About Data analytics for benchmarking process control performance

Facilitators: Associate Professor Mohsen Yahyaei; Dr Francisco Reyes; Dr Gordon Forbes
Cost:  [all prices in AUD and exclude GST]
            Online - Option 1 - $2500 / Option 2 - $2000
            In person - Option 1 - $3000 / Option 2 - $2500
            Students - 50% discount
Delivery:  In person (Brisbane) and Online options
Duration:  Option 1 - 3.5 hours per day over 5 days; Option 2 - 3.5 hours per day over 4 days

Free registration available for two students:  Open to Honours and HDR candidates. Candidates should submit 500 words to Dr Gordon Forbes by Wednesday 5 September, explaining how this course will assist them in their study and future careers. Email

Overview:  This short course will provide metallurgists and plant managers with a basic understanding of data analytics and tools that can be utilised for processing the plant data, to benchmark the performance of the process control and identify opportunities for improvement. The course targets explicitly, operational strategies that are critical drivers for performance improvement.

Participants of this short course will be able to conduct basic data cleaning and analysis of process data to calculate the stability of various operating units in a mineral processing circuit and identify gaps in process control strategies, using Python and Excel. A hands-on approach is taken when covering all the topics in this short course, with practical problems that participants should solve using the course's learnings.

Option 1 (Days 1-5)

  • Introduction to Python
  • As per Option 2

Option 2 (Days 2-5)

  • Introduction to data analytics
  • Basics of process control
  • Excel and Python for data analytics
  • Exploratory data analysis
  • Data cleaning in Excel and Python
  • Data processing for understanding performance
  • Understanding process stability indices
  • Calculating process stability indices in Excel and Python

Target Audience:

This short course is aimed at junior metallurgists,  senior metallurgists  plant managers and students at various levels. The prerequisites for attendees are engineering degrees and experience in metallurgical processes (comminution, flotation, dewatering, etc.) and knowledge of Microsoft Excel. Knowledge of Python programming language will be advantageous, but not required. Participants with no Python programming experience should enrol for the 5-day course which includes the module “Introduction to Python”.