The value of machine learning and artificial intelligence to the global mining industry is growing rapidly - in particular in areas such as predictive maintenance, operational optimisation and production profitability analysis

SYDNEY - Aug. 25, 2020 - PRLog -- Boutique investment banking & strategy consulting firm LCC Asia Pacific has released a whitepaper on the emerging use of artificial intelligence & machine learning technology in the mineral processing sector.

The white paper, which includes details on operational areas of mineral processing that will become more of a focus for ML in the coming years, is the first in a series of research documents that focuses on the changing nature of the Mining Sector due to technology.

"With the amount of start up capital available to pursue operational improvement through technology, the timing has never been better for young mining engineers and technologists to turn their minds to how AI and ML can be applied to improve the performance of the mineral processing circuit," Nicholas Assef, LCC Asia Pacific's Founder & Principal said.

One area where Mining Companies and Mining Services Providers alike have interest is in the ability to predict with far greater certainty the performance of both fixed plant and mobile plant on mine site operations.  Historically this has been both a labour intensive exercise and one that is not overly precise.  That lack of precision resulting from a variety of causes including changing environmental conditions, human error, different engineering skill sets from service providers, incompatible OEM equipment and ore characteristics that can differ from site to site.

Industry 1.0 technology generally involved a simple physical observation of a sensor that was embedded in a piece of equipment (typically some form of wear plate) and gradually that sensor wore out – similar to the brake pad in a car and a warning light.  Connection options to read data were also limited.

The Industry 2.0 is going far beyond that and applying large data sets to allow early warning signs (through pattern recognition) to be identified much earlier by purpose designed algorithms.  Through machine learning multiple streams of data can be processed simultaneously and via the algorithm previously unseen patterns can be observed.  This in turn delivers a number of strategic advantages including a more precise:

• alert system that reduces the number of breakages / unplanned shutdowns
• ability to holistically plan maintenance and operational activities on the entire mine site through a network of interconnected AI applications

"Predictive analytics requires precise measurement of 'change' in operational patterns, which in turn requires new thinking for integrated Data Management Systems that are robust enough to both collect and analyse data, talk to different networks and importantly do all this in some of the planet's harshest environments," Nicholas Assef continued.

"Leaving all this science to one side, implementing new technologies is already proving to drive productivity which in turn results in a larger bottom line profit,"  Nicholas Assef concluded.

The LCC Asia Pacific white paper on the topic can be accessed here. To learn more on LCC Asia Pacific visit here: www.lccasiapacific.com

About LCC Asia Pacific

Founded in 2003, LCC Asia Pacific is an award winning specialist investment banking and strategic management consulting Firm that specialises in the Mining Services, Engineering, Infrastructure Services and METS Sector - including adoption of Artificial Intelligence & Machine Learning.  www.lccasiapacific.com

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