Title: Phenomenological simulation of a graphite flotation circuit
Topic: The main objective of this project is to adapt and calibrate simulation models for unitary flotation operations of a graphite concentration circuit. These tasks require the use of MATLAB programming software and the determination of model parameters using the least squares method.
Co-direction: Jocelyn Bouchard (research director)
Start in the IAM program: 04/2023
End in the IAM program: 08/2023
Email: farah.fersi.1@ulaval.ca
Title: Valorization of oil analysis data from mining equipment.
Topic: Mines use oil analysis to determine the state of degradation and wear of their machinery components. The aim of this research is to exploit a database of oil analyses from a Canadian mine, in an attempt to establish a model for predicting oil degradation.
Co-direction: Michel Gamache (research director), Bruno Agard (co-director) and Antoine Tahan (co-director).
Start in the IAM program: 09/2022
End in the IAM program: 06/2024
Summer School: 2023 presentation ( .pdf )
Email: daniel.ley@polymtl.ca
Title: Blockchain, an innovative way of decentralizing decision making in the mining sector
Topic: The objective of this research is to evaluate the effectiveness of the Blockchain in the traceability of minerals in a supply chain. This decentralization solution could lead to a more robust data sharing between the different actors of a mining supply chain.
Co-direction: Christophe Danjou (research director) and Michel Gamache (co-director)
Start in the IAM program: 09/2022
End in the IAM program: 08/2024
Summer School: 2023 presentation ( .pdf )
Email: julien.pons@polymtl.ca
Title: Dynamic time prediction of underground mining equipment activities
Topic: The main objective of this master's project is to develop a method to reliably predict the activity times of underground mining equipment based on operational parameters and sensor data. To this end, we will first try to clean and format the available raw data. We will then use the formatted data to develop a machine-learning algorithm capable of reliably predicting the duration of various mining activities.
Co-direction: Robert Pellerin (research director) and Michel Gamache (co-director)
Start in the IAM program: 09/2022
End in the IAM program: 08/2024
Summer School: 2023 presentation ( .pdf )
Email: victor.simon@polymtl.ca
Title: Digital Twins in underground mines
Topic: This study focused on the development of a digital twin for the underground mining industry, as well as addressing associated challenges and limitations. As part of the Digital Twin architecture, optimization, evaluation, and simulation decision support tools will be defined as modules, taking into account the unique features and requirements of underground mining operations to create an interoperable, functional, and scalable architecture. The resulting architecture will allow end-to-end integration and remote controllability of digital twin technologies in the mining industry with a long-term vision that can be customized and developed for case-specific configurations.
Co-direction: Jean-Marc Frayret (research director) and Michel Gamache (co-director)
Start in the IAM program: 09/2022
Summer School: 2023 presentation, 2024 scientific poster ( .pdf )
Email: mostafa.dadkhah@polymtl.ca
Title: Advanced control of mineralurgical processes - Geometallurgical and mineralogical aspects
Topic: The main objective of this PhD project is to develop a control strategy for a grinding and flotation circuit based on mineral liberation data. This will be achieved through the following sub-objectives. The first one is the reconciliation of high frequency and low resolution liberation measurements (LIBS) with low frequency and high resolution (SEM/EDS). The second is the addition of variables such as chemical composition and density to the current liberation model to considerate changes in raw materials. Finally, the addition of reagents to the flotation kinetic model allows generalizing it, thus limiting the number of empirical parameters and increasing the control possibilities.
Co-direction: Jocelyn Bouchard (research director) and Éric Poulin (co-director)
Start in the IAM program: 09/2022
Summer School: 2023 presentation ( .pdf ), 2024 scientific poster ( .pdf )
Email: david-alexandre.desrosiers.1@ulaval.ca
Title: Guiding the digital transformation of existing underground mines
Topic: The main objective of this PhD is to facilitate the digital transformation of existing underground mines. To do so, we will first determine what the smart mine is in order to know where the mining industry is heading. Then, we will determine a model to identify initiatives to be implemented and finally we will develop a model to build a portfolio of digital transformation projects.
