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Enhancing Mineral Processing with AI, Digital Twins and Computer Vision

Webinar Details

This presentation discusses the transformative impact of Artificial Intelligence and Machine Learning (AI/ML) combined with Digital Twin technologies in reshaping Advanced Process Control (APC), Asset Performance Management (APM), Process Engineering, and Smart Sensors. By integrating these advanced technologies, industries can achieve enhanced operational efficiency, reduce unplanned downtimes, and optimize resource utilization. Case studies illustrating successful implementations of predictive modeling, real-time analytics, and simulation techniques will be examined. The discussion will also highlight how AI/ML-driven insights foster proactive maintenance strategies and informed decision-making, ultimately driving sustainability and productivity within industrial operations.

Learning Objectives:

Understand the effective integration of AI and ML with Digital Twin technologies to enhance mineral processing.
Learn strategies to improve operational efficiency via Advanced Process Control (APC) and Asset Performance Management (APM).
Emphasize the role of real-time analytics and predictive modeling in facilitating proactive maintenance and informed decision-making.
Explore successful real-world implementations of AI/ML and Digital Twin technologies to identify practical applications.

Recognize how these technologies drive productivity in mineral processing operations.

Meet the speakers

Rodrigo Toro, Solutions Offering Leader, MMM, Honeywell Process Automation

Rodrigo Toro is an expert in automatic control, with a Master of Science degree from the Polytechnic University of Catalonia in Barcelona, Spain. He also holds a Bachelor of Science degree in Electronic Engineering from the Federico Santa María Technical University in Valparaíso, Chile. During his 16 years at Honeywell, he’s been working on topics such as dynamic systems modeling, identification and simulation, optimal/predictive control, and data science.

Rodrigo has extensive experience in data-driven solutions and project management. As a Data Science Manager at Honeywell Chile S.A., he led a diverse team of engineers, data scientists, and developers to deliver advanced process control, simulation, data science, advanced analytics, and information application projects.

Cesar Bravo, AI Solutions Director, Honeywell Process Automation

Cesar Bravo is AI Solutions Director at Honeywell Process Automation. He has over 24 years of experience setting the strategy and overseeing research, development, and implementation of digital solutions for process industries.

He has performed various leadership roles in Research and Development, Product Management, and Consulting at industry-leading Oil & Gas services and operator companies. Cesar is a recognized thought leader and author of more than 30 technical papers about Digital Transformation, the Digital Oil Field, and the application of Artificial Intelligence and optimization methods in industrial production processes.

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