Process Optimization in Mineral Processing

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Processing and Extractive Metallurgy".

Deadline for manuscript submissions: closed (18 June 2021) | Viewed by 26667

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Oulu Mining School, University of Oulu, 90570 Oulu, Finland
Interests: process optimization; process chemistry; mine to mill; water and tailings management; metallurgical testwork
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Special Issue Information

Dear Colleagues,

The theme of the Special Issue is process optimization in mineral processing, a vitally important and comprehensive area of research. Multidisciplinary collaboration is required, since production of saleable concentrate of high quality is the sum of many factors and requires wide understanding of the technical and economical aspects of mineral processing and the stages linked to it.

In simple terms, the primary aim of process control is to maximize efficiency of the process: achieving maximum production at minimum cost. The quality of the final concentrate determines the success of further downstream process and the optimum outcome requires proper characterization and optimization of the process. Successful performance of large complex industrial plants depends upon precise measurements and control of a number of process variables. Variability of ore feed, complex mineralogy, quality of process water, reagents—all these impact process performance and pose challenges for process optimization and control. To optimize the process in the best possible way, integrated and frequent mineralogy-based analysis, reliable real-time information from the various process stages, and optimized data management play key roles: Repeatable measurements provide the control system with essential information for a stable operation.

Prof. Dr. Saija Luukkanen
Guest Editor

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Keywords

  • process control
  • mineralogy
  • process chemistry
  • sensors and measurements
  • process automation
  • data management

Published Papers (10 papers)

