In 2000, Sony launched a marketing campaign for its Memory Stick with the tag-line “We are all connected”. Two decades later and that promise is becoming true for the Australian mining industry, which is undergoing a significant change as mining companies embrace new technologies. The Internet of Things, algorithms, artificial intelligence, big data and automated devices are assisting in mine and personnel management, in search of greater efficiencies from pit to port.

In the age of Industry 4.0, mining companies are beginning to take advantage of these technologies on a daily basis. This gives rise to interesting questions about how these technologies will be integrated into mining operations, and how this integration can be achieved from a procedural, operational and legal standpoint.

Two publications released in early 2019 explore possible answers to these questions. First, Deloitte released the 11th edition of its ‘Tracking the Trends 2019’ report (Deloitte Report) outlining the ways mining operations may benefit from Industry 4.0 technologies. Secondly, the Global Mining Guidelines Group released its guidelines for the implementation of autonomous systems within mining operations.[1]

Combined with topical discussion at the AustMine 2019 and Clariden Global’s Digital Mines conferences in recent months, the time is right to consider the implications of these matters.

In this series, we explore some of the key technological themes arising in the mining industry, commencing with the Deloitte Report, and consider the issues arising for lawyers working in this interesting field.

What is Industry 4.0 and how does it relate to mining?

Sometimes called the fourth industrial revolution, ‘Industry 4.0’ is the name given to the trend towards increasing use of automation and connected devices in manufacturing and industrial processes. Industry 4.0 is characterised by assistive technologies and connectivity between the physical and digital worlds.[2] Increasing collection of data across all aspects of the supply chain is a key component, as is the analysis and use of that data for decision-making across all aspects of the supply or value chain.

As with ‘smart factories’ and ‘smart buildings’, mining operations can also benefit from Industry 4.0 technologies. Examples in the real world are numerous, the most obvious being the increasing use of remotely operated vehicles (rail, drilling rigs, road haulage and aircraft/drones), a trend underway for many years. Less obvious applications come from the use of analytics such as those created by Interlate – an Australian company – which analyses real-time data gathered from across the mining operation together with historical and contextual information about the operation in order to find efficiencies across the entire supply chain.[3]

Analytics and the 3 horizons of AI

Deloitte conceives of 3 horizons when it comes to the role of analytics and artificial intelligence working with human decision-makers:

  • Horizon 1 involves ‘assisted intelligence’. Human assistance is required in operation or interpretation.
  • Horizon 2 involves ‘augmented intelligence’. Here, ‘machine learning’ (where AI systems are ‘trained’ with large amounts of data) augments decision-making by humans.
  • Horizon 3 involves ‘autonomous intelligence’. In this scenario, the AI decides and executes autonomously.

Moving through these phases over time, mining companies will progressively shift from analytics that are descriptive in the sense that trends may be identified by the data, to analytics that are predictive and then prescriptive. These processes can be used by companies in a number of ways, for instance in optimising processing plants to minimise downtime, managing haul truck movements to avoid bottlenecks and delays, and planning or predicting maintenance using real-time incident response, monitoring and reporting. Some have reported the successful use of AI to identify mineralisation in Australia.[4]

New Horizons for Risk Management

To manage all of this information, Deloitte calls for the implementation of a ‘digital mine nerve centre’[5] where data is collected, parsed, analysed and deployed. So what are all of these nerves connected to? In its report, Deloitte identifies the following possible digital elements in the network:

  • Autonomous/automated ground vehicles, such as haul trucks, trains and drilling rigs;
  • Remotely piloted aircraft or drones, used for asset inspections and monitoring;
  • Wearable electronics for use by employees;
  • Connected sensors on most assets; and
  • Possibly blockchain technology for asset traceability.

Of course, with this reliance on technology comes new threats such as cybersecurity risks as well as other organisational risks inherent in digital transformation, the amount of data to assimilate, and the pace of change in the modern world. Deloitte suggests this increases the need for robust internal auditing, and that this be approached from a ‘whole-of-business’ standpoint. This may in turn involve the use of AI and analytics to anticipate risk and assist in taking preventative action.

From an integrated physical and cybersecurity standpoint, one need only be reminded of the damage caused by the Stuxnet worm, which infected an Iranian nuclear facility in 2010. It targeted some of the facility’s programmable logic controllers, specifically the automated electromechanical processes responsible for controlling the speeds at which centrifuges separating nuclear material ran. It falsified feedback data in order to mask the true status of its operations. Threats such as these ought to be borne in mind when transitioning a business model to include networked automation.

The Future Workforce

All of this change will necessarily impact the future workforce. The Deloitte Report notes enrolment in mining engineering courses in Australia from 292 in 2014 to 171 in 2017, with a projected fall to 47 in 2020.[6] Of course, mining activities will continue, with some predicting increasing export volumes during this time, levelling out in 2021.[7] Clearly, mining workforces will be adapting . Given repetitive tasks may be automated, this will involve a shift in the types of skills needed by mining companies, new training requirements, and a need for appropriate transitioning.

Change will not be limited work at the coal face, but also within the executive ranks which will need to respond to changing operations, crowdsourcing, the “gig economy”, millennial culture, and the differing ways which employees communicate with each other and with the company. Deloitte speculates this may lead to the need for greater collaboration between leaders of the different operational aspects of the business.

One notes that, while data networks of the future will embed in each aspect of the mine and supply chain, perhaps a similar level of inter-connectivity will be required from business leadership. Additionally, is it possible AI software can be usefully used to predict issues relevant to the workforce and assist leadership in early identification and management?

Implementing the Big Ideas

Rome wasn’t built in a day, and neither will any digital mine. Big change is unlikely to happen overnight, particularly in risk-averse industries such as mining. Rather, Deloitte suggests the following phrase be adopted “Think Big, Start Small, Scale Fast”.[8] In this incremental way, the project to implement digital transformation is scoped, tested in a safe environment, improved and (once proven) scaled-up.

This gives implementation a practical grounding: miners will “get on solving real problems” first, and using this experience to work towards the bigger picture.[9]

It will therefore be key in this process to define the business’ goals and its strategies for achieving them, to ensure than any digital transformation will serve these ends.