Explore our solutions marketplace

Discover innovation with our solution finder

How does it work?

Learn more about how Axora can help you

Explore our knowledge

Read our expert insights, reports, watch webinars


Explore our community

Share knowledge in our expert community

Join us

Connect, collaborate and chat

About us

Learn more about Axora

Find out more about Axora and our team


The pressure is on for mining: Is the traditional model fit for the future?

The challenges facing the industry range from severe skills shortages to the increasing difficulty in locating rich, surface ore deposits; accelerated in the past year by the global pandemic. Technology and the use of data will be crucial in tackling these, but what can companies do right now, regardless of size?

14 December 2020


contact-Joe Carr

Joe Carr

Mining Innovation Director, Axora

Mining has never been more essential and the plans for a green future confirm this. The traditional energy providers are making way for renewable alternatives, the automotive industry is making plans to phase out fossil fuels, and these goals have something in common; the need for metal. Whether it is hundreds of pounds of copper for a wind turbine or lithium for a Tesla battery, the demand for raw materials to be extracted from the ground is as high as ever and growing.

Although the industry’s core model has an essential role to play in the future, this does not mean the traditional business model can afford to go unchanged. The challenges the industry face range from severe skills shortages to the increasing difficulty in locating rich, surface ore deposits. These challenges have been compounded in the past year by the global pandemic, accelerating the need for solutions. Technology and the use of data will be crucial in tackling these, but which are the lower hanging fruits that mining companies can benefit from regardless of their size?

COVID-19 and the skills crisis

The mining industry has not escaped the disruption caused by the pandemic, from outbreaks on sites that have led to closures, to borders being shut by governments. A standout example is Rio Tinto’s move to relocate 800 miners and their families to Western Australia from Queensland because of intra-state border closures. Because of these impacts, organisations across the industry are exploring and implementing autonomous and semi-autonomous technologies in a bid to increase efficiency and safeguard business continuity.

As more technology is integrated and remote operations become increasingly common, it is likely that the mining workforce will become younger, more diverse, and more technologically savvy as new opportunities provide a better work-life balance.

The pandemic has also exacerbated the growing problem of the skills gap, sharpening the industry’s focus on finding ways of enabling existing workforces to achieve more with what they already have. This is driving an increase in autonomous and remote operations centres (ROC) where engineers can oversee on-site operations from afar. The likes of Caterpillar, Komatsu and newer companies like Zyfra are leading the charge in supporting mining companies to adopt new, autonomous technologies, and today there are already some mines where there are no drivers at all. Rio Tinto’s AutoHaul train fleet is another good example, with autonomous trains transporting ore from mines to ports in Australia - allowing more production with the same assets.

While COVID-19 is pushing mining organisations to find solutions to the skills shortage, the knock-on effect of these innovations could transform the industry’s traditional demographics. As more technology is integrated and remote operations become increasingly common, it is likely that the mining workforce will become younger, more diverse, and more technologically savvy as new opportunities provide a better work-life balance.

Locating ore and navigating government policy

Some of the world’s mining heartlands include North America, Australia, South Africa and Chile, where rich, surface ore deposits have traditionally been found. While organisations across the industry will continue to find materials in these locations, it is becoming harder, increasing the pressure on organisations to explore outside of these safe havens and to go underground. Mining underground poses a range of technical and financial challenges, which demand stronger returns from shareholders and local stakeholders; something mining companies will have to adapt to if they are to succeed.

Government policy is another locational challenge that is shaping the future of mining. We are seeing an example of this in Mongolia as the government presses to increase in their existing 34 per cent share of Oyu Tolgoi, while nationalisation plans are being rolled out in places like Papua New Guinea, Zambia and Tanzania, to increase government shares in operations.

In terms of mining underground, technology also holds the key to remedying the challenges associated with it. An example from my own experience is when I was in charge of ventilation engineering, a critical process in ensuring that there was the right amount of air supplied underground to those working at the face. Forty per cent of an underground mine’s energy cost is linked to airflow management and ventilation, and automated technology offers a multipronged solution. By removing people from the working face we can reduce or eliminate the need for costly ventilation and heating systems, as well as adapting mine design to be less conservative with reduced CAPEX spending on shafts and raises.

Building the connected mine

We have heard a lot about automation and robotics, but there are a range of technologies that are changing and improving the way miners work. As innovative technologies begin to mature, they cease to be the preserve of the top-tier mining companies with a billion dollars to spend on it. Now we are beginning to see more mid-tier players establishing the infrastructure and connectivity that is necessary for beginning the journey toward automation.

I think there is a huge and easily accessible opportunity for mining organisations to implement machine learning and AI for equipment maintenance.

On the subject of infrastructure, the mines of today are being built with 5G in mind. A recent report from Fitch Solutions has predicted that 5G will be widespread in mining in the next five years, and last month, Polymetal contracted with Nokia to install 5G on a site in Russia. These advances in connectivity are not exclusive to new sites, with organisations presenting multiyear plans to install underground Wi-Fi networks in old mines that will extend all the way to the face. Connectivity is vital to the capture and analysis of important data being generated at the heart of mine operations, drilling data being a prime example that can be leveraged to optimise efficiency and yield. Once robust connectivity is in place, mining organisations can begin integrating IoT and edge connectivity, collating real-time data from a variety of sensors to create a clear and detailed view of all activity and associated conditions.

I think there is a huge and easily accessible opportunity for mining organisations to implement machine learning and AI for equipment maintenance. Today, most mining organisations carry out maintenance periodically, or simply based on how hard a machine has been worked. From air filters that need to be changed to engines that require rebuilding, there are constant issues that are expensive and interrupt operations, so much of which could be prevented with predictive maintenance.

Much of this data is already available to mining companies, even for those operating a semi-modern fleet of vehicles, meaning that for most, the data is just waiting to be leveraged to great advantage. I have seen first-hand the delays caused when a truck breaks down and blocks the haul road, or when a primary crusher stops due to unexpected maintenance issues. These expensive incidents become avoidable when moving from a planned maintenance approach to a predictive one, which will be key to optimising mine production uptime with existing assets.

Why data is key to overcoming industry challenges

Process automation promises many benefits, but for most mining organisations this is a longer-term goal that cannot be implemented over night. Getting the right infrastructure and specialisation are essential foundations to automation and robotics, and the right use of data is the gateway to achieving these ends.

It is important that mining companies recognise the value of the data they already have at their disposal, especially for powering machine learning processes that can allow for predictive maintenance. With this in place, mining organisations can tackle a range of short-term challenges in a single move, from enabling existing workforces to achieve more, saving money and improving the visibility and efficiency of underground operations. Collecting and leveraging data effectively is an easily accessible way for mining organisations to achieve a number of quick wins, while at the same time setting the scene for future innovations.

It is often said that progress comes with a bang, but for the mining industry that has never been the case. The industry can and will progress with small, steady gains. Organisations will begin to optimise each step for slightly more tonnage, less unplanned downtime, more utilisation and a smarter way of working, and these are the right steps to take.

Sometimes a small step has a greater impact than a large leap.

This article is a part of our Innovation Leaders in efficiency series. To view the report and further interviews and insights into efficiency solutions, visit our Innovation Leaders page here.

14 December 2020

Unlock transformation

What industry-specific challenges are you facing right now? Talk to us so we can find proven solution to help you.

I want to learn more

Visit our knowledge hub

I want to explore solutions

Visit our solutions catalogue