Co-direction: Robert Pellerin (research director) and Michel Gamache (co-director)
Start in the IAM program: 09/2022
Summer School: 2023 presentation ( .pdf )
Email: marine.echternach-jaubert@polymtl.ca
Title: Artificial intelligence approaches to geological data characterization.
Topic: The main objective of this PhD is to use artificial intelligence to characterize geological data. Mining and geological data require specific processing because they often exhibit a spatially dependent structure. In our research, we combine machine learning inference methods with spatial interpolation and variography techniques to take into account geological features and spatial structure. Our methods will be applied to estimate the blastability index (BI) in undrilled areas using the BI calculated in boreholes.
Co-direction: Michel Gamache (research director), Richard Labib (co-director) and Jean-françois Plante (co-director)
Start in the IAM program: 09/2022
Summer School: 2023 presentation, 2024 scientific poster ( .pdf )
Email: yakin-2.hajlaoui@polymtl.ca
Title: Development of a digital twin for an underground mine ventilation system
Topic: Digital twin technology has gained considerable importance in recent years, with diverse applications spanning several sectors. The aim of this project is to develop a digital twin of an underground mine ventilator by developing a three-dimensional model of the gallery, ventilator and its accessories. The model needs to take into account all aspects of ventilation, such as ventilation routes, dimensions, access doors, exhaust outlets and surrounding conditions.
Co-direction: Hatem Mrad (research director)
Start in the IAM program: 05/2024
End in the IAM program: 08/2024
Email: SaifEddine.BenYoussef@uqat.ca
Title: Artificial intelligence prediction of the evolution of the overall equipment effectivness (OEE) of production machines
Topic: The aim of this project is to harness and consolidate the flow of data made available by Industrie 4.0 tools to define and train predictive models. The model selected will be trained to recognize situations leading to a deterioration in performance or, on the contrary, situations enabling optimal use and operation of production resources.
Co-direction: Souheil-Antoine Tahan (research director)
Start in the IAM program: 05/2024
End in the IAM program: 07/2024
Email: hiba.tlili.1@ens.etsmtl.ca
Title: Development of a perfectly mixed reactor simulation and analysis of anode signals in primary aluminum production
Topic: A Simulink model of a perfectly mixed reactor for solid flotation will be developed. In a second part, a Matlab script for analyzing signal data will be written, which should then enable parts of the analyzed solid to be identified.
Co-direction: Jocelyn Bouchard (research director) and Carl Duchesne (co-director)
Start in the IAM program: 05/2024
End in the IAM program: 08/2024
Email: benoit.turgeon.7@ulaval.ca
Title: Used oil data analysis
Topic: Mines use oil analysis to determine the state of degradation and wear of their machinery components. The aim of this research is to exploit a database of oil analyses from a Canadian mine in an attempt to establish a model for predicting oil degradation.
Co-direction: Michel Gamache (research director), Bruno Agard (co-director) and Antoine Tahan (co-director)
Start in the IAM program: 03/2024
End in the IAM program: 07/2024
Email: mariem.zrigua@polymtl.ca
Title: Analysis of mining equipment maintenance data
Topic:
Co-direction: Bruno Agard (research director), Antoine Tahan (co-director) and Michel Gamache (co-director)
Start in the IAM program: 01/2024
Email: martin.cuenot@polymtl.ca
Title: Risks associated with the use of autonomous vehicles in Quebec mines
Topic: The use of autonomous vehicles in Quebec mines will be a major step forward for technology and the mining industry. The aim of this ambitious project is to reduce human-vehicle interactions in the mines, and thus avoid work-related incidents/accidents. Nevertheless, this innovation could be accompanied by risks already existing in the sector, as well as new risks not yet identified by health and safety professionals. Thus, the aim of our study is to identify all the probable risks (unforeseen system failure, remote hacking, etc.) that could arise from the use of these vehicles in mines. Our work is organized in two parts:
- the first consists of defining the different levels of autonomous vehicles and their characteristics through a review of the literature and current developments;
- as for the second, it aims to identify the risks associated with the use of these vehicles and to propose preventive/protective measures while respecting the nine principles of prevention.
