Keywords: Artificial intelligence, machine learning systems, and human machine systems
Abstract: Artificial Intelligence approaches are increasingly being used in mining, metallurgy, and geology to automate tasks, optimize processes, and improve decision-making. They can be used for a variety of applications, including mining operations and exploration, process optimization, and predicting geological hazards.

This workshop presents the fundamentals of dynamic neural networks, fuzzy-neural networks, and deep learning, as well as their applications to the design of autonomous systems and operations common in the mining industry. This workshop has two parts: - Part 1 focus on the methods for the deep learning of dynamic neural networks and fuzzy-neural networks. - Part 2 focus on the applications for the modeling, control and estimation of dynamical autonomous systems and operations in the mining and metallurgy industries.

Speaker: Dr. Antonio Moran Cardenas Doctor in Mechanical Systems Engineering, Tokyo, Japan, with more than 30 years developing solutions based on computational intelligence for diverse applications in industry, economics, and education. He has published in several renowned journals and conferences, and one of his coauthored papers received the Best Paper Award at an IEEE-USA Conference in 2018. Dr. Antonio Moran is also chairman of the APEC Engineer Peru Committee, an ABET international evaluator, and was president of the Robotic and Automation Society of IEEE-RAS, Peru Section (Best Society Award in 2014).

Keywords: Fault diagnosis, process monitoring
Abstract: Efficient event recognition and alarm management are essential for ensuring safety, reliability, and productivity in mining and metallurgical operations. Traditional monitoring systems often suffer from high false alarm rates and poor adaptability, leading to operational inefficiencies and increased risks.

This workshop introduces the fundamentals of V-nets, a powerful formalism for modeling complex event sequences in industrial environments. It also explores how artificial intelligence techniques can enhance fault detection, alarm prioritization, and predictive diagnostics in real-world processes.

This workshop is divided into two parts: - Part 1 focuses on the foundations of V-net modeling, discrete event sequences, and the principles of intelligent event recognition. - Part 2 explores practical applications of V-nets and AI methods for fault diagnosis, alarm system optimization, and predictive maintenance in mining and metallurgy.

Speaker: Dr. John William Vásquez Capacho Dr. John William Vásquez Capacho is a renowned expert in electronics, industrial automation, and fault diagnosis, with over 20 years of experience in both academia and industry. He holds a Ph.D. in Engineering from Universidad de los Andes (Colombia) and Université de Toulouse (France). His work focuses on mechatronics, robotics, and industrial system safety, with a strong emphasis on intelligent fault diagnosis. Currently a Senior Researcher and Peer Evaluator for Minciencias, he also serves as a professor at Universidad Industrial de Santander, where he leads impactful R&D+i projects that connect academia, industry, and government. In 2016, he received the Colombian Innovation Award from ECOPETROL–INNPULSA for his outstanding contributions to technological innovation.

Keywords: Fault diagnosis, process monitoring
Abstract: This workshop, divided into three lectures, will present key developments in the field of Fault-Tolerant Control (FTC), beginning with fundamental definitions and core challenges. The series will place particular emphasis on robustness considerations and highlight significant application domains.

Lecture 1: Principles of Model-Based Fault Monitoring and Fault-Tolerant Control (FTC). This lecture will cover: i) Architectures and classifications of FTC strategies ii) Definitions and concepts in Fault Detection and Diagnosis (FDD) iii) Design approaches: Active vs. Passive FTC iv) Representative FTC examples from the literature v) The role of Fault Detection and Isolation (FDI) in FTC systems vi) Fault estimation and the concept of bi-directional robustness in FTC

Lecture 2: Fault Monitoring in Open-Loop and Closed-Loop Systems – Robustness Challenges This session will explore how robustness impacts fault detection in both open- and closed-loop control systems, with attention to modeling uncertainties and system resilience.

Lecture 3: Integrated Design Approaches for Robust Fault-Tolerant Control The final lecture will focus on integrated FTC design methodologies that explicitly address robustness, offering strategies for unifying monitoring and control objectives in practical implementations.

Speaker: Dr Ron J. Patton

He graduated with BEng (E&EE), MEng (Control) and PhD (Control) degrees at the University of Sheffield UK (72, 74 & 80). He was lecturer at Sheffield Hallam (78-81), & York Universities (81-94), leaving York as Senior Lecturer to the Chair of Control & Intelligent Systems Engineering at Hull University in 1995, and is now Emeritus Professor. His life work includes mathematical modelling in biology, ship positioning, fault diagnosis and fault tolerant flight/satellite control, and fault tolerant control for marine energy systems, with GS record of 33167 citations. He was awarded IEEE Fellow in 2010, for contributions to ‘Robust Fault Diagnosis and Fault Tolerant Control’. Ron is founder member of the IFAC TC Safeprocess (since 1990), leading Hull Safeprocess ’97 and was TC chair (96-02). He has co-authored/ authored books on Fault Diagnosis, Fault Tolerant Control & Eigenstructure Assignment.

Keywords: Ore preparation, flotation, Control and optimization
Abstract: Mineral flotation is a multi-stage process that operates in interconnected circuits. For the past two decades, we have studied the impact of flotation circuits on both metallurgical performance and the economics of the mining industry. In this workshop, we will start with a brief introduction to flotation circuits. We will then explore how to design these circuits and examine the effects of stochastic and epistemic uncertainty on their design and performance. Finally, we will discuss how to identify bottlenecks and critical variables that can enhance the efficiency of these circuits. Our analysis will encompass both monometallic and polymetallic circuits.

Contents 1. Introduction to Flotation Circuits and Their Functionality. 2. Designing a Flotation Circuit Using Optimization Techniques.   3. Impact of Epistemic Uncertainty on Flotation Circuit Design.   4. Impact of Stochastic Uncertainty on Flotation Circuit Design.   5. Enhancing the Performance of Flotation Circuits. 6. Application of Techniques to Polymetallic Ores.

Speaker: Dr. Luis Cisternas holds a Ph.D. in Chemical Engineering from the University of Wisconsin-Madison (USA). Professor Cisternas has also served as a visiting professor at several institutions, including CAPEC at DTU in Denmark, Aalto University in Finland, IRME at the Université du Québec en Abitibi-Témiscamingue in Canada, and Wuhan University of Technology in China. His research focuses on developing systematic tools (computer-aided) and experimental methods to address issues within the mining industry. These issues can be categorized into several topics: modeling, design, and optimization of mineral processes, the use of seawater in mining, and froth flotation. Professor Cisternas serves as the Associate Editor of the Green and Smart Mining Engineering Journal (KeAi Publishing). He is also a member of the Editorial Boards of Mineral Processing and Extractive Metallurgy Review (Taylor & Francis), Minerals (MDPI), International Journal of Mining Science and Technology (Elsevier), and Minerals and Mineral Materials (OAE Publishing Inc). He has authored over 160 peer-reviewed journal articles listed in the Web of Science, more than 100 conference papers, over 35 book chapters, and nine books.