12th International Copper Conference
Proceedings of the Extraction 2025 Meeting & Exhibition, Volume I
- 2025
- Book
- Editors
- The Metallurgy and Materials Society of CIM
- The Society for Mining, Metallurgy & Exploration
- The Minerals, Metals & Materials Society
- Publisher
- Springer Nature Switzerland
About this book
Copper 2025 is the first of three volumes devoted to the Copper 2025 + Ni-Co 2025 + Cross-Cutting Symposia of the Extraction 2025 Meeting & Exhibition joint conference, held November 16–20, 2025, at the Sheraton Grand at Wild Horse Pass in Phoenix, Arizona, USA. The success of the Copper Conference is thanks to the efforts of eight leading international societies (IIMCh, GDMB, MMIJ, TMS, SME, MetSoc of CIM, NFSOC, and SAIMM), who continue to bring forth symposia of the highest quality on mining, mineral processing, pyrometallurgy, hydrometallurgy, electrometallurgy, process control, and instrumentation. The Extraction 2025 volumes collect important research examining new developments in foundational extractive metallurgy topics and techniques. They also offer new programming designed to share the latest research and insights on emerging technologies and issues that are shaping the global extractive metallurgy industry.
The Extraction 2025 Meeting & Exhibition was jointly organized by The Metallurgy and Materials Society (MetSoc) of the Canadian Institute of Mining, Metallurgy and Petroleum (CIM), the Society for Mining, Metallurgy & Exploration (SME), and The Minerals, Metals & Materials Society (TMS).
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Table of Contents
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Process Control and Optimization
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Frontmatter
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Developing Copper Analyses Application Using EDXFR Benchtop Instrument
Hussain Al HalwachiThis chapter delves into the innovative use of Energy Dispersive X-Ray Fluorescence (EDXRF) for the non-destructive analysis of ancient copper objects, with a particular focus on artifacts from the Dilmun civilization. The study highlights the modification of calibration curves to improve the accuracy and reliability of measurements, a crucial advancement for the field of archaeometry. The chapter provides a detailed account of the analytical procedure using the Epsilon 1-Meso instrument, including the addition of certified standards to enhance calibration lines. It also discusses the challenges and solutions related to sample preparation, such as the removal of patina to ensure accurate bulk composition analysis. The results reveal significant findings about the chemical composition of Dilmun copper objects, including the presence of trace elements like nickel, arsenic, and tin. The chapter concludes with a discussion on the broader implications of these findings for understanding ancient metallurgy and the cultural significance of the artifacts. This comprehensive approach makes the chapter a valuable resource for professionals seeking to apply advanced analytical techniques in archaeological research.AI Generated
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AbstractObtaining accurate copper analyses is crucial step in the copper filed. Analyses are very important to characterize ancient copper objects, control the copper production and to certify the final copper products. Epsilon 1 Meso EDXRF is a movable benchtop instrument with a spot camera to focus on the required analysis spot. The instrument is equipped with Omnian standard less software capable of measuring most of the elements. The instrument’s calibration was modified to measure different types of ancient copper objects with high accuracy. -
Suggested Guidelines for Inspection, Dispositioning, and Acceptance of No. 1 and No. 2 Copper Scrap: Practice and Practical Considerations
Philip ElbazThis chapter delves into the complexities of inspecting and accepting No. 1 and No. 2 copper scrap, highlighting the importance of quality control in the scrap metal industry. It discusses the challenges of managing suppliers and ensuring the quality of scrap copper, with a focus on reducing contamination and improving inspection methods. The text shares practical experiences and methods that have been successfully implemented to reduce contamination rates and improve the overall quality of copper scrap. It also explores the use of hand-held XRFs and magnets as essential tools for quality control, and the importance of involving all personnel in the quality control process. The chapter concludes with recommendations for supplier management, customizing raw materials specifications, and developing visual inspection skills. By implementing these strategies, professionals can enhance their quality control practices and ensure the delivery of high-quality copper scrap.AI Generated
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Abstract#1 and #2 Copper scrap, along with Bare Bright, are highly traded grades of copper scrap. There are widely used definitions for these grades, and newsletters regularly publish market price estimates. These grades allow some imperfections but still set boundaries to distinguish them from lower grades. Imperfections, while permissible, can be exceedingly difficult to quantify for acceptance criteria. Judgement and discretion are unavoidable. Opportunities exist for inconsistencies and differences of opinion between buyers and sellers. Unquantified and subjective criteria also make it challenging to establish standard operating procedures. Some acceptance criteria within published scrap grades are absolute and binary. Other criteria are qualitative, with no quantitative parameters. In addition, representative sampling of #1 and #2 Copper is difficult to achieve. Loads are often not homogenous, nor are they required to be. Commercially prepared scrap may involve significant human intervention and therefore cannot be presumed to be randomized, nor is scrap commercially required to be randomized. For these reasons, evaluation of these grades of copper scrap often rests on rejection rather than acceptance, i.e., finding the non-conforming item. In practice, disposition practices are also subject to discretion. The aims of this presentation are to recommend practices, procedures and criteria that will promote consistent operation, better enable training, and promote predictability and understanding between buyers and sellers. -
Digitalizing Conveyed Copper Ore Flows to Improve Mill Feed Quality and Process Control
H. KurthThis chapter explores the implementation of real-time measurement technologies in copper ore processing to enhance mill feed quality and process control. It delves into three key technologies: Prompt Gamma Neutron Activation Analysis (PGNAA) for multi-elemental measurement, microwave transmission for moisture content analysis, and 3D infrared cameras for particle size distribution (PSD) measurement. The text discusses the benefits of these technologies, including improved ore quality, reduced variability, and enhanced process efficiency. It also highlights successful case studies and the importance of integrating multi-sensor data for comprehensive process optimization. The conclusion emphasizes the value of real-time data in improving mining and processing operations, reducing environmental impact, and increasing revenues.AI Generated