The results of our work could serve as a basis for health and safety professionals as soon as this project is implemented.
Co-direction: Firdaous Sekkay (research director) and Michel Gamache (co-director)
Start in the IAM program: 01/2024
Summer School: 2024 presentation ( .pdf )
Email: gaston-deferre.dingong-hen@polymtl.ca
Title: Development of a Connected Mining Pump
Topic: Our initiative aims to design and develop a connected, intelligent mining pump in partnership with Technosub, based in Rouyn-Noranda, Quebec, Canada. This revolutionary pump will be equipped with sensors enabling early detection of anomalies for immediate intervention, thus preventing the spread and accumulation of problems. The connected aspect of this reinvented pump will greatly simplify the task of preventive and curative maintenance by identifying likely sources of malfunction. This connectivity will also enable the creation of a comprehensive, real-time database on the pump's operating status, facilitating monitoring, maintenance and decision-making to optimize the performance and reliability of mining equipment.
The ultimate aim of this innovative project is to significantly improve operational efficiency in the mining sector by reducing downtime, anticipating failures and ensuring maintenance based on accurate, real-time data.
Co-direction: Hatem Mrad (research director) and Hela Soussi (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: Mohaned.Djedidi@uqat.ca
Title: Study of structural reliability through intelligent data analysis and implementation of a failure prediction model for rotating mining equipment
Topic: This research project is part of the transition to Industry 4.0 and focuses on improving the reliability of rotating equipment in the mining industry. Using advanced data analysis techniques, such as machine learning and intelligent data analysis, we collect and analyze real-time sensor, maintenance and operational data to anticipate potential failures. The main objective is to develop a failure prediction model based on historical data. By identifying early warning signals of failure, we can implement more effective preventive maintenance, reducing unplanned shutdown times and improving worker safety. In summary, this research aims to combine advanced data analysis and predictive modeling to increase the reliability and availability of rotating equipment in the mining industry, contributing to more efficient operations.
Co-direction: Hatem Mrad (research director)
Start in the IAM program: 09/2023
Summer School: 2023 presentation ( .pdf ), 2024 scientific poster ( .pdf )
Email: Nour.Elkhenin@uqat.ca
Title: Phenomenological simulation and predictive control of a graphite flotation circuit
Topic: The project is divided into two distinct parts. The first concerns a phenomenological simulation of primary/residue flotation, involving the assembly of a simulation model of unit operations, a test campaign at demonstration plant, as well as calibration, model validation and performance evaluation. The second part focuses on the predictive control of primary flotation and tailings flotation. It includes characterization of the effect of collector dosing on sulfide flotation kinetics, design and validation of predictive control systems, and evaluation of system performance, particularly in terms of mill product size and reduction of reagent dosing for tailings flotation.
Co-direction: Jocelyn Bouchard (research director) and Éric Poulin (co-director)
Start in the IAM program: 01/2024
Summer School: 2024 presentation ( .pdf )
Email: farah.fersi.1@ulaval.ca
Title: Development of a techno-economic analysis tool for mobile underground mining equipment
Topic: The goal of the research is to develop algorithms for detecting anomalies and calculating failure probabilities. The algorithms will then be used to develop a visualization and decision-support tool for the status of underground equipment, based on reliability and economics.
Co-direction: Antoine Tahan (research director), Bruno Agard (co-director) and Michel Gamache (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation
Email: david.lauzon.3@ens.etsmtl.ca
Title: Development of a Control Interface for Underground Drilling and Ground Support Bolting
Topic: The project aims to develop a control interface for the operation of an arm used in drilling and bolting ground support in underground tunnels. The interface will consider the arm's design elements, including input/output, components, mobility, operational sequence, and tunnel geometry. The end goal is to create a conceptual model for both planning the ground support operation and remote monitoring. Expertise in database programming, engineering, and automation is required for this endeavor.
