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AI and the digital mine

AI and the Digital Mine

Big data, analytics and AI are transforming our world. They will have a similar impact on the mining industry.

AusBiz Magazine - June/July 2019

Words: Darren Baguley


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In its recent report, ‘The top 10 business risks facing mining and metals 2019–2020‘, consultancy firm Ernst & Young (EY) placed digital effectiveness as the number-two business risk facing mining companies, down one place from its position last year. 

According to the report, although Australian mining companies lead the world in automation, they’re well off the pace when it comes to the digital transformation gathering force in other industries. According to EY, “a recent poll of over 600 mining and metals executives revealed that a significant 37 per cent of management have little or no knowledge of the digital landscape. The stark reality is that digital is the key to achieving productivity and margin improvements. Miners are making significant strides in applying digital solutions to single issues or bottlenecks. But it is only when miners apply these solutions across the entire value chain to create a digital mine that they can truly transform and emerge as the dominant players in the market.”

Like any fundamental transformation, transitioning to a digital supply network (DSN) will take time. It cannot be done overnight, however industries that have already begun their digital transformation journey have left clear signposts for those following. The transition to the digital mine of the future begins almost invariably with a focus on core mining processes, working towards the goal of automating mining operations and digitising those assets. The technologies driving this step change include autonomous vehicles, wearable technology, three-dimensional (3D) printing, drones and a plethora of Internet of Things (IoT) sensors all connected in real time through a pervasive network. 

While this level of automation and interconnectedness will greatly increase safety and improve profitability through efficiency and reduced maintenance costs, the real value will be found in the data these systems generate and capture. Nevertheless, when it comes to big data, remember what they say: data is not information, information is not knowledge, knowledge is not understanding, understanding is not wisdom. 

Nowhere is this truism more correct than in the mining industry. To truly create the digital mine, information must flow from node to node of the digital supply network through a series of iterative steps known as the physical-digital-physical (PDP) loop. In a PDP loop, data is first captured in the physical world through sensors and warehouse in enterprise resource planning (ERP) or similar systems – essentially creating a digital record. The captured data is analysed and useful insights are gleaned, informing actions and decision-making in the physical world. 

In the report, ‘Tracking the trends 2019: The top 10 issues transforming the future of mining‘, consultancy Deloitte contends, “Although most mining companies have the first stage of the PDP loop in place, and many have the second, far fewer are yet able to harness the last, most important stage – the ability to act on the data they have analysed. In fact, some research shows that miners may use less than 1 per cent of the data they collect from their equipment. 

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“Before the industry can use the supply network to fuel growth, rather than merely driving incremental improvements, a cultural shift must take place – one that empowers executives to make decisions by relying on data outputs rather than on gut experience. This is ultimately the nirvana of the DSN – the ability to leverage advanced algorithms, AI and machine learning to turn data into insights that allow companies to reduce their capital expenditures, respond to changing project requirements on the fly and optimise mine planning to integrate real-time changes.”

To truly unlock this value, companies will have to completely rethink the way they use information. Creating an information layer that aggregates data in multiple timelines from across the digital supply network will enable mining companies to use data-driven analytics to inform planning, control and decision-making.

One of the many challenges this data-gathering presents, however, is its sheer volume. The world currently creates 2.5 quintillion bytes of data every day, and as the IoT becomes ever more pervasive this number will increase exponentially. For a human to draw insight from this data unaided is akin to drinking from a firehose, so mining organisations are tackling the challenge with the aid of analytics and artificial intelligence (AI).

For the purposes of definition, AI can be thought of as machines that are able to perform tasks that up until now required human intelligence. As AI becomes a reality, three stages of development are becoming apparent. Stage one is AI that digitises processes but still requires human assistance and interpretation – robotic process automation, for example. In stage two AI uses machine learning to augment human decision-making. Machine learning ‘trains’ algorithms with large amounts of data and the algorithm responds without being explicitly programmed. Finally, in stage three AI decides and executes autonomously in response to an overarching directive, eg a fully autonomous haul truck or dragline.  

Many mining organisations, especially those below the top tier of miners, are only working at stage one AI, or not working with AI at all. Leading mining companies have been at stage one for some time now and are now moving towards stage two, where AI drives cognitive insights which are used to augment human decision-making. In a case study cited by Deloitte, “A global miner’s haul trucks that operate within the pit were often observed queuing at the crusher and shovels. Analysis of truck fleet data revealed an uneven distribution of haul trucks between shovels. This resulted in longer cycle times and truck bunching. Through the adoption of machine learning and Internet of Things (IoT), truck cycle efficiency was improved, resulting in greater capital utilisation and increased annual material movement.”

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To succeed in transitioning to a digital supply chain which fully uses the capacity of AI to transform operations, miners will need to think big, start small and scale fast. Thinking big means getting clear on the vision, strategy and desired business outcomes for the future. Starting small means executing on the strategy by designing and delivering in sprints. Scaling fast means developers work quickly to get to minimum viable product, rapidly scale up and embed successful products operationally before moving on to the next one.

According to Deloitte China’s Mining and Metals Leader, Kevin Xu, “The mining sector is at the earliest stages of building a digital supply network – which is both a risk and an opportunity. Those organisations that crack the code around fully interlinking their supply chains can gain the end-to-end visibility they need to enhance their asset utilisation, operational efficiency and productivity – realising hard dollar savings as a result.”

Australia was the third country in the world after the UK and the USA to have an operational computer, an early lead which subsequent generations squandered. Top-tier Australian mining companies are leading or level with the rest of the world when it comes to AI and digitally transforming the mining supply chain. Hopefully we’ll learn from history.

 

FAST FACTS

1951

In 1951, CSIR Mk.1 (later CSIRAC) was the first computer in the world to play music at the first computer conference held in Australia.

 2.5 quintillion

The world currently creates 2.5 quintillion bytes of data every day.


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