Asset Predictive Maintenance

Digital Mine - Digital Plant

Currently equipment must be inspected on site for condition and performance evaluation, which requires experts to be on location and undertake equipment maintenance when it may not be required or even worse may be too late and damage/leaks could have been avoided. The Asset Predictive Maintenance Application is able to predict and optimize against damage/leaks in Mining processes before they happen through the use of Big Data and AI.


The real-time decision making software platform: (1) ingests real-time data, (2) performs real time modelling to create a digital twin of the equipment; and (3) gives performance status, alerts, and predictions of both individual equipment the overall system to enable intelligent decisions and optimum asset performance.


Engineers can test various operational scenarios for training purposes in a process simulation environment. This is enabled through the creation of a digital twin to create a safe environment for testing which accurately replicates the variables present in the live operational process. This can also be done remotely through the creation of an ROC (Remote Operations Center).


Streamed data from the assets is ingested into Data from multiple sources and of multiple types is combined and run through data quality modules, and then is passed to a series of machine learning and first principle models to create new real time information as well as predicted future states, to enable decision making for optimum asset performance. Benefits are delivered from early warning of asset underperformance and failure and reduced site inspections.The application also provides a data input for future optimizations and stakeholder conversations. The application is unique in delivering benefits on its own whilst serving as the basis for more active control and optimization of assets.


  • Monitoring alerts, and recommendations for asset performance will lead to reduced field visits
  • Proactive failure prevention leading to reduced capital expenditure.
  • The application will also provide a data input for future optimizations and stakeholder conversations.


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