and systems at mines run by Chilean copper producer Codelco.

The dashboard of real-time data shown by the solution included over-speeding events, hard-braking events, vehicle concentration levels and gave an overall safety score for mines, and specific regions and shifts.

This ability to compare KPIs and identify how management-level decisions impact on the metrics were having a transformative effect on safety, said Evans Diaz, superintendent of Mine Process Control Engineering at Codelco.

"The beauty of the technology is the level of granularity it gives to ‘attack' these KPIs and get results," he said, adding that the ability to compare the safety scores being achieved by groups, shifts and equipment had helped drive real buy-in from management and operators.

"Speeding is a big issue we need to monitor and analyse, this use of data science in safety enables us to identify trends and also forecast results."

"More importantly than the other comparisons such as between teams and sites, is the ability to see how management decisions are impacting mine safety."

"Now, my organisation has the right tools to show to workers that we take safety incredibly seriously," said Diaz.

Spencer Gracias, CEO, N America of IHM Stefanini said it was heartening to see that AI and clear KPIs can play a positive role in change management and the adoption of technology shifts.

"It feels good to see the safety benefits that this technology can achieve. To hear that it is actually improving the relationship between operators and managers in a big step forward."

 

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