How to harness the power of virtual twins to deliver a sustainable future for mines

It has been a long time since ‘sustainability’ was seen as a simple and vague notion that a reluctant executive had to occasionally report on.

Today, mining companies know that sustainability means transforming their activities to ensure long-lasting and responsible governance of a resource and the surrounding environment, with our future generations in mind.

This transformation is a complex multi-dimensional topic that covers every aspect of a mining project, from exploration and the greenfield phase, through to extraction and finally the rehabilitated site. Companies now often also consider the end-use of their mined products and their impacts, from the early supply chain through to usage of the product up to its end of life. And a range of complex environmental, social and governance (ESG) issues are considered throughout the life of the project, ranging from water stewardship and waste management, through to energy and fuel choice, plant running time, workforce and more.

This multidisciplinary approach is a broad challenge for responsible mining companies. They need to make three smart choices to track the execution of their ESG commitments:

• Which promises (and associated KPIs) will they make to measure their contribution to a sustainable tomorrow?
• Which data will they collect to verify their performance?
• What modelling and analysis will they perform on these data to understand where they are, versus where they want to be?

To assist companies in this challenge, the most powerful tool is the digitalisation of their operations. So called ‘virtual twins’ can enable the future-proofing of mining activities, as they handle large amounts of data that can be used for sophisticated modelling, simulations and analytics.

What is a virtual twin?

A vitual twin is the digital copy of a system, informed with real world data, that allows the user to perform data analytics and simulations at any stage of the system’s lifecycle, and in any chosen configuration. It is usually enriched with artificial intelligence to smooth and accelerate the process and aid decision making.

From a holistic approach to big data across all phases of mine life

During pre-feasibility and feasibility phases, mining companies are responsible for gathering a lot of information and verifying it against economic calculations and regulatory compliance. During the design and planning of the mine, engineers need to include the rehabilitation of the site to align with relinquishment requirements. Processing plant engineers are always trying to optimise the process (recovery rate, co-product valorisation, water recirculation, waste dewatering, fines management, etc). The complexity of the process and the quantity of data require data analytics, as well as modelling and simulating capabilities. During operations, a key factor of an operation’s carbon footprint is the fleet powering choice (fossil fuel, natural gas or electric vehicle); being able to digitally supervise the entire fleet system brings automation and optimisation possibilities.

Many of these processes can have data in common (such as pre-mining water testing and rehabilitation water management; process waste disposal and closure waste management, etc) so having a single source of truth enables a high degree of reliability, integration and automation. A holistic virtual twin of the mine site can provide data on all these parameters and more.

From big data to standardisation

Collecting the data is one thing; storing and accessing it is another. Because of the extensive amount of data that can be captured, companies are encouraged to implement cloud-based ‘Big Data’ storage and computing capabilities. As these assets are remote, this approach allows the various site locations to access a single source of truth, which in turn facilitates a consistent, standardised approach to each process. Company leaders can supervise and update these methods and tools in one place, and roll these changes out to all their remote assets.

From standardisation to smart technologies

Once standardisation and a single source of truth have been established, integration and automation are enabled. These remote, integrated and automated systems can then be enriched with machine learning and artificial intelligence technologies to create a smart virtual twin of all the company's assets.

From smart technologies to a sustainable mining future

Adding smart technologies to create a powerful virtual twin provides visibility, transparency, accountability and robustness – i.e. the mine of the future.

Our recommended approach to build a fully integrated virtual twin is to assemble the following components:

• A systems engineering model of the company or its assets, highlighting its mission, its stakeholders, its lifecycle, and its operational environment to define the company’s transformation purpose.
• A data storage solution to collect the metrics in a single source of truth, in order to establish a baseline and to help leaders make decisions based on data.
• A 3D model of relevant assets to contextualise the data and provide understanding to the workforce.
• A simulation of the main processes to run ‘what if’ scenarios and prediction trends to ensure future robustness.
• Data analytics to reconcile ‘real’ and ‘virtual’ data and perform multi-parameter analysis to identify the most influential parameters. For example, to reduce a site’s carbon footprint, it may be more efficient to reduce the employees’ commute (less FIFO, more local workers), or change the fleet to electric vehicles.

Digitalisation is a powerful ally of businesses transformation to build a future mining experience based on trust. Sustainable mining generates the commodities the population needs with minimal waste, increases the production yield, reuses water, produces its own energy and monitors autonomous vehicles and equipment to perform operations without exposing humans to danger, while offering broad-based stakeholder transparency.

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