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Research

19 pages, 653 KiB  
Article
Calibration and Validation of a Cone Crusher Model with Industrial Data
by Robson A. Duarte, André S. Yamashita, Moisés T. da Silva, Luciano P. Cota and Thiago A. M. Euzébio
Minerals 2021, 11(11), 1256; https://doi.org/10.3390/min11111256 - 11 Nov 2021
Cited by 7 | Viewed by 3668
Abstract
This paper reports the calibration and validation of a cone crusher model using industrial data. Usually, there are three calibration parameters in the condensed breakage function; by contrast, in this work, every entry of the lower triangular breakage function matrix is considered a [...] Read more.
This paper reports the calibration and validation of a cone crusher model using industrial data. Usually, there are three calibration parameters in the condensed breakage function; by contrast, in this work, every entry of the lower triangular breakage function matrix is considered a calibration parameter. The calibration problem is cast as an optimization problem based on the least squares method. The results show that the calibrated model is able to fit the validation datasets closely, as seen from the low values of the objective function. Another significant advantage of the proposed approach is that the model can be calibrated on data that are usually available from industrial operation; no additional laboratory tests are required. Calibration and validation tests on datasets collected from two different mines show that the calibrated model is a strong candidate for use in various dynamic simulation applications, such as control system design, equipment sizing, operator training, and optimization of crushing circuits. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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19 pages, 5543 KiB  
Article
Applied Calibration and Validation Method of Dynamic Process Simulation for Crushing Plants
by Kanishk Bhadani, Gauti Asbjörnsson, Barbara Schnitzer, Johannes Quist, Christian Hansson, Erik Hulthén and Magnus Evertsson
Minerals 2021, 11(9), 921; https://doi.org/10.3390/min11090921 - 25 Aug 2021
Cited by 2 | Viewed by 1848
Abstract
There is a need within the production industry for digitalization and the development of meaningful functionality for production operation. One such industry is aggregate production, characterized by continuous production operation, where the digital transformation can bring operational adaptability to customer demand. Dynamic process [...] Read more.
There is a need within the production industry for digitalization and the development of meaningful functionality for production operation. One such industry is aggregate production, characterized by continuous production operation, where the digital transformation can bring operational adaptability to customer demand. Dynamic process simulations have the ability to capture the change in production performance of aggregate production over time. However, there is a need to develop cost-efficient methodologies to integrate calibrations and validation of models. This paper presents a method of integrating an experimental and data-driven approach for calibration and validation for crushing plant equipment and a process model. The method uses an error minimization optimization formulation to calibrate the equipment models, followed by the validation of the process model. The paper discusses various details such as experimental calibration procedure, applied error functions, optimization problem formulation, and the future development needed to completely realize the procedure for industrial use. The validated simulation model can be used for performing process planning and process optimization activities for the crushing plant’s operation. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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14 pages, 964 KiB  
Article
Holistic Pre-Feasibility Study of Comminution Routes for a Brazilian Itabirite Ore
by Juliana Segura-Salazar, Natasha de S. L. Santos and Luís Marcelo Tavares
Minerals 2021, 11(8), 894; https://doi.org/10.3390/min11080894 - 18 Aug 2021
Cited by 5 | Viewed by 2739
Abstract
Comminution is an essential step in processing itabirite ores, given the need to liberate silica and other contaminants from the iron minerals for downstream concentration and then pellet feed production. In general, these ores in Brazil are not particularly hard to crush and [...] Read more.
Comminution is an essential step in processing itabirite ores, given the need to liberate silica and other contaminants from the iron minerals for downstream concentration and then pellet feed production. In general, these ores in Brazil are not particularly hard to crush and grind, but both capital (CAPEx) and operating (OPEx) expenditures in this stage of preparation can be critical for the project, in particular due to uncertainties in iron ore prices. Several circuits have been designed and are in operation for this type of ore in Brazil; however, it is not yet clear which technologies are more cost-effective and in which configuration they should be applied. This work critically analyzes four comminution circuits for an undisclosed case study. For these circuits, CAPEx, OPEx, and some environmental sustainability indices, as well as qualitative technical criteria, were used in the comparisons. This work concludes that two of these process routes, especially those based on more energy-efficient technologies (and one of these still rarely explored even at bench-scale), have demonstrated to be very attractive from multiple standpoints. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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15 pages, 6298 KiB  
