How mining companies use AI, machine learning and robots

Many of us would assume that advances in robotics, automation, artificial intelligence (AI) and machine learning would have been driven by the mining industry, due to the remote mine sites, the hazardous nature of the work and the high costs of labour and transport.

However, it is the manufacturing sector that has spearheaded most of the technological developments, but it is now the mining sector that is now taking advantage of those proven technologies to help boost its recovery after a significant downturn.

Mining is a complex and fluctuating industry, that is fraught with uncertainty around resource pricing, unpredictable resource fields and major projects that need to be managed right through their lifecycle.

Controlling costs for mineral exploration, construction and operation right through to project completion is a monumental challenge, but if the financial elements are managed well it can help mining companies to be both competitive and profitable.

The key to increasing profits is knowing the precise time to increase production when there is strong demand using resource planning, improving the reliability of machinery with predictive and condition-based maintenance monitoring, delivering clarity with precise financial and operational reporting and at the same time providing actionable insights using real-time data extracted from every part of the organisation.

In today’s highly efficient mining operations, making the right decisions depends on their 360-degree visibility of the business and the market, combined with accurate demand forecasting.

With huge footprints in remote locations, diverse labour forces and complex and time-consuming projects, mining companies are using Enterprise Resource Planning (ERP) systems as the technology backbone to their businesses.

Mining’s impact on the economy

If the Australian mining sector is going to continue its widely reported recovery in the wake of the mining industry downturn, using advanced technologies like robotics, integrated with artificial intelligence and machine learning to improve efficiency and productivity is crucial to increasing profitability.

Even modest improvements in yields, speed and efficiency through machine learning can make a significant impact on profits.

The mining industry is uniquely positioned to take its place as a major driver of the Australian economy again.

Those financially or emotionally invested in the mining industry are keen to see the multitude of planned mining projects and developments come to fruition as they will ultimately become the Australian mines of the future; a boost to exports as well as jobs.

Mining’s heartland, Western Australia is still leading the way with new mining projects at the committed and feasibility stage, but according to the Australian Government’s June report – Resources and Energy Quarterly, Queensland is also set for expansion with upcoming developments in a diverse range of commodities, including coal, gold and copper.

Australia currently has the world’s largest gold resources and this is forecast to overtake coal as our fourth largest export by 2020, according the Australian Government.

While iron ore, coal and gold are currently Australia’s leading commodity exports and will play a key part in the sector’s resurgence, the next generation of Australian mines will exploit new opportunities such as battery minerals, including lithium as well as uranium, which is recovering from a sharp downturn.

Therefore, accelerating the discovery minerals that will become Australia’s future mines using advanced technologies is a key priority for the mining industry.

Mineral exploration

AI is leading to earlier identification for mining companies, which can eliminate time and money spent on wasted exploration as well as increasing discovery potential.

The latest mineral exploration technologies have led to more efficient and targeted drilling campaigns, as well as world class discoveries. 

Autonomous vehicles, trains, aircraft and mines

With a vast amount of new technologies emerging over the last ten years including autonomous vehicles, trains, aircraft and even autonomous mines, the mining sector has leapt ahead with a raft of technologies now available to make mining more efficient, safer and autonomous.

Mining companies are currently exploring some of Australia’s new greenfield sites across Western Australia and the Northern Territory that haven’t been previously evaluated due to the terrain or remoteness.

This includes using the most advanced airborne electromagnetic technology, collecting high resolution electromagnetic, magnetic and radiometric data from an autonomous aircraft.

This can simultaneously map shallow and deep features at a higher level of resolution than previously possible, enabling them to develop an understanding of an area’s geology and fully analyse it before drilling any unnecessary deep holes.

Safety and maintenance

Aside from cost savings, AI uses real-time data and analytics to help mining companies prevent accidents and injuries on the job.

If enough high-quality data can be collected, the applied technology should be able to predict failures transforming preventative maintenance into predictive maintenance.

What’s next?

It is clear that the use of robotics, AI and machine learning can significantly help save costs, increase efficiency, improve safety, increase discovery potential and many other benefits for mining companies.

What has held them back was the data challenge. As being able to extract and make actionable insights from a large amount of data has often been too difficult.

However, mining companies are now working on scaling the use of AI in mining and we will start to see more sophisticated use of AI in the mining industry.

Rob Stummer is SYSYPRO Australasia chief executive.

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