This site uses cookies to provide you with a more responsive and personalised service. By using this site you agree to our use of cookies. Please read our privacy policy for more information on the cookies we use and how to delete or block them.
  • Data and the Mining Industry
Industry issue:

Data and the Mining Industry

15 November 2018

Tim Berners Lee, the inventor of the World Wide Web said “Data is a precious thing and will last longer than the systems themselves”. 

The mining industry is already experiencing an automation revolution.  BDO’s 2020 vision for the mining industry centred firmly upon the impact of this technological change.  We predicted the use of robots will replace 50% of miners by 2020, that the use of Block chain and AI will become commonplace in the industry.

Digitisation will be at the forefront of future investment in the industry. Companies that harness and invest in tools to analyse their data will ultimately gain the competitive advantage.

Digitisation may not necessarily be new to the mining industry but the industry is just figuring out how to get the most out of it. The mining industry is a veritable gold mine of data and we are starting to see companies investing in systems to harness this data and use it to improve the effectiveness and efficiency of their operations.   

 

Rio Tinto; an example of data driving performance

Data underpins all mining operations and has an impact on everything from procurement through to processing and even safety.  Rio Tinto set up a Data Intelligence and Insights team in 2016 as part of their own growth strategy. The Rio Tinto team set up a system to optimise plant and truck utilisation.  The system analyses real time data captured at the crusher, such as bin levels and run rates, and overlays real time truck data such as location and payload.  As a result, the crusher can communicate with trucks and let them know when material is required. 

This means that the machinery can be operated at the ultimate utilisation which helps to extend its life, reduce downtime and save energy and therefore operating costs.  This is a great example of the analysis of data providing the catalyst for improved operational performance and cost savings.

Rio recently announced further investment in a “pioneer lab” in Australia. Employees will move out of their normal business roles to look at how the company can create new digital and technological pilots. 

 

Potential applications of data analytics in Mining

Mining companies should consider the huge range of areas where smart data analytics can enhance business decisions. Data can be used to; 

  • improve the utilisation of machinery so the resource is extracted in the most efficient manner 
  • identify areas of inefficiency and direct further capital spend at areas that will provide the best return
  • provide real time monitoring of both people and machinery to improve safety 
  • monitoring future needs for spare parts, consumables and fuel
  • give procurement teams real time data on pricing to help reduce costs.   

 

Finding the right solutions for Big Data

Management teams understand that they need the right tools to extract and analyse data. Our International Network has always helped mining companies solve financial issues. We are now also developing the digital and data analysis tools for global mining companies. For example, BDO Canada is developing technology that provides mining companies with deep insights into forecasting, budgeting, cost control and corporate compliance practices.

 

BDO solutions for data analytics

Lundin Mining Corporation, the TSX listed diversified base metals mining company, used manual processes and spreadsheets for planning and reporting. This time-consuming approach prevented making timely and effective decisions and was affecting efficiency.

With the help of BDO, Lundin implemented a cloud-based business planning tool which significantly improved forecasting and budget cycle efficiency. The new tool improved accuracy as well as giving the key decision makers real time visibility into metrics and results.   

 

Cybersecurity; managing the risks associated with Data and Digitisation

Big data and innovative technology are driving competitive advantage, but they also represent a risk that needs to be managed carefully. Cybersecurity needs to be front of mind. The industrial control system, the central hub controlling a mine’s automated operations, could serve as the hacker’s point of entry. Damage and disruption to automated equipment could jeopardise the safety of miners. Many of the systems in place are designed to monitor and detect dangerous conditions.

The mining industry is no stranger to environmental scrutiny. Advances in technology have introduced more sustainable mining methods such as bioleaching. Operations extract minerals by using biological assets instead of harmful chemicals. Despite those advancements, environmental concerns persist, including water and soil contamination, carbon emissions, and impact on animal life. We have seen the emergence of hacktivists, environmentally-motivated hackers.

Our 2020 vision for mining predicts that hacktivists will launch at least five cyberattacks on mines because of the environmental and social threats they pose. Permanent denial of service (PDOs) attacks will use workers connected devices to launch the attacks. These PDOs are different from previous cyber-attacks in that they aim to destroy physical equipment and structures, permanently disable services and wipe out data.

Global mining companies should not underestimate the potential risk, especially those in the early stages of adopting digital technologies and big data. Management must ensure that all new digital technologies and tools are secure and able to withstand highly motivated and skilled cyber attackers.