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AbstractAs average copper ore grades decline and processing costs increase, the mining industry is implementing proven technologies to improve sustainability: reducing energy, water, and reagent consumption, tailings generation and GHG emissions. Mining companies have realized value in sensing ore quality in real time to better understand quality variability implications on processing and assess potential benefits through improved control. Real time measurement to digitalize conveyed flow quality using proven technologies has been implemented with minimal risk. High performance Prompt Gamma Neutron Activation Analysis (PGNAA) has been used successfully in the minerals sector for representative, continuous, real time multi-elemental measurement of conveyed flows in many commodities. High performance PGNAA has been successfully applied in bulk ore sorting where 20% + increases in ore grade have been recorded and 5–20% of the mined material being rejected as waste after primary crushing, reducing GHG emissions up to 20% with only minor metal losses. Multi-elemental data is used to improve ore blending, waste diversion from plant feed, feed forward control to process operators, ore reconciliation and metal accounting. Additional technologies include real time free moisture measurement using transmission microwaves, and particle size distribution analysis using next-gen 3D infrared camera technology. Synergies from multi-sensor data allow a greater understanding of material characteristics that remain directly unmeasurable in conveyed flows, such as ore hardness. Installations at multiple sites have proven the measurement capabilities and the paper outlines results at various copper operations. Methods for risk reduction in assessing and implementing the technology are discussed. -
Enhancing Operational Efficiency Through Advanced Process Control Health Check Solution
Seyedhamidreza Khatibi, Farah Kaboodanian, Jorge Poblete, Jakob JanzenThis chapter explores the critical role of Advanced Process Control (APC) systems in enhancing operational efficiency in mining operations. It highlights the challenges faced by classic regulatory controllers and the advantages of APC techniques like Model Predictive Control (MPC) and fuzzy expert control. The text presents a comprehensive APC health check methodology, including the classification of control loops by criticality, data analysis of current control strategies, and on-site fine-tuning services. A detailed case study of a major mining operation in Chile demonstrates the tangible benefits of APC health checks, such as improved process stability, reduced variability, and increased productivity. The chapter also discusses the importance of addressing issues in lower control levels to enhance APC performance and provides a roadmap for further optimization. Key topics include the classification of control loops, data analysis for identifying opportunities, and the implementation of MPC for better control of multivariable processes. The conclusion emphasizes the value of APC health checks in driving continuous operational enhancement in mining operations.AI Generated
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AbstractThe comprehensive Advanced Process Control (APC) health check, structured in three phases, significantly boosts operational autonomy and efficiency in mining operations. This process begins with the classification of control loops based on operational criticality, studying the existing process control strategy, and executing a detailed control loop performance analysis of basic layer controls (PID loops) of circuits using the Hatch Solution. The second stage includes an in-depth performance analysis of the existing strategy, including current APC applications (Model predictive control, fuzzy logic, etc.), and provides a comparative study with and without APC, benchmarking it against industry standards. This analysis identifies areas for further improvement, confirms the functionality or non-adherence of the APC strategy, and proposes a roadmap with quantified improvement opportunities for further optimizing the circuits via tuning of existing APC applications or additional implementation of advanced controls like Model predictive control. The final stage involves fine-tuning services on identified unsatisfactory basic layer control loops and potentially implementing or fine-tuning advanced control loops. The successful completion of this three-stage APC health check solution maximizes the utilization of control loop diagnostic tools, sustains operational performance, maintains the benefits of the APC scheme, and identifies opportunities for further optimization of circuits. A recent case study, which will be covered in this work, demonstrates how Hatch effectively leveraged its integrated team of experts in process, control systems, and APC to deploy this APC health check solution for a mining operation in South America. This deployment delivered insightful outcomes, finding new opportunities and maximizing the benefits of APC schemes for Grinding & Regrinding (SAG and conventional grinding), and Flotation areas. This case study serves as a testament to the potential of Hatch’s APC solutions in enhancing operational efficiency. -
Digital Transformation of Smelters–Exploring the Benefits of Optimization and Generative AI on Operational Planning and Scheduling
Yael Valdez-Navarro, M. A. H. Zahid, Ahmadreza Azadi, Yale ZhangThis chapter delves into the digital transformation of smelters, focusing on the benefits of optimization and generative AI in operational planning and scheduling. It highlights the challenges faced by the metals industry, such as depleting ore grades and the need for enhanced operational efficiency. The text introduces the Hatch Smelter Optimizer, a cloud-based tool that leverages advanced analytics and AI to generate optimal production schedules. A case study demonstrates the successful implementation of this tool in an African PGM smelter, resulting in significant improvements in throughput and productivity. The chapter also discusses the integration of a Vision AI framework, which uses machine vision algorithms to track and analyze smelter activities in real-time. This framework enhances operational visibility, safety, and traceability, providing actionable insights for operators. The conclusion emphasizes the importance of digital transformation in the metals industry and the need for continuous innovation to meet future demands.AI Generated
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AbstractSmelter production scheduling presents numerous challenges due to the complex, interconnected, and dynamic nature of smelter operations. In this paper, we explore the transformative impact of digital technologies on smelter operations, with a specific focus on the benefits derived from optimized operational schedules. By investigating the current and future challenges inherent in smelting processes, the paper emphasizes the pivotal role of advanced mathematical optimization techniques, real-time data analytics, and vision AI in orchestrating efficient and sustainable smelter activities. We illustrate with an industrial case study how a digitally enabled scheduling ecosystem, enhanced by vision AI for precise monitoring of critical activities such as ladle movements, crane operations, and furnace tapping events, can significantly improve efficiency, reduce environmental impact, and unlock new levels of adaptability in the face of operational complexities. The proposed optimization framework synchronizes the activities of furnace, cranes, and converter aisle, while adhering to process and environmental constraints, resulting in a minimization of molten material idle time by up to 50%. The integration of computer vision ensures high-resolution data capture and continuous performance feedback, driving real-time adjustments and enhancing operational oversight. -
Mining Magic: From First Principles to AI Enhancing the Engineering Experience
Mariana SandinThe chapter delves into the critical challenges facing the mining industry, including declining ore grades, knowledge loss due to an aging workforce, and the urgent need for sustainability. It explores how traditional engineering methods are being augmented by AI and digital technologies to enhance operational efficiency and productivity. The text presents compelling case studies from Boliden’s Gerpenberg Mill and Lumina Copper’s Caserones mine, demonstrating significant improvements in grinding efficiency, copper recovery, and water recovery through AI-driven solutions. Additionally, it discusses the role of Generative AI in capturing and transferring institutional knowledge, reducing problem-solving time, and improving decision-making processes. The chapter concludes with a vision for the future, emphasizing the importance of AI adoption in achieving net-zero goals and securing a sustainable future for the mining industry.AI Generated
