The focus on digital mining, even though not a new concept, has to do with the need to ensure an uptick in a mining company’s overall performance.
Definition and scope
Terms such as ‘digitalisation’, digital transformation and analytics, when used without clear definition, can lead to confusion within an organisation, and, in turn, can result in misguided and poorly scoped projects. ‘Digital’ (and its variants) or the process of moving to “digital mining” is “the use of electronic tools, systems, devices and resources that generate, store or process data to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business.”
Digital mining: The evolution
Digital mining is not new; it has been with us for over half a century. Over the last few decades, the mining sector has embraced the introduction of new technologies, such as mainframe and personal computing, processing plant control systems, Despatch, Global Positioning Systems (GPS), mobile broadband, cheap sensors and data storage, through to cloud computing. Significant benefits have already been realised from digital mining.
Crowdsourcing: The introduction of global brainstorming to mining enabled cost reduction while speeding up the data sifting process to identify possible Greenfield deposits.
Mine planning and optimisation tools: Better results have been achieved through remote operations centres that allow companies to monitor activities happening hundreds of miles away via satellite link.
In the digital world, the desired end state for mining and metals companies has been generally accepted. This future is characterised as one where decision-makers (either human or automated) rapidly optimise decisions to maximize some objectives (e.g., cash flow, NPV) through the efficient use of resources (eg, ore body, assets, labour), subject to some constraints, like market, regulatory, ethical. This decision-making process strives to make the most effective decisions through the most efficient use of the available resources. Various aspects of this vision are already playing out in differing degrees of aspiration and scale. These developments are maturing in parallel with an increase in commentary highlighting the opportunities offered by analytics, big data, Internet of Things and machine learning — terms that are used liberally and often with little definition. Against this backdrop, the mining and metals companies are looking for a sober assessment of genuine potential from digital transformation along with the implementation pathways, which take advantage of the opportunities while avoiding common pitfalls.
The pathway for digital mining enterprises
Productivity remains the number one operational risk in the mining sector particularly in the bulk commodities. Despite recent improvements in cost reduction and labour productivity, asset productivity continues to lag, and this is the next area miners need to focus on. To address the productivity gap, miners need to focus on improving the management of variability in their organisation.
The manufacturing industry is the best example of a sector recognised as a leader in asset productivity as measured by overall equipment efficiency (OEE). By adopting a manufacturing mindset, miners can better manage variability and hence improve productivity.
There are three key elements to this:
Digital alignment to the productivity agenda (digital as the enabler)
A market-to-mine approach to the business (end-to-end)
Leadership and culture to support elimination of loss (zero-loss focus culture). Digital can enable new ways to drive productivity, manage the variability challenges of the sector and pursue commercial excellence.
Some examples of what mining and metals companies can achieve with the right focus on digital include:
Optimising plans and productivity rates across any operation and managing variability under any conditions: Digital will enable this through combining detailed ore body data with equipment operational and maintenance data, in a real-time environment, to produce alternative operating plans and the ability to refine these plans for variability.
Enhancing asset availability and reliability: A move to digitally enabled predictive maintenance would allow for the extension of maintenance windows, reduced component and labour costs, and the minimisation of costly breakdown events. Further, once the effective maintenance practices are standardised, the introduction of robotic process automation (RPA) and schedule optimisation tools is possible.
Understanding true end-to-end capability and systems bottlenecks, and supporting loss elimination: This is fundamental to the manufacturing mindset.
Increasing agility and responsiveness to changes in market factors, such as demand, freight rates and customers’ buying behaviour trends: This would optimise shipping and scheduling to reduce demurrage, maximise rail and port utilisation, and also enable miners to capture spot markets and price premiums via sales contracted at different points of the value chain.
Source: Ernst & Young