Co-direction: Hatem Mrad (research director) and Chahid Ahabchane (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: Aynaz.MohammadiAghbash@uqat.ca
Title: Development of decision-aid tools for predicting mechanized/autonomous arm failure during support operations in underground mining galleries
Topic: The mining industry faces a major challenge in optimizing its complex operations through real-time monitoring of equipment status and integrated management of operational data. Our project involves developing decision-support tools for the intelligent prediction of failures during support processes in underground mining galleries. The approach consists of collecting and analyzing historical data relating to past failures, operational parameters (gallery geometry, drilling plan, aeration, etc.); drilling-bolting technology (swellex, rebar, shotcrete, mesh type, etc.); sensor data from motorized components (hydraulic, electrical and pneumatic). Subsequently, we are developing predictive regression and classification models such as XG-Boost and Support Vector Machines (SVM), aimed at anticipating problems such as excessive wear and mechanical malfunctions of the mechanized/autonomous arm; Neural networks and k-means clustering models, for detecting anomalies in operating data, and predicting control system faults. The results of this project will improve the availability and reliability of the mechanized/autonomous ground support arm, while reducing operational costs and accident risks for mining companies.
Co-direction: Hatem Mrad (research director) et Chahid Ahabchane (co-director)
Start in the IAM program: 09/2023
End in the IAM program: 03/2025
Summer School: 2023 presentation ( .pdf ), 2024 scientific poster ( .pdf )
Email: SteveLandry.PANDOTIOKOU@uqat.ca
Title: Simulation and control of a graphite grinding process
Topic: The project consists in establishing a control strategy to optimize the size of the grinding product of a graphite plant. The aim is to reduce the effect of geometallurgical deposit variability on plant profitability. To achieve this, a dynamic simulation model must first be built. As the latter is made up of phenomenological models, it will have to be calibrated and then validated. Data reconciliation will also be carried out to improve the calibration procedure.
Co-direction: Jocelyn Bouchard (research director) and Éric Poulin (co-director)
Start in the IAM program: 09/2023
Summer School: 2023 presentation ( .pdf ), 2024 scientific poster ( .pdf )
Email: thomas.picard-beaudoin.1@ulaval.ca
Title: Structural and normative optimization of the hub/blade system: Towards AMCA certification of an axial mining fan
Topic: The project consists in optimizing the hub/blade system according to normative, technico-economic and damage criteria, as well as developing an instrumented test bench consisting of sensors, modern measuring instruments and data collection and analysis systems using artificial intelligence. This test bench will be developed in compliance with AMCA standards, with a view to fan certification. This project is in partnership with Hyperflo, a company based in Rouyn-Noranda, Quebec, which has been developing and distributing the CHINOOK type of mining axial fan for several decades. The aim of this project is to reduce the company's fan manufacturing costs through optimization, and to open up new international markets through certification.
Co-direction: Hatem Mrad (research director) and Guyh Dituba Ngoma (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: Wilfrid.OYONGGBETNKOM@uqat.ca
Title: LIBS tests and development of a measurement protocol
Topic: The main goal of this project is to set up an LIBS measurement protocol for determining gold concentration. This involves carrying out a series of tests on samples to measure gold concentration under various conditions. These samples will also be subjected to XRF analysis, which will contribute to the development of a database for assessing the potential of combined LIBS-XRF use for ore sorting. Following this, statistical modelling will be used to distinguish latent signatures or a prediction of gold content, enabling ore to be distinguished from sterile rock.
Co-direction: Jocelyn Bouchard (research director) and Carl Duchesne (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: hamdiat.sakande.1@ulaval.ca
Title: Development of a mechanical failure detection model for an ore conveyor drive system
Topic: In a context where Industry 4.0 is redefining predictive maintenance standards, our approach is based on the smart use of artificial intelligence. The main objective of this master's project is to optimize mining operations, reduce intervention costs and improve equipment safety. Our quest is based on the analysis and valorization of data from connected sensors and conveyor drive system maintenance records, offering significant advances for an innovative research study focused on the prediction of mechanical failures in rotating equipment within mining industries.