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AbstractMining is at a crossroads, facing challenges like lower ore grades, knowledge loss, net-zero goals, and the energy transition. Engineers are the heroes in this story, using everything from keen hearing to detect bearing failures, to first-principles engineering for calculating dilution factors, to statistical analysis for process control, and now, AI to enhance human capabilities and speed up data analysis.This presentation will cover the journey from traditional techniques to cutting-edge AI solutions, highlighting how industry leaders are overcoming different operational challenges. The potential of AI in mining is exciting, and real-world examples of how it is transforming the lives of plant professionals will be discussed here. -
Case Report—Use of MaxiFlox® R Series to Enhance the Water Recovery in a Copper Sulphide Process Circuit
Jamiel Muhor, Martin Nieto, Daan LoohuysThis chapter explores the use of MaxiFlox® R Series chemistry to enhance water recovery in a copper sulphide process circuit. The case study focuses on the challenges of water scarcity and the need for improved tailings thickener performance. Through laboratory tests and plant trials, MaxiFlox® 530R was identified as the optimal flocculant, resulting in a significant increase in underflow density and water recovery. The text delves into the process description, issues identified, and the solutions implemented, including the reduction in flocculant dose rate and the use of advanced co-polymer flocculants. The results demonstrate a 4% absolute increase in underflow density, an 18.4% increase in water recovery, and a 20% reduction in flocculant dose rate. The chapter concludes with the benefits realized by the client, highlighting the effectiveness of tailored chemistry and professional services in optimizing water recovery and reducing operational costs.AI Generated
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AbstractThe mining industry faces many challenges and issues relating to the use of water and the impact of exploration, extraction, and residue management on the environment. These include minimizing reagent consumption and maximizing mineral recovery by improving the rate and degree to which solid–liquid separation takes place in thickening (McKetta John in Unit operations handbook unit 2—mechanical separation and materials handling) applications. MaxiFlox® R Series chemistry combined with can deliver an increase in water recovery in a copper processing plant. This can be achieved through a combination of reduced dosage and increased underflow density in the tailings thickener whilst maintaining the yield stress of the underflow. Dose can also be controlled through an advanced control unit called OptiFlox® SRt. Process water is recovered in a thickener from the tailings of a flotation process. Make-up water is pumped to the site and can be a costly resource. The performance of the tailings thickener can be improved through the selection of a flocculant. MaxiFlox® R series range is not conventional flocculant. They deliver higher underflow density and more robust floccules and are effective for many mineral ore types. The flocs formed are more tolerant to solids concentration and shear variations, and the dense particle shape allows for faster consolidation, higher underflow density, and lower yield stress. These changes are apparent in bench-top cylinder tests, a guide used prior to field trials. SciDev currently has a field case study from a Copper Sulphide process in Australia and is working with clients globally, with results from this work in 2025 to be included in the presentation. -
Quantification of Demand-Side Flexibility in Copper Ore Mineral Processing Operations: Enabling the Sustainable Energy Transition
Mohsin Sajjad, Arda Simsek, Karl Gerald van den Boogaart, Ashak Mahmud Parvez, Jorge TorrubiaThis chapter explores the quantification of demand-side flexibility in copper ore mineral processing operations, focusing on optimizing energy consumption and integrating renewable energy sources. The study models a conceptual copper ore mineral processing plant using HSC Sim software, with process data derived from real-world mining operations. Key topics include the methodology of modeling the plant, the energy consumption calculations for various processes, and the evaluation of flexibility approaches such as scaling and pausing operations. The research highlights the significant energy consumption in comminution processes, particularly ball mills, and presents flexibility parameters that cover technical and environmental aspects. Results demonstrate that adjusting energy consumption in response to renewable energy availability can enhance sustainability and operational efficiency. The study concludes with a framework for integrating renewable energy with industrial operations, emphasizing the need for further research on economic trade-offs and scalability.AI Generated
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AbstractThe transition to renewable energy sources introduces variability in energy availability, necessitating adaptive energy consumption strategies for energy-intensive industries like copper mineral processing. Copper demand is predicted to rise substantially due to the expansion of electric vehicles, renewable energy infrastructure, and digital technologies. The current study quantifies the demand-side flexibility potential of copper ore mineral processing operations to align energy use with renewable supply fluctuations. Using HSC Sim software, a simulated plant modeled on real-world operations demonstrated that scaling (adjusting throughput) and pausing (temporarily halting units) reduced energy consumption by 25–50% in comminution stages (e.g., ball mills saved 17,666 kW at 29% downscaling). Life cycle assessment via openLCA software revealed a global warming potential of 0.78 kg CO2 eq/kg for concentrate production. Key challenges include stockpile management and operational continuity, but results highlight that integrating these flexibility strategies enables 40–100 h operational windows aligned with intermittent renewable energy availability. This work provides actionable insights for reducing the carbon footprint of copper mineral processing while supporting renewable energy integration in future energy systems. -
Automated Irrigation of Leaching Piles with Clean and Renewable Energy
Belén NuñezThis chapter explores the development and implementation of an automated irrigation system for leaching piles in Chile, focusing on enhancing safety, efficiency, and sustainability. The system leverages clean and renewable energy sources, primarily solar panels, to power advanced technologies such as drones equipped with AI, fixed-site cameras, and a centralized control room. These technologies enable real-time monitoring and dynamic adjustments of the irrigation process, ensuring uniform distribution of the leaching solution and maximizing copper recovery. The chapter highlights the system's ability to reduce operational risks for workers, minimize resource waste, and improve process efficiency. Additionally, it discusses the integration of predictive algorithms and PID controllers for precise control and optimization of the irrigation process. The chapter concludes with tangible results from a major copper mine, demonstrating a 1.4% increase in copper recovery, improved flow rate stability, reduced response time to anomalies, and significant enhancements in worker safety.AI Generated