Article
Development and Validation of an Online Analyzer for Particle Size Distribution in Conveyor Belts
by Claudio Leiva, Claudio Acuña and Diego Castillo
Minerals 2021, 11(6), 581; https://doi.org/10.3390/min11060581 - 30 May 2021
Cited by 3 | Viewed by 2830
Abstract
Online measurement of particle size distribution in the crushing process is critical to reduce particle obstruction and to reduce energy consumption. Nevertheless, commercial systems to determine size distribution do not accurately identify large particles (20–250 mm), leading to particle obstruction, increasing energy consumption, [...] Read more.
Online measurement of particle size distribution in the crushing process is critical to reduce particle obstruction and to reduce energy consumption. Nevertheless, commercial systems to determine size distribution do not accurately identify large particles (20–250 mm), leading to particle obstruction, increasing energy consumption, and reducing equipment availability. To solve this problem, an online sensor prototype was designed, implemented, and validated in a copper ore plant. The sensor is based on 2D images and specific detection algorithms. The system consists of a camera (1024 p) mounted on the conveyor belt and image processing software, which improves the detection of large particle edges. The algorithms determine the geometry of each particle, from a sequence of digital photographs. For the development of the software, noise reduction algorithms were evaluated and selected, and a routine was designed to incorporate morphological mathematics (erosion, dilation, opening, lock) and segmentation algorithms (Roberts, Prewitt, Sobel, Laplacian–Gaussian, Canny, watershed, geodesic transform). The software was implemented (in MatLab Image Processing Toolbox) based on the 3D equivalent diameter (using major and minor axes, assuming an oblate spheroid). The size distribution adjusted to the Rosin Rammler function in the major axis. To test the sensor capabilities, laboratory images were used, where the results show a precision of 5% in Rosin Rambler model fitting. To validate the large particle detection algorithms, a pilot test was implemented in a large mining company in Chile. The accuracy of large particle detection was 60% to 67% depending on the crushing stage. In conclusion, it is shown that the prototype and software allow online measurement of large particle sizes, which provides useful information for screening equipment maintenance and control of crushers’ open size setting, reducing the obstruction risk and increasing operational availability. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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16 pages, 13303 KiB  
Article
Study on Sintering Characteristics of Ultra-Poor Vanadium-Titanium Magnetite
by Songtao Yang, Mi Zhou, Tao Jiang and Xiangxin Xue
Minerals 2021, 11(5), 515; https://doi.org/10.3390/min11050515 - 13 May 2021
Cited by 10 | Viewed by 1906
Abstract
Artificial rich ore for blast furnace use can be produced by sintering ultra-poor vanadium-titanium magnetite (PVTM) with a high-grade iron concentrate. Here, acid (R = 0.33, 0.50), self-fluxing (R = 1.10), and high-basicity (R = 2.60) PVTM sinters were produced in a sinter [...] Read more.
Artificial rich ore for blast furnace use can be produced by sintering ultra-poor vanadium-titanium magnetite (PVTM) with a high-grade iron concentrate. Here, acid (R = 0.33, 0.50), self-fluxing (R = 1.10), and high-basicity (R = 2.60) PVTM sinters were produced in a sinter pot. Their performances were determined using the comprehensive index. The microstructures of the PVTM sinter were observed by metallographic microscope and scanning electron microscopy equipped with an energy dispersion spectrum (SEM-EDS). The results suggest that the acid PVTM sinter had a low flame front speed, low productivity, an uneven size distribution, and poor softening properties. It did have a high tumble index (TI) and low-temperature reduction disintegration index (RDI). The self-fluxing PVTM sinter had the worst performance (TI, RDI, reducibility index (RI)), while the high-basicity PVTM sinter had the highest flame front speed, highest productivity, a reasonable size distribution, excellent softening properties, and satisfactory TI and RDI values. The main consolidation form of the acid sinter was crystal stock, the main bonding phase of the self-fluxing sinter was silicate, and the main bonding phase of the high-basicity sinter was silico-ferrite of calcium and aluminum (SFCA). The comprehensive index values (from high to low) were the high-basicity (R = 2.60), acid (R = 0.50), natural acid (R = 0.33), and self-fluxing (R = 1.10) PVTM sinters. When the production capacity of the acid pellet was in shortage, the acid PVTM sinter (R = 0.50) could be produced by the surplus from the sinter plant. This replaced a part of the acid pellet and the burden structural model of the blast furnace smelting vanadium so the titanium burden could adopt a ‘high-basicity PVTM sinter + acid V-Ti pellet + acid (R = 0.50) PVTM sinter’. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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18 pages, 2986 KiB  
Article
Design of Cell-Based Flotation Circuits under Uncertainty: A Techno-Economic Stochastic Optimization
by Seyed Hassan Amini and Aaron Noble
Minerals 2021, 11(5), 459; https://doi.org/10.3390/min11050459 - 27 Apr 2021
Cited by 1 | Viewed by 2026
Abstract