To this end, predictive neural network models are being developed to anticipate mechanical failures at conveyor level, thereby reducing unplanned shutdowns.
Co-direction: Hatem Mrad (research director)
Start in the IAM program: 09/2023
End in the IAM program: 11/2024
Summer School: 2023 presentation ( .pdf ), 2024 scientific poster ( .pdf )
Email: MohamedChadi.Yakoubi@uqat.ca
Title: Economic and environmental optimization for open pit mines
Topic: Mines produce a lot of waste and may impact the environment. An approach to mitigate the impact is to backfill the waste and tailing materials into the pit. Today, this is done sequentially after the mine operation is complete; however, it may be possible to optimize the process of backfilling, for example, by looking at opportunities to start it earlier and for optimizing the sequence of backfilling to control geotechnical/chemical properties of the material. This thesis aims for modelling the backfilling process and optimizing it so that the environmental impact is reduced at the minimum cost for the mining company.
Co-direction: Nelson Morales (research director) and Carlos Ovalle (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: parisa.akbari@polymtl.ca
Title: Intelligent optimization of microgrids. Raglan Mine case study
Topic: This research will focus on the use of machine learning, deep learning and other algorithms to optimize the microgrid. Optimization will maximize certain energy resources such as wind generation and minimize factors such as the cost of electricity and the reduction of environmental pollution. Another objective will be to enable a high penetration of renewable energies in the microgrid, thus decarbonizing the mine.
Co-direction: Adrian Ilinca (research director) and Daniel Rousse (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: joseph-kantole.basakayi.1@ens.etsmtl.ca
Title: Improving the fatigue strength of axial mining fan blades
Topic: Today's fans are facing several types of failure, particularly those caused by vibration, fatigue and excessive mechanical stress, leading to significant drops in performance and economic losses. To this end, the main objective of this PhD project is to set up a co-simulation approach, integrating damage laws for fatigue fault prediction, to detect their initiation, monitor their propagation and evaluate the service life of axial mining fans. The aim is to improve the latter's performance and establish health indexes that will subsequently be used to help the partner in decision-making when designing and adjusting fans before and after delivery.
Co-direction: Hatem Mrad (research director) and Slim Ben Elechi (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: Mariem.BENhASSEN@uqat.ca
Title: Ore sorting circuits
Topic: The main objective of this thesis is to develop dynamic simulation models for LIBS-based ore crushing and sorting equipment. These numerical models will be structured in coherence with those of the current crushing circuit simulation platform and for mineral liberation. These reproduce the macroscopic behavior of mineral particles by means of equations (differential or algebraic) describing the transformation (fragmentation or mineral separation) incorporated in population balances for ideal reactor assemblies.
Co-direction: Jocelyn Bouchard (research director) and Éric Poulin (co-director)
Start in the IAM program: 09/2023
Summer School: 2023 presentation ( .pdf ), 2024 scientific poster ( .pdf )
Email: iman.meziane.1@ulaval.ca
Title: Optimization in underground mine design and scheduling considering environmental variables
Topic: Currently, the process of design and scheduling of stopes in underground mining is a process that takes into account fixed values for certain parameters. One of them are the environmental variables (EVs). This approach neglects several aspects such as ore chemistry, which can lead to the generation of acid drainage. This thesis aims to integrate environmental variables into the underground mine design and scheduling process, so that economic value is maximized but at the same time environmental risks, such as acid mine drainage, are minimized.
Co-direction: Nelson Morales (research director) and Michel Gamache (co-director)
Start in the IAM program: 09/2023
Summer School: 2024 presentation ( .pdf )
Email: santiago-xavier.valencia-morales@polymtl.ca
Title: Determinants of investor decision-making in an ESG context
Topic: Quality of ESG information disclosed by companies in the mining sector and analysis of investor perception
Co-direction: Nathalie de Marcellis-Warin (research director)
Start in the IAM program: 02/2024
Email: daniel.kouloukoui@polymtl.ca
Title: Simulation model for column flotation
Topic: The goal of the project is to design a Simulink simulation of a flotation column. This requires the development of flotation cell equations, as well as the use of Matlab software.