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AbstractLeaching pads in Chile face significant challenges due to harsh environmental conditions and difficult terrain, posing risks such as falls, sun exposure, physical strain, gas inhalation, and communication breakdowns. To address these issues, EPCM Chile developed an automated irrigation system powered by renewable energy to enhance leaching efficiency, worker safety, and copper recovery. The system has several key objectives: to maximize copper production from leaching piles by ensuring uniform application of leaching solution across pre-designated areas using a custom irrigation grid. Reduce manual worker intervention and minimize their exposure to critical risks. Maintain optimal irrigation uniformity throughout the leaching process, ensuring the irrigation rate remains stable and potential vulnerabilities in the piles are addressed. Continuous monitoring through a control room, AI-equipped drones, and field cameras enables real-time anomaly detection and prompt interventions. Powered by renewable energy from northern Chile, the system ensures sustainable production while maintaining worker safety. Over a 60-day cycle, there has been a 1.4% increase in soluble copper recovery, demonstrating the system's effectiveness. The initial flow rate, which was 78% before automation, has improved to 99.48% during a leaching cycle, drastically reducing the need for human intervention. The automated control system, consisting of control stations, offers safe and efficient leaching solutions under optimal conditions, minimizing undesirable effects from deviations. This enables real-time decision-making that is both quick and precise, allowing irrigation modelling to be adapted to specific conditions, whether environmental, physical, or natural. -
Advancements and Impacts of Expanded FrothSense+™ on Cu Special at Doe Run’s Pb/Zn/Cu Mill: A Case of Applied First Principles of Industrial Flotation
Weishi Mang, Adam Steimel, Brian Mangogna, Chris Hogan, Craig Romrell, Erwan Yap, Dustin RouleauThe chapter explores the successful implementation of the expanded FrothSense+™ system at Doe Run's Fletcher mill, focusing on optimizing Cu Special flotation. Key topics include the integration of modern selective reagents, advanced data analytics, and expert control technologies to enhance flotation performance. The chapter also discusses the challenges of processing complex, low-grade Cu ores and the innovative solutions employed to overcome these challenges. Notably, the replacement of traditional xanthate with selective Cu collectors resulted in significant improvements in concentrate grade and recovery. The chapter concludes with the successful application of the FrothSense+™ system, demonstrating its potential for broader adoption in the mineral processing industry.AI Generated
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AbstractThe Doe Run Company (Doe Run) defined and characterized thermodynamics, kinetics, hydrodynamics and phase equilibria of industrial flotation at IMPC 2024. Doe Run applied these first principles to develop an expert control system for Cu ore flotation (Cu Special). Initially implemented at Fletcher mill, with prior applications at Buick mill (excluding liberation), the system integrates expanded FrothSense+™ technology with the “Magnificent 4” Modules—particle density, modern reagents, bubbles, and froths—alongside “Intelligent Bulk Reagents.” These modules and reagents operate independently but synchronize through online X-ray Fluorescence (XRF) assays of mill feed, process froth and tail streams as flotation phase equilibria. This approach optimizes Cu recovery while achieving target concentrate grades with minimal Pb and Zn impurities. Reagents form the chemical foundation of flotation, making them a key validation point for expert control. Buick mill, followed by Fletcher mill, successfully replaced xanthate with dual selective Cu collectorsone for primary collection and the other for scavenging. This breakthrough enabled efficient processing of lower-grade Cu ores with elevated pyrite/marcasite that xanthate could not handle, significantly improving Cu concentrate grade and recovery. This advancement marks a paradigm shift in Cu flotation within Doe Run’s Viburnum Trend. The expanded FrothSense+™ enhances Doe Run’s ability to process lower-grade Cu ores and may enable economical Co/Ni concentrate recovery from Cu concentrates containing siegenite (Ni, Co)₃S₄. Grounded in first principles, this technology is scalable and extendable to Doe Run’s other mills, strengthening both Cu Special and Pb/Zn/Cu production and flotation optimization. -
An Innovative Tuyere Punching Machine to Improve Productivity and Extend Campaign Life of Peirce-Smith Converters
Max Zuang, Jean-Francois Stumper, Marc Flammang, Filipe RodriguesThe chapter delves into the functionalities and benefits of the TMT Tuyere Puncher, a compact and automated machine designed to enhance the productivity and longevity of Peirce-Smith Converters. Key topics include the machine's technical details, such as its rodless cylinder system, adjustable punching energy, and smart sensor systems for real-time diagnosis. The text also explores the machine's operational modes, which optimize tuyere wear and energy consumption. Additionally, it discusses the machine's ability to detect tuyere positions and adapt its punching stroke to match the reduced tuyere length over time. The chapter concludes by highlighting the machine's drilling capabilities and its role in extending the campaign life of converters.AI Generated
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AbstractThe proposed tuyere puncher is an innovative machine specifically designed for use with the Peirce-Smith Converters (PSC) or similar converters, to increase their campaign duration and operational efficiency. This paper demonstrates how various machine features address common issues in PSC tuyere maintenance, including premature tuyere wear, tuyere clogging, and misalignment between the converter and punching system. Knowing that the actual tuyere puncher accounts for a smaller fraction of PSC operation cost, its effects on the process gains can be tremendous. Since some features can be retrofitted to existing PSCs or punching systems, this work should be of interest to operators of new as well as existing converters. A primary advantage of the new tuyere puncher is its compact designabout half the size of conventional equipmentwhich simplifies installation and reduces the required workspace around the PSC. The modular design allows the machine to easily integrate additional features and extensions, providing flexibility. The machine offers a new pneumatic punching mode that reduces compressed air consumption and at the same time enables a smoother punching bar movement. This is a significant benefit, as compressed air is an expensive energy source, and smoother movements reduce the wear on the tuyeres and on its check valves. Operators can select either the conventional or the new punching mode on the fly, depending on the operating conditions. It is known that the length of the tuyeres is decreasing over their lifetime, thereby affecting the surrounding refractory and leading to premature need for relining. A full penetration of the punching bar through the tuyere into the copper bath deteriorates the fragile tuyere end and exposes the tip of the punching bar to excessive heat. As a distinctive solution, the punching bar’s stroke can be adjusted precisely for each tuyere individually, enabling operators to adapt the punch depth to the earlier recorded measurement value. In addition, the correctness of the tuyere length measurement is verified after each punch by a camera-based analysis of the punching bar, such that the measurement can be updated online. This functionality has a significant impact on PSC maintenance costs and extends campaign duration. To address clogged tuyeres, the machine can be fitted with a specialized drilling function. A drilling test campaign has proven that with adequate drilling tools, clogged tuyeres can be re-opened within a short time. Reactivating lost tuyeres restores the productivity of the PSC and helps distribute operational load amongst all tuyeres, thereby reducing tuyere and refractory wear. A tuyere position detection system, combined with automatic recalibration, monitors and ensures precise alignment of the punching system with each tuyere. Horizontal misalignment can occur due to issues during tuyere installation. The vertical alignment confirms whether the PSC has been properly rotated into its working position. This function prevents operational errors before any damage occurs. -
