Digital mines: on the pathway to mining without miners

By on 29 November, 2017

Rio Tinto – Autonomous Haulage Trucks, West Angelas minesite; credit Christian Sprogoe Photography.

This article was originally published in the October/November 2017 issue of Position magazine.

The age of the digital mines is here, Australia. They’re neither a futuristic fantasy, nor a frightening iron bot nightmare (thinking back to 1989 and Stephen King’s Maximum Overdrive). Australian mining giants took the lead a decade ago to research and develop technology which has now secured their position as world leaders in the race to mine without miners.

“Digital mines” is a term used to describe highly wired, intensely tracked, and heavily automated mining operations. The benefits of the digital mine are far-reaching for places like Australia’s remote and climatically extreme iron ore deposits, where the road to full automation is well underway.

The evolution of the modern mine is the result of a volatile market and a focus on longer asset lifecycle coupled with the continued triumph of capital over labour. Virtually all the notable innovations developed in the last decade were designed to reduce or eliminate human presence at the mine site. This has the obvious advantage of improved safety, but automation of systems has also been shown to improve efficiency and thereby the bottom line.

Autonomous haulage systems reduce fuel consumption and extend tyre life, and autonomous train loading and transportation can run products straight to port. Automated underground mining systems improve accuracy and allow continuous longwall mining and haulage operations, and automated drilling increases efficiency. Software can autonomously interpret data and make changes to the parameters of processes or machinery to improve results on the fly.

Seven of Rio Tinto’s copper and coal operations are monitored remotely. Image provided by Rio Tinto.

The conversion to automation requires high-precision location data and monitoring. Not only is every individual haulage unit fitted with GPS or GNSS, but so is every other interacting vehicle. LiDAR is used for collision prevention and drones monitor road conditions and maintenance issues. All of this hinges on location data being real-time, highly accurate, and dependable.

The financial benefits are reaped by reducing shift changes and operator fatigue, minimising operating costs, increasing productivity, optimising plant and equipment use, and improving safety for workers. However, the increased efficiency has shifted the needs of mines and created operations that required a smaller labour force. As a result, automation is bad news for unskilled labour and those performing tasks that are historically dangerous or time consuming.

Rio Tinto launched their Mine of the Future in 2008, what former CEO Sam Walsh described in an interview with Business Spectator as “all the things that will actually give the quantum leap in performance and productivity.” With a central hub in Perth, 69 autonomous haulage trucks are remotely operated 1200 km away in the Pilbara. But these enhancements don’t come quickly or cheaply. The operation is supported through university partnerships, including a $21 M deal with the University of Sydney for the development of mine automation technology, and a $10 M deal with Curtin University for materials sensing technology for applications such as ore grading and waste detection.

Walsh also offered insight into looking outside the traditionally obstinate mining sector for inspiration.

“We’re looking at aerospace. We’re looking at oil and gas. We’re looking at some parts of manufacturing.” He continued, “We’re even looking at agriculture. You know, technology for sorting millions of items an hour. It’s going to come from agriculture, food products. It’s not going to come from mining.”

And when it comes to bringing it all together, Walsh noted that the toughest part wasn’t in the lab or behind the workstation developing the technology, but rather in the boardroom. “It’s not the idea, it’s the actual implementation.” The onus is on management to overcome their own bias for historical ways to bring about change.

Adopters of automation have been heavily criticised for the resultant reduction in jobs, which may in itself be a false paradigm.”

 

Change also needs to come in the way that we prepare mining engineers before they even get to the workplace. Dr Mehmet Kizil is an associate professor at the University of Queensland School of Mechanical and Mining Engineering. His research students work on a broad range of projects that feed directly into mining optimisation, and he’s keen to introduce mine automation and data analytics into their mining curriculum. Dr Kizil says updating the curriculum is an ongoing agenda item at UQ, but admits regretfully, it’s a lengthy process. “Change is slow,” he says. “To implement something you have to start the conversation a year ago.”

Beyond the educational hurdles, Dr Kizil sees Big Data, the constant flood of bits and bytes that comes with many sensors that might be attached to a single vehicle, as the single biggest challenge to tackle.

“Our industry is behind in analysing this data,” Dr Kizil says. “We have to learn how to store and analyse and convert these data in into useful information, KPIs and knowledge. We can produce data in real time, but we can’t analyse it in real time – for that we need machine learning.”

Many mining companies don’t have the capacity to analyse the real-time data they acquire, which Dr Kizil refers to as “cyber garbage”. Not that the data are meaningless, but without evaluation and analysis it can’t be converted into the enhancements that probably drove the initial business decision to adopt real-time data acquisition in the first place.

Not surprisingly, mining automation has been met with a fair amount of disapproval. Adopters of automation have been heavily criticised for the resultant reduction in jobs, which may in itself be a false paradigm. True, the number of haul truck drivers and ore graders has been reduced, but the need for remote operators and maintenance personnel has increased. And under a lower-cost environment, mines can continue to be operational for longer and with lower quality ore.

In an address at a business leadership gathering, Mike Henry of BHP Minerals Australia described the move to automation as one borne out of necessity, saying, “Without advancements like these that keep us competitive, the losses in investment and jobs would be much greater,” Henry explains.

Intentional or not, many of the technological improvements that have led to a smaller workforce have also reduced the environmental impact of mines, such as reduced fuel consumption. They’ve also been successful in reducing the frequency and severity of hazards faced by mine workers. When Bingham Canyon experienced one of the largest landslides every recorded, no loss of life occurred due in no small part to the use of radar, prisms and real-time geotechnical sensors that gave workers enough warning to evacuate. Dangerously unstable areas were then cleared using remotely control excavators.

The migration of the mining industry to automation will drive continued enhancements and improvements in positioning and location data. Adopters will also have to tackle new challenges to digital security and network reliability. While automation remains an expensive undertaking, primarily reserved for majors with deeply-lined pockets, manual mining operations will eventually join the ranks of the pit ponies and canaries as the tide of technology floods the industry without ebb.

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