Panel Discussion – August 17, 2021

Battle on Advances in Materials Manufacturing

Special invited Panel discussion include:

  • Mathieu Brochu, McGill University Canada
  • Priti Wanjara, National Research Council Canada
  • John Campbell, University of Birmingham, UK.


Mathieu Brochu

McGill University

About Mathieu Brochu

Mathieu Brochu

Priti Wanjara

National Research Council Canada

About Priti Wanjara

John Campbell

University of Birmingham, UK.

About John Campbell

Plenary Session - August 18, 2021

Digital Transformation in Mining and Metallurgical Industrial Complexes

Ores are becoming extremely variable with mineralogy and hardness disturbing the integrated crushing, grinding, flotation, and thickening processes. The current grinding and flotation sensors provide large amounts of data for process optimization. To augment the operational knowledge for proactive actions for improving the performance of the grinding and flotation circuits, we need to add the right process knowledge context and operational modes.

Without these proper operational contexts in place, the results are unmanaged downtime, process troubles, maintenance interruptions, and unmet production schedules. By measuring operational modes and managing these unproductive times (trouble times), people can find new ways of improving profitability and efficiency of the plant. The inFORMAtion (inSHAPEtion) created by the real-time analytics enables us to calculate the metal recovery in real time and to develop predictive analytic models to secure the best operating conditions based on the type of ore currently mined. Using the latest tools and cloud computing enables the creation of new workflows and collaboration between mining, concentrator plants, and the enterprise, including services providers.

Machine learning pervades our culture in a multitude of ways, from medical diagnosis and data management to speech synthesis and search engines. The novel approach of using machine-learning techniques coupled with dynamic process models in grinding, such as Dynamill™ and Dynaflote™, a new operational integrated grinding model is realized and implemented.

These days of remote operations utilizing the capability to integrate mining operations from drilling to product delivery is an industry boon. With mines in inconvenient, out-of-the-way locations, people can now work from home, remotely supporting operations and staying safe and healthy during these challenging times. Today, subject matter experts (SMEs) can increase productivity by developing predictive models to classify the operating conditions owing to large variations in ores, catching the hidden production, energy, and water losses by ore type and unmeasured disturbances. People call this a “follow the money” strategy, the ability to survive and adapt to these unforeseen forcing factors affecting the communities and support.

The application of a digital plan twin to mining, mineral processing and extractive metallurgical process using advanced analytics tools is presented here.


Osvaldo Bascur

Principal Digital Transformation, OSB Digital, LLC., USA
Consultant fellow, Seeq Advanced Analytics, USA

Dr. Osvaldo A. Bascur is a Chemical Engineer and Metallurgical Engineer at the University of Concepción. PhD in Metallurgical Engineering from the University of Utah, Salt Lake City, Utah. Worked with Duval Corporation with Process Control Engineer; He was Manager of the Continuous Improvement Group (now Freeport McMoRan) in Tucson, Arizona and then as Director of the Process Control and Optimization Group for Pennzoil in Houston Texas. He currently works at OSB Digital, LLC as Principal advising clients on their Digital Transformation in Industrial Complexes. He is Consultant fellow for Seeq Advanced Analytics which take the real time series data to build predictive analytics models. The key is to avoid trespassing operational and equipment constraints depending on the mineral ore types and enabling to maximize the metal recoveries. Recently, he has designed a template for the Digital Transformation of Process Plants. This template transforms data into Information for use by people, systems and enables the modeling of industrial processes. It facilitates the use of new predictive modeling and artificial intelligence tools. He developed a Blue Print for the integration of operational data for the optimization of industrial plants. In 2013, he received the most prestigious Antoine Gaudin Award from the Society of Mining and Metallurgical Engineers, Dr. Bascur has published more than 95 technical works, two books and several chapters of engineering books were published. In addition, Dr. Bascur is a member of the following engineering companies: SME, AIST, AIChE, IFAC MMM and IMPC.