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Using Automation to Optimise Mining’s Value Chain

In the mining industry, there is huge potential to optimise the entire value chain through automation. With the integration of AI and machine learning tools, the capabilities of automation can be extended, improving asset management, productivity, and visibility.

For example, combining IIoT sensing technology with AI-powered data analytics enhances asset management by continuously monitoring assets and equipment, and alerting operators to developing risks or maintenance issues. These predictive maintenance technologies can also estimate an asset’s lifespan and provide prescriptive maintenance measures.

Key fact: In the mining industry, around 63% of all maintenance is unnecessary. Extended automation ensures that maintenance is only carried out when it’s actually required

Advanced data analytics also leads to improved visibility across every stage of production. Using wireless sensors to collect information in real-time, and machine learning algorithms to analyse and turn it into actionable insights, automation technology can create a predictable production process, such as in the case of digital twin technology.

With the power to preempt events, operators can make more informed, powerful decisions that optimise resources, lower operational costs, minimise emissions, and streamline production.


  • Optimises the value chain

  • Increases productivity

  • Minimises operational costs

Learn more insights by browsing our resource centre and learn about digital transformation trends among metals and mining companies in the Axora Innovation Forecast, which surveyed 150 senior industry decision makers.

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