MATLAB and Simulink Seminars

Advanced Automation in Mining with MATLAB Series

As miners and mine suppliers are continuing to improve their operations, more and more sensors are introduced in the workflow.  But how do we make sense of all the data presented to us? What insights can we draw from them? And do we even trust the information presented to us?

When companies enter the data analytics space, they need to realise that their most valuable asset is the experience of its employees – the subject matter experts. Your employees can tell you if a sensor is operating correctly, or if it introduced an error because dirt build-up is causing the signal to flatline with some wobble.

In this mining webinar series you will hear examples of how mining companies are successfully employing sensor information, and learn best practices on how you can leverage these insights. The common denominator for all these cases is that sensor information is used within the context of the system that it monitors.  As such, each example uses more than just one sensor and combines this with knowledge about the system, obtained from subject matter experts and math. Use cases presented cover:

  • Pulp chemistry monitoring
  • Geological exploration
  • Predictive maintenance
  • Developing and using autonomous systems
Date & Time Session Session  
12 August
12:00 - 1:00 PM
Application of the Pulp Chemistry Monitor at a Copper Mine in Australia Christopher Greet, Magotteaux View OnDemand
19 August
12:00 - 1:00 PM
Predicting Boiler Trips with Machine Learning

John Atherfold, Opti-Num Solutions and Christopher van der Berg, John Thompson

View OnDemand
26 August
12:00 - 1:00 PM
Optimising exploration while minimizing environmental impact Peter Brady, MathWorks View OnDemand
2 September
12:00 - 1:00 PM
Developing Autonomous Mining Systems Alex Shin & Ruth-Anne Marchant, MathWorks View OnDemand