Two-Stage Powered Tuyere Replacement—TPID/TKID for Anode Furnace Process Optimization
Christoph Sagadin, Martina Hanel, Andreas Filzwieser, Manuel SeidlThis chapter explores the optimization of the anode furnace process through the implementation of a two-stage powered tuyere replacement system, known as TPID/TKID. The text delves into the design and functionality of the TPID/TKID, emphasizing its ability to reduce physical strain on operators and minimize refractory damage. It highlights the use of hydraulic precision for smooth tuyere insertion, enhancing operational efficiency and safety. The chapter also discusses the structural optimization of the system, including the use of heat-treated stainless steel to increase tuyere lifespan and reduce replacement frequency. Additionally, it explores the integration of a permanent gas supply and the use of ionic liquids as a safer hydraulic medium. The text concludes with a summary of the key advancements introduced by the TPID/TKID, including its potential for future developments in segmented tuyere designs to minimize steel input and improve overall efficiency.AI Generated
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AbstractThe integration of a hydraulically driven device for supporting the tuyere replacement, especially for continuous production routes, can contribute to an optimized anode furnace operation. By hydraulically driving in tuyeres with precision—applying just enough force for a smooth inlet, the impact on the refractory can be minimized even at this highly stressed area. Especially when compared to the use of a sledgehammer or jackhammer, as the state-of-the-art method. With the Tuyere push-in device (TPID) or Tuyere knock-in device (TKID), not only is the impact on the refractory, but also the impact on the operators is minimized. The currently heavy, physical work in a danger zone and the hot environment is exhausting and dangerous for the workers. Since the TPID/TKID is lifted via crane but still can apply a force of 20 t precisely to the tuyere, it can reduce the strain on operating personnel. Two different operational stages, one slow speed and full force, one full speed at low force support the introduction of the worn tuyere. Subsequently, with the adapted and improved design at the furnace structure, safety risks can be minimized with the switch to a permanent gas supply, just to name one example. -
Radiative Correction Method for Precise Temperature Measurements in the Presence of Interfering Gaseous Media Using an Optical Probe in Direct-to-Blister Flash Furnace
Felipe Lamas, Jonathan Torres-Sanhueza, Francisco Perez, Erick Flores, Bruno Rossel, Sergio Torres, Roberto Parra, John Barbante, Mark O’SullivanThis chapter explores the challenges of precise temperature measurements in copper smelting furnaces, focusing on the interference caused by gaseous media and dust. It introduces a dynamic assisted adjustment (DAA) method that corrects temperature measurements using optical probes and thermocouple data. The method was validated in a real-world scenario at the Olympic Dam's direct-to-blister flash furnace, demonstrating significant improvements in accuracy and reliability. The chapter also discusses the design and installation of the optical probe, highlighting its robustness in high-temperature and corrosive environments. Additionally, it presents performance metrics and statistical analyses, showcasing the method's ability to reduce errors and enhance temperature measurement precision. The findings pave the way for more accurate process control in copper smelting, ultimately improving efficiency and sustainability in the industry.AI Generated
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AbstractOptical sensors used for temperature measurements are very susceptible to errors when interfering with gaseous media are present in the optical path between the measured object and optical sensor. These errors are not only of great magnitude but also random in nature, hence the use of optical sensors in real industrial scenarios like Flash Furnaces where interfering gaseous media are always present is increasingly challenging. This work proposes a correction to the two-color pyrometric technique for temperature estimation based on Planck’s radiation model to correct errors in measured signal caused by the interfering medium. The basis of this correction method hinges on the fact that an effective emissivity can be estimated by minimizing the error of the measured signal to the ideal object irradiance. Furthermore, an estimation of the transmission of the interfering medium can be estimated from the measured data, which is used to recover the original radiative signal of interest. This provides a low computational cost and effective method that estimates temperature accurately even in the presence of interfering media. -
Considerations for Selection and Integration of Online Elemental Analysers for Mineral Processing Operations
Nur Muhamad, Tom StrombotneThis chapter delves into the critical aspects of selecting and integrating online elemental analysers for mineral processing operations. It begins by highlighting the evolution from traditional offline laboratory analyses to real-time monitoring technologies, emphasizing the advantages of continuous data collection. The text explores various elemental analysis technologies, including X-Ray Fluorescence (XRF), Laser-Induced Breakdown Spectroscopy (LIBS), and Prompt Gamma Neutron Activation Analysis (PGNAA), detailing their principles, applications, and limitations. It also discusses the importance of representative sampling, the impact of plant layout on analyser selection, and the economic considerations involved. The chapter includes practical case studies, such as the implementation of online elemental analysis in a nickel concentrator and a mine-to-mill scenario, demonstrating the benefits of improved grade consistency, enhanced production efficiency, and reduced production losses. The conclusion underscores the transformative impact of online elemental analysis on the mineral processing industry, emphasizing the need for ongoing collaboration between analyser manufacturers and end-users to drive continuous improvement and innovation.AI Generated
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AbstractIntegrating online elemental analysers into industrial processes marks a significant leap in real-time material composition monitoring. This paper discusses strategies for their effective selection and integration. These analysers significantly enhance process optimization, efficiency, and quality control but require meticulous planning to avoid operational disruptions. Choosing analyser technology and design tailored to specific process needs is crucial. Inline analysers are favoured for their ability to deliver precise, timely data by integrating directly into the process stream, thus minimizing measurement delays and cross-contamination risks from sample transport. Ensuring accurate, reliable data in diverse and challenging environments is vital, necessitating robust analysers that can withstand extreme temperatures, pressures, and corrosive conditions. It is also essential that the analysed samples represent the bulk material accurately. Implementing a continuous sampling mechanism that provides homogeneous, representative samples is key. At Thermo Fisher, we collaborate closely with end-users to create robust, cost-effective solutions, ensuring analysers deliver meaningful data for optimizing process performance. -
Computational Simulation of Copper Solvent Extraction: Modelling and Analysis of the SX Control
