Mineral Processing plants now are operated much differently to how they were 5 years ago. The rate of change for digitising process control, decision making and analytics is growing rapidly and the capacity to leverage new methods and technologies is becoming the differentiating factor for highly successful operations. Ernst and Young has identified digital effectiveness as one of the top ten risks for the minerals industry and this is especially true in minerals processing.

MinAssist is a champion of the benefits that a well structured program to leverage digital solutions can have for a minerals processing operations or development project. We believe that through use of tools such as digital twins, advanced analytics, machine learning and artificial intelligence mineral processing operations can get more value from their data and drive significant productivity benefits.

What is Digital Mineral Processing?

Digital Mineral Processing is an all encompassing term that captures various facets of digital transformation within a minerals processing operation. A minerals processing plant is incredibly data rich, with high frequency data captured at almost every point. This data may be stored within a Historian system but until now, linking that data to support decision making and shift the process to more predictive operation has only rarely been done.

Many operations are now moving towards implementation of Digital Twins, which use operational data in a dynamic process simulation to predict changes in behaviour. This can be supported by advanced data analytics, machine learning, deep learning and artificial intelligence to link data sets and identify value opportunities.

Application of these tools has been growing in exploration, resource modelling, mine planning and geometallurgy but has lagged behind in minerals processing. Development of a structured digital transformation strategy can allow a minerals processing operations to generate better links with mine planning, optimise efficiencies and implement predictive maintenance strategies to reduce downtime and improve productivity.

MinAssist’s development and analytics capabilities

MinAssist provides unique capabilities to support operations on their digital transformation journey. Combining our experience in geometallurgy with deep mineralogy and minerals processing expertise we are ideally positioned to work with a range of analytics providers to tailor a fit for purpose program that is focused on generating the greatest value from data available from a minerals processing plant.

We have developed tools to help link geometallurgical models and mine planning with process behaviour using operational mineralogy. This allows us to generate a ‘whole of operation’ view to decision making, that means decisions focus on maximising the value of product produced, rather than just optimisation of individual parts of the operation.

How can we help you?

  1. Digital Twin
  2. Benchmarking
  3. Deep Learning
  4. Machine Learning

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