The design of cell-based flotation circuits is often completed in two distinct phases, namely circuit structure identification and equipment sizing selection. While recent literature studies have begun to address the implications of stochastic analysis, industrial practice in flotation circuit design still strongly favors [...] Read more.
The design of cell-based flotation circuits is often completed in two distinct phases, namely circuit structure identification and equipment sizing selection. While recent literature studies have begun to address the implications of stochastic analysis, industrial practice in flotation circuit design still strongly favors the use of deterministic metallurgical modeling approaches. Due to the complexity of the available mathematical models, most flotation circuit design techniques are constructed based on deterministic models. Neglecting the impact of various sources of uncertainty may result in the identification of circuit solutions that are only optimal in a narrow region of specific operating scenarios. One promising strategy to address this shortcoming is through the Sample Average Approximation (SAA) methodology, a stochastic approach to handling uncertainty that has been widely applied in other disciplines such as supply chain and facility location management problems. In this study, a techno-economic optimization algorithm was formulated to select the optimal size and number of flotation cells for a fixed circuit structure while considering potential uncertainty in several input parameter including feed grade, kinetic coefficients, and metal price. Initially, a sensitivity analysis was conducted to screen the uncertain parameters. After simplifying the optimization problem, the SAA approach was implemented to determine the equipment configuration (i.e., cell size and number) that maximizes the plant’s net present value while considering the range of potential input values due to parameter uncertainty. The SAA methodology was found to be useful in analyzing uncertainty in flotation kinetics; however, the approach did not provide a useful means to assess the influence of uncertainties in ore grade and metal price, as these values are not significant in determining equipment size but rather influence the optimal circuit structure, which was not considered in this study. Results from an application example indicate that the SAA approach produces optimal solutions not initially identified in a deterministic optimization, and these SAA solutions tend to provide greater robustness to uncertainty and variation in the flotation kinetics. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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10 pages, 6194 KiB  
Article
Empirical Study on Reduction Behavior and Metallurgical Properties of Vanadia–Titania Magnetite in Blast Furnace
by Zhanwei He, Xiaojun Hu, Mo Lan, Jianxing Liu, Gongjin Cheng, Xiangxin Xue and Kouchih Chou
Minerals 2021, 11(4), 418; https://doi.org/10.3390/min11040418 - 15 Apr 2021
Cited by 2 | Viewed by 1645
Abstract
The loss of permeability affects the reduction of the ferrous burden in the cohesive zone of a blast furnace (BF). Vanadia–titania magnetite (VTM) burden of various chemical compositions have different metallurgical properties. The reduction and softening-melting-dripping properties of different kinds of VTM were [...] Read more.
The loss of permeability affects the reduction of the ferrous burden in the cohesive zone of a blast furnace (BF). Vanadia–titania magnetite (VTM) burden of various chemical compositions have different metallurgical properties. The reduction and softening-melting-dripping properties of different kinds of VTM were investigated. The results showed that the core of sinter or pellet is indirectly reduced to wustite and (Fe,Ti)Ox, and the periphery contains interlinked metallic iron and CaSiO3 in the cohesive zone. Wustite and (Fe,Ti)Ox are directly reduced in the melting-dripping zone. The aggregate (Fe, V, Cr) present in the non-dripping causes a loss of valuable components. With the increase in TiO2 content, the substrate phase of molten slag changes from melilite to titanaugite, and the mass of dripping decreases gradually. In addition, the permeability index S increased and the melting zone widened, which indicates that the increase in TiO2 content negatively affected the melting-dripping performance. The mass of the dripping is directly proportional to the pellet ratio. Considering the adverse effect of TiO2 on softening-melting-dripping properties, it is recommended that high TiO2 VTM is smelted while mixed with ordinary ores or with an increased pellet ratio in the burden structure. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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15 pages, 3039 KiB  
Article
Application of Optimization Method for Calibration and Maintenance of Power-Based Belt Scale
by Kanishk Bhadani, Gauti Asbjörnsson, Erik Hulthén, Kristoffer Hofling and Magnus Evertsson
Minerals 2021, 11(4), 412; https://doi.org/10.3390/min11040412 - 14 Apr 2021
Cited by 7 | Viewed by 2103
Abstract
Process optimization and improvement strategies applied in a crushing plant are coupled with the measurement of such improvements, and one of the indicators for improvements is the mass flow at different parts of the circuit. The estimation of the mass flow using conveyor [...] Read more.