Khuthadzo Mudzanani, Samuel Ramatsoma, Terence PhadiThis chapter delves into the computational simulation of copper solvent extraction (SX), a vital process in hydrometallurgy for separating and purifying metals from aqueous solutions. The study emphasizes the importance of dynamic modelling and advanced process control strategies to optimize copper recovery and minimize reagent consumption. It explores the evolution of SX, highlighting its advantages over traditional pyrometallurgical methods, particularly in sub-Saharan Africa. The chapter also discusses the principles of operation, including the critical role of the aqueous-organic interface in mixer-settler systems. Mechanistic models and their application to process control are thoroughly examined, with a focus on improving extraction efficiency and reducing operational costs. The study validates the computational model using industrial plant data, demonstrating its predictive capability and identifying areas for further refinement. Additionally, it recommends the implementation of advanced control strategies and continuous model updates to enhance copper recovery and operational efficiency. The chapter concludes with insights into the future of copper SX, emphasizing the need for sustainable and cost-effective extraction processes.AI Generated
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AbstractSolvent extraction (SX) is a fundamental process in hydrometallurgy that recovers valuable metals from aqueous solutions. Mintek-Measurement and Control Division (MAC) has conducted audits on SX plants and found that most of the SX plants are operating inefficiently due to a lack of advanced process control and instrumentation. In response, a prototype instrument has been developed and advanced process control strategies have been proposed. To initiate testing of the proposed control strategies, the development of a simulator was deemed necessary. Testing the proposed strategies using a simulator is more cost-effective than using the actual plant or pilot plant. Conducting online or plant tests for control strategies can be very expensive, highlighting the need for reliable simulation models. These models will aid in troubleshooting plant performance issues and will be valuable for future plant auditing and troubleshooting, in addition to testing control strategies. To achieve this, a computational simulation of solvent extraction was developed using both Python and MATLAB Simulink. For this part of the study, the focus was on the copper extraction circuit from a plant in Southern Africa. This SX plant runs with a feed flow rate range of between 500 and 700 m3/h of pregnant leach solution. The organic feed flow rates range from 1.3 to 1.5 times the PLS feed. A distribution coefficient (KD) was randomly selected from 10–50 to model the transfer of copper ions from the aqueous phase to the organic phase during equilibration. The simulation then incorporates a stripping step where the organic phase, enriched with copper, is mixed with a stripping solution. An assumed stripping efficiency of 80% is applied to transfer copper ions back to the aqueous phase. Python-based simulator was developed following a fundamental analysis of the chemical reactions inherent to the solvent extraction process. The simulation tracks copper ion concentrations in both the aqueous and organic phases over 50 discrete time steps using mass balance equations. The proposed method is validated using real-time data from industrial copper SX circuits. -
Sitewide De-Bottlenecking and Optimization Using Digital Solutions
Riley Fitzpatrick, Juan Camou, Alireza Kheradmand, Timothy Towers, Bill GoughThis chapter explores the application of digital solutions for sitewide de-bottlenecking and optimization in mining operations. It delves into the use of advanced process control (APC), digital twins, and machine learning to enhance grinding, tailings, and flotation processes. The text presents a detailed case study of a copper mine in Arizona, where Andritz's technologies led to significant improvements in throughput, power savings, and recovery. Key topics include the implementation of APC solutions for SAG and ball mills, the development of digital twins for real-time process monitoring, and the use of machine learning for economic optimization. The chapter concludes with quantifiable results, demonstrating the effectiveness of these digital transformations in improving overall mining efficiency.AI Generated
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AbstractMining companies are increasingly adopting digital technologies to improve operational efficiency and address production bottlenecks. Often cases, the producers try to focus on optimizing one area using new solutions and technologies. However, addressing one bottleneck can lead to the bottleneck moving elsewhere in the process. To mitigate this, Andritz developed a Sitewide roadmap for Digital Transformation, a structured approach that partners Andritz with mining companies to identify, prioritize, and implement optimization projects across a mine site. Andritz, together with the customer, develops a tailored roadmap that includes advanced control strategies and process simulations to target key operational areas. A critical part of this approach is ensuring that each operational area has the proper instrumentation required for advanced control solutions. Andritz begins by assessing instrumentation readiness, recommending upgrades or adjustments where needed to ensure accurate data collection. In collaboration with a copper mine in Arizona, Andritz applied this method to various parts of the processing plant. Optimization solutions spanned the mine to areas including grinding, flotation and tailings circuits. The full roadmap of projects enabled the copper mine to experience a 6.7% ore throughput increase and 7.6% decrease in SAG mill specific energy. The solutions in the tailing circuit helped with more water recovery and resulted in about 2% power savings. The team is currently commissioning the APC solution for the flotation circuit step-by-step. The level control and better grind size control have so far contributed to about 0.4% increase in recovery with more to expect after optimizing mass pull. -
Optimizing Flotation Circuit Using a Model that Can Predict Both Grade and Recoveries
Mohit Gupta, Holden Lim, Aaron Noble, Roe-Hoan YoonThis chapter explores the optimization of flotation circuits using a model that predicts both grade and recoveries. The model incorporates surface forces as kinetic parameters, including electrical double-layer, van der Waals, and hydrophobic forces. The study validates the model through simulations and experiments, demonstrating its accuracy in predicting flotation performance. A significant finding is the use of a Super Collector, which increases contact angles and hydrophobic forces, leading to higher recoveries and throughput. The chapter also discusses the impact of mineral liberation and the benefits of using the Super Collector in both closed and open circuit configurations. The results show substantial improvements in copper recovery and revenue, highlighting the potential of this approach in industrial applications.AI Generated
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AbstractIn 1905, Sulman and Picard received a U.S. patent to disclose a method of blowing air bubbles into a pulverized ore slurry to upgrade a mined ore. This process, known as dispersed air flotation, is simple, efficient, and cost-effective; therefore, it has been used to produce practically all metals humans use. Thus, flotation is regarded as the greatest single metallurgical improvement of the modern era. It is a kinetic process in which bubbles and particles collide with each other to form thin liquid films between them. The films must rupture for air bubbles to collect target mineral particles (e.g., chalcopyrite), forming finite contact angles (θ). In the present work, we used a simple Arrhenius-type rate equation that can predict the rate constants (k) for bubble-particle interactions as functions of the surface forces in TLFs, which include the electrical double-layer, van der Waals, and hydrophobic forces. This new approach made it possible to predict both the grades and recoveries under different operating conditions. The model has been validated versus a set of plant survey data obtained on a rougher flotation bank. Further, the model suggests how one can improve coarse particles recovery and throughput by control of surface forces. -
