Professional Development Network – Training Courses

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Optimising your Mining Operations

Location:                Perth

Venue:                    Fraser Suites, 10 Adelaide Terrace

Date:                       Friday 23 November 2018

Time:                       7.30am – 5.30pm

A day of insight into the latest developments in mineral processing and how to effectively optimise your mining operations.  In conjunction with Orway Mineral Consulting, Blue Cube Systems and Jamieson Group.


  • Multi-Stream Inline Mineral & Elemental Analysis
  • Advanced Process Control
  • Milling Optimisation
  • Cyanide Management and Control
  • Operator Training and Intervention


for Simulation & Optimisation


Location:                Perth

Date:                        Q1 2019 (subject to EOI)

Duration:                 3 day course

Requirements:      Own laptop required for this course

Simulation Modelling is the process of creating a digital twin of a physical model to predicts its performance in the real world.

The purpose of simulation modelling (in the context of mineral processing operations) is to identify how to change the operation of a plant to increase the recovery of minerals for an optimum profit.  i.e. should particles be ground finer to increase liberation recognising that energy costs increase.

Further Course Details

Course Detail

Day 1 – Foundations

  • Data structures for simulation
  • Discussion on current simulation methods
  • Mathematical optimisation
  • Probability-based methods – including a discussion on the difference between probability, statistics and pseudo-statistics
  • Information theory
  • Deductive Inference and Plausible inference
  • The difference between statistical inference and probabilistic inference
  • Flow sheeting using Visio
  • Relational databases for mineral processing

Day 2 – Mass Balancing

  • Mass Balancing 1D data
  • Mass Balancing 2D data
  • Mass Balancing 3D data – creating the data structure for simulation
  • The difference between least squares mass balancing and probabilistic mass balancing
  • Error analysis
  • The role of standard deviations in least squares mass balancing

Plausible Inference – estimating unmeasured data

Day 3 – Simulation

  • Flowchart-based simulation
  • Design simulators compared to existing-operation simulators
  • Modelling frameworks: Data-driven models, hypothesised models, Information-based models
  • Information-based machine learning algorithms.
  • Discussion – the role of Artificial Intelligence in simulation
  • Model adaption
  • Using online data as the basis for machine learning algorithms
  • Discussion – Steady state models versus dynamic models, and the role of control systems with steady state simulation.
  • Specifying operational parameters.
  • Customised interfaces for simulation
  • Hierarchical modelling
  • Manual Optimisation

Automated optimisation

Who Should Attend
This course is for professionals.  The course does require participants to be able to think logically and structually.   The course is well-suited to people from engineering and science backgrounds and equivalent.  The course does not require strong mathematical skills, but does require people to be comfortable with using ‘models’. This will be explained in more detail in the course.

To Book

Contact Paula Jarvis on email or call 08 9240 4357

To Book

Contact Paula Jarvis on email or call 08 9240 4357

Process IQ Pty Ltd

Unit 1 / 23 Gibberd Road Balcatta, WA 6021 Western Australia
Tel: +61 (0) 8 9240 4357
Fax: +61 (0) 8 6316 0486