Process optimization and improvement strategies applied in a crushing plant are coupled with the measurement of such improvements, and one of the indicators for improvements is the mass flow at different parts of the circuit. The estimation of the mass flow using conveyor belt power consumption allows for a cost-effective solution. The principle behind the estimation is that the power draw from a conveyor belt is dependent on the load on the conveyor, conveyor speed, geometrical design, and overall efficiency of the conveyor. Calibration of the power-based belt scale is carried out periodically to ensure the accuracy of the measurement. In practical implementation, certain conveyors are not directly accessible for calibration to the physical measurement as these conveyors have limited access or it is too costly to interrupt the ongoing production process. For addressing this limitation, a better strategy is needed to calibrate the efficiency of the power-based belt scale and maintain the reliability of such a system. This paper presents the application of an optimization method for a data collection system to calibrate and maintain accurate mass flow estimation. This includes calibration of variables such as the efficiency of the power-based belt scale. The optimization method uses an error minimization optimization formulation together with the mass balancing of the crushing plant to determine the efficiency of accessible and non-accessible conveyors. Furthermore, a correlation matrix is developed to monitor and detect deviations in the estimation for the mass flow. The methods are applied and discussed for operational data from a full-scale crushing plant. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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13 pages, 3050 KiB  
Article
The Effect of Hydrodynamic Conditions on the Selective Flotation of Fully Liberated Low Grade Copper-Nickel Ore
by Haresh Kumar, Kirsi Luolavirta, Saad Ullah Akram, Hassan Mehmood and Saija Luukkanen
Minerals 2021, 11(3), 328; https://doi.org/10.3390/min11030328 - 21 Mar 2021
Cited by 2 | Viewed by 2645
Abstract
Low grade sulfide ores are difficult to process due to their composite mineralogy and their fine grained dissemination with gangue minerals. Therefore, fine grinding of such ores becomes essential to liberate valuable minerals. In this research, selective flotation was carried out using two [...] Read more.
Low grade sulfide ores are difficult to process due to their composite mineralogy and their fine grained dissemination with gangue minerals. Therefore, fine grinding of such ores becomes essential to liberate valuable minerals. In this research, selective flotation was carried out using two pitched blade turbine impellers with diameters of 6 cm and 7 cm to float copper and nickel. The main focus of this research was to generate optimum hydrodynamic conditions that can effectively separate nickel and copper from gangue minerals. In addition, we investigated the effects of superficial gas velocity, impeller speed, bubble size distribution, and bubble surface area flux on the flotation recovery and rate constant. The results demonstrated that a 7 cm impeller comparatively produced optimum hydrodynamic conditions that improved Cu-Ni recovery and the rate constant. The maximum copper and nickel recoveries in the 7 cm impeller tests were observed at 93.1% and 72.5%, respectively. However, a significant decrease in the flotation rate of nickel was observed, due to entrainment of nickel in copper concentrate and the slime coating of gangue minerals on the nickel particle surfaces. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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18 pages, 8329 KiB  
Article
Influence of Two Mass Variables on Inertia Cone Crusher Performance and Optimization of Dynamic Balance
by Jiayuan Cheng, Tingzhi Ren, Zilong Zhang, Xin Jin and Dawei Liu
Minerals 2021, 11(2), 163; https://doi.org/10.3390/min11020163 - 04 Feb 2021
Cited by 5 | Viewed by 3248
Abstract
Inertia cone crushers are widely used in complex ore mineral processing. The two mass variables (fixed cone mass and moving cone mass) affect the dynamic performance of the inertia cone crusher. Particularly the operative crushing force of the moving cone and the amplitude [...] Read more.
Inertia cone crushers are widely used in complex ore mineral processing. The two mass variables (fixed cone mass and moving cone mass) affect the dynamic performance of the inertia cone crusher. Particularly the operative crushing force of the moving cone and the amplitude of the fixed cone are affected, and thus the energy consumption of the crusher. In this paper, the process of crushing steel slag is taken as a specific research object, to analyze the influence of two mass variables on the inertia cone crusher performance. A real-time dynamic model based on the multi-body dynamic (MBD) and the discrete element method (DEM) is established. Furthermore, the influence of the fixed cone mass and moving cone mass on the operative crushing force, amplitude and average power draw are explored by the design of simulation experiments. The predictive regression models of inertia cone crusher performance are obtained using response surface methodology (RSM). After increasing the fixed cone mass, the optimized amplitude, average power and moving cone mass are decreased by 37.1%, 33.1% and 10%, respectively, compared to without the adjustment. Finally, a more effective dynamic balancing mechanism of inertia cone crusher is achieved, which can utilize the kinetic energy of a balancer, and minimize the mass of the fixed and moving cone. The fixed cone mass and moving cone mass of a balancing crusher are decreased by 78.9% and 22.8%, respectively, compared to without the balancing mechanism. Full article
(This article belongs to the Special Issue Process Optimization in Mineral Processing)
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