Co-direction: Jocelyn Bouchard (research director)
Start in the IAM program: 09/2024
End in the IAM program: 12/2024
Email: jeanne.dufresne.1@ulaval.ca
Title: Characterization and valorization of waste rock from the graphite mine at Lac des Îles, Quebec
Topic: The main objective of the project is to valorize mine waste rock as a raw material for the manufacture of cat litter, in collaboration with the companies Northerm Graphite and Intersand. The aim is to assess the geochemical behavior of waste rock and develop optimized cat litter recipes. The study is part of a drive to promote sustainable, environmentally-friendly operations with low waste production, while integrating economic practices.
I'm focusing on the first part of the project, which consists of accurately characterizing mine tailings in the field using portable, non-destructive and deterministic technologies. These technologies include pXRF for geochemical analysis, hyperspectral imaging for mineralogical composition, and carbonate staining for carbonate identification.
Laboratory results will be validated on samples, using techniques such as ICP, inorganic and total carbon measurements, as well as mineralogical examinations by XRD and electron microscopy, to validate the on-site characterization protocol and ensure compliance with waste rock reclamation criteria.
Co-direction: Isabelle Demers (research director) and Marc Lagault (co-director)
Start in the IAM program: 09/2024
Summer School:
Email: MohamedMalik.HASSAID@uqat.ca
Title: Development of a prototype ore grain distribution system
Topic: The aim of this project is to design and develop an ore grain distribution system in collaboration with Goldex. This system must be able to distribute ores on a surface in a more uniform, homogeneous and optimized way, in order to guarantee rapid sample preparation and validate elemental analysis using LIBS (Laser-Induced Breakdown Spectroscopy) technology. The aim is to obtain a more precise qualitative and quantitative identification of the ore, while reducing the time required for this analysis, with a view to optimizing the choice of ore processing parameters according to their chemical composition.
Co-direction: Hatem Mrad (research director) and Mohamed Slim Abes (co-director)
Start in the IAM program: 09/2024
Summer School:
Email: Aymen.Jleli@uqat.ca
Title: Prediction and prevention of premature wear of SAG Mills coatings
Topic: Semi-Autogenous Grinding Mills are ball mills widely used for grinding hard ores. Their efficiency depends on the performance of their linings, which are subject to heavy wear due to abrasion, impact load and friction. The consequences of excessive wear include reduced production, increased energy consumption, product contamination and failures that can cause costly production shutdowns. In this context, measuring wear on coatings is crucial for monitoring their condition and planning maintenance.
Various techniques exist, such as thickness gauges, ultrasound, radiography and modeling, to ensure this measurement.
The main objective of this project is to monitor and predict premature wear of SAG Mills linings. This can be achieved by applying novel numerical and experimental techniques for instrumentation, data collection and evaluation.
Co-direction: Hatem Mrad (research director)
Start in the IAM program: 09/2024
Summer School:
Email: Eya.Kharrat@uqat.ca
Title: Intelligent discrete finite element modeling of turbomachinery fatigue
Topic:
Co-direction: Hatem Mrad (research director) and Haykel Marouani (co-director)
Start in the IAM program: 01/2025
Email: tawfik.ajbouni@uqat.ca
Title: Development of a digital twin for a mining ventilation system
Topic: This project aims to develop a digital twin for a ventilation system used in an underground mining environment. The main objective is to create a numerical tool capable of simulating, predicting and optimizing system performance in real time, reducing energy costs while improving safety and operational efficiency. The approach includes parametric CFD modeling to analyze fluid-structure interactions, the creation of reduced models (ROMs) to accelerate calculations, and their integration in the form of functional units (FMUs). The resulting digital twin offers advanced simulation and prediction capabilities, laying the foundations for future industrial applications such as predictive maintenance and decarbonization of mining activities.