A Data-Driven Approach to Improving and Optimizing Process Plant Operations
W. Hempel, D. Frost, S. AnandThis chapter explores the transformative impact of data-driven approaches on process plant operations in the mining and mineral processing industry. It highlights the challenges faced by the industry, such as declining ore grades and stringent environmental regulations, and how leveraging big data, artificial intelligence, and remote monitoring centers can address these issues. The NeuroMine Mining Insights Center is introduced as a cutting-edge digital hub that centralizes monitoring, data analytics, and optimization solutions to enhance mineral processing facilities. Key benefits of remote monitoring and data science centers include improved operational efficiency, predictive maintenance, and enhanced safety. The chapter also delves into the structure and capabilities of the NeuroMine Center, detailing its hub-and-spoke operating model and high-level process flow. Two detailed case studies illustrate the practical applications and measurable benefits of the NeuroMine Center, showcasing significant improvements in process stability, recovery rates, and cost savings. The conclusion emphasizes the importance of embracing data-driven decision-making and remote intelligence models for long-term resilience and profitability in the mining industry.AI Generated
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AbstractThe NeuroMine Mining Insights Center, developed by Minopex (a member of DRA group), is a centralized remote monitoring and data analytics hub designed to optimize mineral processing operations. By integrating advanced process monitoring, predictive maintenance, and anomaly detection, the center enhances throughput, recovery, stability, and cost efficiency across multiple sites and commodities. This paper explores how data-driven intelligence is transforming mining and mineral processing, enabling real-time decision-making and proactive interventions. Case studies highlight NeuroMine’s ability to detect inefficiencies early, implement corrective actions, and deliver measurable financial and technical value. The results demonstrate significant improvements in process stability, equipment performance, and overall plant efficiency. As the industry moves toward digital transformation, remote monitoring solutions like NeuroMine are becoming essential in optimizing operations, reducing costs, and improving sustainability. This paper underscores the value of centralized data-driven intelligence in ensuring long-term resilience and competitiveness in the mining sector. -
Applying the Novel Cross-Belt Neutron Activation Analysis for Real-Time Analysis of Elements and Mineralogy in Copper Ore
Eduardo Janampa, Jinhong ZhangThis chapter explores the application of cross-belt Neutron Activation Analysis (NAA) for real-time analysis of elements and mineralogy in copper ore processing. The study evaluates the performance of NAA against conventional laboratory techniques, focusing on its ability to provide accurate and comprehensive data. Key topics include the methodology of NAA, its calibration process, and the results of comparative measurements. The chapter also discusses the environmental benefits and cost-efficiency of NAA, highlighting its potential to revolutionize grade control and process optimization in the mining industry. The findings suggest that NAA offers superior accuracy, real-time reporting, and comprehensive mineralogical insights, making it a valuable tool for enhancing operational control and environmental management.AI Generated
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AbstractIn the copper mining industry, it has become critical in the past decade to apply real-time analysis of the elemental analytical and mineralogy of the copper ore, which can provide fast and reliable ore information to improve process control, for better mine planning and process assessment. Generally, there are some technical challenges, such as frequent calibration and maintenance, significant operational costs, and unsatisfying analysis accuracy, in the application of a real-time analyzer in practice. Recently, a novel cross-belt Neutron Activation Analyzer (NAA), i.e., Prompt Gamma NAA or Pulsed Fast Thermal NAA, has been applied to directly measure the elements and the mineralogy of copper ore. NAA uses Americium-Beryllium Industrial Neutron Sources, which not only saves the isotope replacement, but provides high energy to use neutron inelastic scatter and thermal neutron capture reactions for the direct measurement of the elements of carbon (C), oxygen (O), and fluorine (F), which are difficult to be accurately measured by using other available real-time analyzers. In the present study, a cross-belt NAA was applied to analyze the elements and mineralogy of various copper ore samples. The analyzer was calibrated by implementing the site reference standard and the mineralogical reference standard. The results are compared to those obtained with inductively coupled plasma mass spectrometry and atomic absorption spectroscopy. The measured mineralogy results are compared to those obtained with X-ray fluorescence and QEMSCAN. Findings show that NAA has the advantages of (1) reducing operation costs, (2) analyzing the elements of C, O, and F, and (3) analyzing the mineralogy with high accuracy and reliability, all of which make a cross-belt NAA very promising to be widely applied in copper mining industry. -
Local and Global Interpretation of Flotation Recovery Predictive Machine Learning Models
Kirsten Louw, Jixue Liu, Richmond AsamoahThis chapter delves into the application of machine learning models, specifically Gaussian Process Regression (GPR), to predict rougher copper recovery in flotation circuits. The study emphasizes the importance of interpretability methods to understand the contributions of various features to the model's predictions. Three modeling scenarios are explored: using only established rougher flotation variables, all variables, and a subset of variables selected by a regularized neighborhood component analysis algorithm. The GPR model with an exponential kernel function is identified as the best-performing model across all scenarios. The chapter provides a detailed analysis of local and global interpretations using Shapley values and SHAP explanations. Local interpretations reveal how individual features contribute to specific predictions, while global interpretations aggregate these contributions to show overall feature importance. The results highlight the significance of pulp chemistry variables, such as Eh and pH, in improving prediction accuracy. The study concludes that interpretability methods can enhance the trust and usability of complex machine learning models in industrial settings.AI Generated
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AbstractInterpretability methods are used to ‘shed light’ onto how ‘black-box’ machine learning (ML) models make their predictions. A local interpretation provides an explanation of features’ contribution to an individual ML prediction while global methods (e.g., SHAP) provide a more general understanding of the ML models. In this paper, interpretability methods have been applied to Gaussian Process Regression ML models used to predict rougher flotation copper recovery. The investigation includes understanding how the combination of plant and chemistry variables affects feature importance and the prediction of rougher copper recovery. The results show the importance of three key process variables, namely: throughput, frother in specific tank cells, and pulp redox potential. The SHAP summary plot further highlights the linear or nonlinear relationship between the features and the prediction of rougher copper recovery. -
Ensure Smooth Operation of Smelter Acid Plants by Using the Right Catalyst Solutions
