April Tech Talk - How engineers and geos are using digital twin technology for mine-to-mill and pit-to-port.

How engineers and geologists are using machine learning for digital mine-to-mill and pit-to-port value chain optimisation.

About this event

Through a series of international case studies, this presentation will demonstrate how digital twin machine learning software sustains the benefits of mine-to-mill and pit-to-port.

Specifically, these case studies will show how mines are using machine learning to implement digital twin models to;

a) add variables to the block model e.g. geometallurgy, product quality and materials handling rates

b) simulate drill and blast designs using historical performance and;

c) dynamically optimise plant set points in near real-time using best operator performance and dynamically responding to changes in ore characteristics.

Raw mining data is by integrated, automatically corrected and calibrated using purpose-built data valorisation algorithms.

Whilst ore tracking, machine learning and mathematical optimisation are the technologies enabling digital twin value chain optimisation, this presentation will also discuss success factors for long-term implementation of digital mine-to-mill and pit-to-port software.

Speaker/s

Dr. Penny Stewart

Mining Engineer and Founder and CEO of PETRA Data Science

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Science. She is a Fellow of the Australian Academy of Technical Sciences and Engineering and holds a Queensland 1st Class Mine Managers’ Certificate of Competency. Whilst working in underground and open pit mines across Australia she gained firsthand knowledge of how geological uncertainty impacts mining professionals. In 2015, Penny established PETRA, guided by the hypothesis that integrating hundreds of millions of tonnes of actual mine performance data into site-specific models provides the most accurate methods for mine productivity and efficiency estimation and optimisation. Today, PETRA’s AI-powered mining software empowers mining professionals to enhance their understanding of orebody knowledge and optimize the entire mining value chain.