CIM Webinar

Optimization in Mineral Processing: Remote Implementation during COVID-19 Times

with Dr. Sohail Nazari
Director of Digital Transformation
Andritz Automation

April 9, 2020 | 2:00 – 2:30 PM EST

Watch the recording now


This talk introduces a dynamic solution for optimizing mineral processing in real time. The proposed technology is a combination of model predictive controller, optimization methods and real-time digital twin for mineral processing. We will discuss how to implement such projects remotely and what is the immediate expected improvement results.

The implemented advanced control strategy consists of two layers in hierarchical structure. The lower layer objective is to stabilize the process stabilization using model based predictive controller (MPC) technique. The unique MPC used in this layer is called BrainWave™ chosen for its robustness, convergence and delay handling; furthermore, the developed platform offers stable and repeatable solution and has short implementation time. The upper layer is a supervisory control, which sends the preferred process operation points to the lower layer to drive the process towards optimal performance. The goal of this layer is to optimize the process targets, as well as making decision. To increase process performance, automatic ore characteristic adaptations are implemented in this layer. A digital twin of comminution area is built in the second layer that runs amongst the process in parallel. By communicating, the process data in real time, a virtual densitometer is built that is being used in our advance process control strategy.

This control strategy has been developed, tested and implemented in various areas of a mineral processing plant. The targets for implementing advance process control are usually increased throughput, decrease energy consumption and variability reduction in particle size distribution. Overall, the results showed in different mine sites are increase throughput between 2 and 5%, specific energy consumption reduction about 15% and process variability reduction up to 60%.

Who should attend and why?

Mill Managers, Operation Superintendents, Innovation Officers, Process Control Superintendents, Metallurgists

About the presenter

Dr. Sohail Nazari, PhD, P.Eng. is the Director of Digital Transformation for ANDRITZ AUTOMATION and has designed and implemented asset condition monitoring analytics, remote monitoring architecture and advanced process control strategies for the mining, oil and gas and automobile industries. Dr. Nazari is responsible for Andritz Automation’s business development in the Mining and mineral processing Industry and was instrumental in winning first prize at Goldcorp’s 2019 #DisruptMining innovation competition. Dr. Nazari has been helping Industry lift automation to a higher level through “Digital Transformation”, including digital twins, advanced data analytics, artificial intelligent (AI) controls with integrated machine-learning and optimizing technologies. He is also a volunteer Presenter on Science and Technology for the Engineers and Geoscientists of British Columbia.