Martin Ariel Alvarez, Mårten Granroth, Patrick PolkThis chapter delves into three critical case studies that underscore the importance of advanced catalyst solutions and technical services in optimizing the performance of smelter acid plants. The first case study focuses on diagnosing and resolving high emissions in a metallurgical plant, highlighting the role of technical service campaigns and the impact of leaks in heat exchangers. The second case study explores the challenges of transient operations in a copper smelter plant, emphasizing the need for dynamic simulations to design effective catalyst loading. The third case study demonstrates how choosing high-performance catalysts can significantly enhance profitability and compliance with environmental regulations. Through detailed measurements, simulations, and cost analyses, the chapter provides a comprehensive overview of the strategies and technologies that can ensure smooth and efficient operation of smelter acid plants.AI Generated
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AbstractCopper smelters are tied to downstream sulfuric acid plants that treat tail SO2 gases before they are discharged into the atmosphere. If the acid plant is not functioning properly and is unable to receive or adequately treat the SO2 off gases from the smelter, it can create a bottleneck that affects copper production and poses severe threats to the smelter's profitability. When the acid plant restricts smelter production, significant losses can occur: in some cases, the cost of a single day of production loss can easily exceed the amount spent on catalysts over many years. It is clear then that, in order to remain competitive in today's fast-paced and dynamic market landscape, copper smelters cannot afford suboptimal operation, extended downtimes, shorter-than-expected campaigns, or reduced rates in the acid plant. The use of the right catalyst solutions and technical service has proven to help operators avoid these issues, ensure smooth operation in their acid plants, and maximize smelter throughput. Examples of this include implementing the appropriate catalyst strategy to maximize the length of the campaign by mitigating pressure-drop build-up and ensuring a high enough conversion for extended cycles, as well as using the appropriate catalyst solution to increase hot standby times, thereby avoiding major shutdowns for frequent repairs or maintenance work. However, it is not only the right catalyst strategy that is important, but also the proper use of catalyst technical service. Using the unique capabilities of technical service to design or optimize catalyst loadings in transient conditions, which are the rule in copper smelters, or being able to quickly identify heat exchanger leaks that could limit plant performance are also key factors in ensuring proper operation. In this paper, Topsoe will present real-life examples of how acid plant operators from copper smelters have already benefited from the right catalyst solutions and technical service to overcome their unique challenges. -
Real-Time Optimization of Grinding in Copper Processing
Eduardo Nunez, Dante Garcia, Joshua Morales, Karl Gugel, Peter Czel, Boris Sullcahuaman, Rayneth LawThis chapter delves into the advancements in grinding optimization for copper processing, focusing on real-time monitoring and control through high-resolution vibration sensors and advanced analytics. It highlights the use of the MillSlicerVIP system, which employs multiple sensors to provide a comprehensive 360-degree vibration profile of the mill. The text discusses how these sensors detect various conditions such as ore size, hardness, and competency, as well as the effects of different ball charges, filling levels, and liner wear. Advanced Analytics Measurements (AAM) are introduced as a means to process vast amounts of data in real-time, enabling the detection of optimal and sub-efficient operating conditions. The chapter also explores the impact of liner damage levels (LDL) and the relationship between ball charge and total charge (Jb/Jc) on mill performance. Through detailed case studies and data visualizations, the text demonstrates how these technologies can prevent mechanical damage, optimize grinding efficiency, and reduce downtime. The conclusion emphasizes the significance of real-time data processing and advanced analytics in achieving peak mill performance and operational continuity.AI Generated
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AbstractThe objective of achieving operational excellence in real-time requires multiple elements working together. Successful implementations require fundamental aspects like the correct instrumentation, data collection, data analytics and optimization engine. All these pieces must work together and integrate with the site process and control system effectively. This paper reviews practical learnings and best practices in autogenous, semi-autogenous, and ball mills. The discussion includes the implementation of advanced instrumentation as vibration sensors attached to the rotating shell of the mill; it explores best practices in data collection and analytics to provide recommendations in real-time and their integration into the site control system to achieve optimum grinding. -
Feasibility Assessment of Copper Projects with MAFMINE ESG: Application and Comparative Predictive Analysis.
T. P. Fernandez, E. A. Petter, C. Petter, J. OppermannThis chapter explores the feasibility assessment of four copper projects using MAFMINE, an academic tool designed to estimate capital expenditure (CAPEX) and operating expenditure (OPEX). The study compares these projects with the Zero Project, a major copper producer, to analyze the accuracy and applicability of MAFMINE in real-world scenarios. By varying strategic indicators, the research provides insights into how different factors influence cost predictions and project feasibility. The study also discusses the integration of ESG factors, emphasizing their growing importance in the mining industry. The results demonstrate the tool's effectiveness in dynamic scenario analysis, offering a significant advancement in pre-feasibility evaluations.AI Generated
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AbstractEfficient calculation is key in the optimisation of copper metallurgical processes, strategic planning and data-driven decision making from extraction to final production. Some of the most important include the modelling of crushing, grinding and concentration curves depending on their respective variables, all in operation with an emphasis on cost. This is why the industry is increasingly interested in mathematical models and computer simulations that allow predicting and dynamically adjusting process variables to obtain much faster and more accurate results and forecasts in a productivity-sustaining consequence. Technological advances in real-time simulation and data analysis are key to reducing energy consumption, for example, and of course improving copper recovery with the added bonus of minimising environmental impacts. In this case based on one of the curves (in the processing area) that were used to predict MAFMINE equations, a project feasibility assessment tool and the amount of points that accumulate in the percentage of certainty of its prediction, we mainly analyse four projects to represent the response activity that the software has, we vary two strategic indicators with which the prediction can be manipulated to find better results in the economic environment.The entire evaluation tool is currently in the ESG version; being MAFMINE ESG, a software designed to generate data indicating up to the level of pre-feasibility of mining projects, it has an underground mine, open pit mine, beneficiation plant and related modules in the interest of costs such as CAPEX and OPEX.
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- Title
- 12th International Copper Conference
- Editors
-
The Metallurgy and Materials Society of CIM
The Society for Mining, Metallurgy & Exploration
The Minerals, Metals & Materials Society
- Copyright Year
- 2025
- Publisher
- Springer Nature Switzerland
- Electronic ISBN
- 978-3-032-00102-3
- Print ISBN
- 978-3-032-00101-6
- DOI
- https://doi.org/10.1007/978-3-032-00102-3
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