Co-direction: Hatem Mrad (research director) and Haykel Marouani (co-director)
Start in the IAM program: 01/2025
Master's/Doctorate transfer: 05/2025
Email: SaifEddine.BenYoussef@uqat.ca
Title: Assessment of the mechanical behavior of mine waste rock open-pit backfill using field monitoring, numerical modeling and back-analyses
Topic: Managing mining waste materials is a major challenge in the global mining industry due to their potential failure and environmental impact. Waste rock, a byproduct without economic value, must be disposed of safely from both geotechnical and geochemical perspectives. My project focuses on investigating the geotechnical stability of high waste rock piles (WRP) backfilled into pits, aiming to create high piles within the old pit rather than spreading waste over vast land areas. This is achieved through numerical modeling, real-time monitoring, and backanalysis of the material's mechanical parameters based on field data.
At the Canadian Malartic Gold Mine, regular deformation monitoring of WRPs provides valuable data, enabling the project to go beyond simple modeling. Each model can be validated with field observations, allowing for accurate recalibration of parameters. This research is pioneering in its integration of Real-Geometry 3D numerical modeling with iterative back analysis, incorporating monitoring data at each step of the construction process. The existing literature on hard rock mine waste is limited, and this project aims to significantly improve waste rock management practices while advancing the scientific understanding of the mechanical behavior of soil-like materials in mining contexts.
Co-direction: Carlos Ovalle (research director)
Start in the IAM program: 09/2024
Summer School:
Email: zahra.jalalichi@polymtl.ca
Title: Optimizing multi-pit mine planning by integrating the supply chain of an open-pit iron ore operation
Topic: Traditional mine planning optimization methods have proved their worth, but are based solely on deterministic models, where all input data are known from the outset. These methods focus more on single orebody estimation techniques and do not take into account many variables that may be environmental or technical, thus increasing the economic risk associated with the mining project.
Mining large deposits such as iron ore remains highly complex in terms of efficient supply chain management, especially in the context of multi-pit mining operations, generally covering large areas. One solution would be to use mathematical models to efficiently plan trains, stockpiles and ships, and integrate them into the mining optimization process.
Optimization research into multi-pit mine planning and open-pit supply chain optimization has gained momentum, but previous studies have often treated the two problems in isolation. Also, the integration of reserve, price and demand uncertainties still remains a complex problem. The aim of my research is therefore to combine the two optimization approaches in an iron ore mining context, in order to improve the entire mining chain from extraction to delivery of the marketable product.
Co-direction: Nelson Morales (research director)
Start in the IAM program: 01/2025
Email: makele-mabika.elde-divel@polymtl.ca
Title: Prediction and management of ore truck trajectory conflicts in underground mines
Topic: The ramp at an underground mine is bidirectional, but too narrow for ore haul trucks to pass each other. Today, painful lane conflicts occur regularly: downhill trucks often have to back up to park upstream and give way to uphill trucks, which has a significant impact on productivity and increases fuel consumption.
My project aims to minimize the impact of these conflicts through a three-step approach.
First, I build a set of analytical fleet management rules to optimize intersections for several common configurations.
Second, I use data from vehicle location tags to build a digital twin of the mine. Through simulation, I can directly compare the daily productivity of a mine using my set of traffic rules with that of a conventional mine.
Finally, I use this digital twin and a machine learning model to predict impending trajectory conflicts, identify those that don't match any of my analytical rules, and, if necessary, simulate different possible reconfigurations of the fleet to find the one that minimizes the impact of the conflict. This reconfiguration is applied to the fleet in real time.
The overall goal is to build an expert underground fleet management system capable of dynamically optimizing vehicle movements in all operational situations.
Co-direction: Robert Pellerin (research director) and Michel Gamache (co-director)
Start in the IAM program: 09/2024
Summer School:
Email: victor.simon@polymtl.ca
