Grinding Circuit Research Articles

A novel approach to the geometallurgical modelling of the Collahuasi grinding circuit

Compañía Minera Doña Inés de Collahuasi SCM initiated the development of a new geometallurgical model to characterize its Rosario deposit in terms of its comminution circuit capacity and flotation performance. The comminution component of the model is now complete and is described in detail in this article. The model uses a combination of simulation and power-based approaches to relate ore hardness and flotation feed size to grinding circuit throughput. Ore hardness values are provided by Collahuasi’s block model which has been populated with ore characterisation data derived from Bond ball work index tests, JK drop-weight tests and SMC Tests ® on diamond drill cores. The influences of planned and unplanned maintenance downtime are taken into account both in terms of frequency and duration. The accuracy of the model is demonstrated using weekly production data taken from the period January–December 2008, showing an average relative error of 5.2% and an R 2 value of 0.95. The model is now in successful routine use at the mine for planning purposes and is currently in the process of being further developed to incorporate the response of the flotation circuit.

Disturbance observer based multi-variable control of ball mill grinding circuits

Ball mill grinding circuits are essentially multi-variable systems characterized with couplings, time-varying parameters and time delays. The control schemes in previous literatures, including detuned multi-loop PID control, model predictive control (MPC), robust control, adaptive control, and so on, demonstrate limited abilities in control ball mill grinding process in the presence of strong disturbances. The reason is that they do not handle the disturbances directly by controller design. To this end, a disturbance observer based multi-variable control (DOMC) scheme is developed to control a two-input-two-output ball mill grinding circuit. The systems considered here are with lumped disturbances which include external disturbances, such as the variations of ore hardness and feed particle size, and internal disturbances, such as model mismatches and coupling effects. The proposed control scheme consists of two compound controllers, one for the loop of product particle size and the other for the loop of circulating load. Each controller includes a PI feedback part and a feed-forward compensation part for the disturbances by using a disturbance observer (DOB). A rigorous analysis is also given to show the reason why the DOB can effectively suppress the disturbances. Performance of the proposed scheme is compared with those of the MPC and multi-loop PI schemes in the cases of model mismatches and strong external disturbances, respectively. The simulation results demonstrate that the proposed method has a better disturbance rejection property than those of the MPC and PI methods in controlling ball mill grinding circuits.

Optimization of comminution circuit simulations based on genetic algorithms search method

Comminution simulators are extensively used by mineral processing engineers for plant design and optimization purposes. Recently, there had been a great progress in developing new and more powerful optimization methods such as Genetic Algorithms (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Tabu Search Algorithm (TSA). Simulation optimization is required if one wants to find the best steady-state values of important process variables. In this paper, the authors investigated the integration of GA optimization algorithm with a pre-existing grinding circuit simulator called Ball Milling Circuits Simulator (BMCS) in MATLAB™ environment. The BMCS code has been written in ANSI C language and has been validated against real industrial grinding circuit data sets. Various C modules of the BMCS grinding software were restructured under a new single source code file so that it can be imported into MATLAB. Then, a number of input simulation data were identified and selected as possible process variables (e.g., solids flow rate, water addition rate, and number of operating cyclones) which must be optimized in order to achieve a pre-defined process objective (e.g., a specific d 80 of circuit output). The obtained results show that BMCS simulation trials can be successfully optimized by applying evolutionary algorithms via MATLAB toolboxes. This allows the mineral processor to perform automatic repetitive simulations to find the possible solutions of the problem at hand quickly.

Applying traceability to grinding circuits by using Particle Texture Analysis (PTA)

LKAB has started a new pelletizing plant at Malmberget, where the raw material will be a mix of ores from Kiruna and Malmberget. The new plant necessitated an investment in a new grinding section in the concentrator. As usual, the new section has larger mills. It also lacks the wet cobbing stage present in the old sections. Comparing the analysis data from the new grinding section with the old grinding sections it shows that they give similar results. There are slight variations; the older mills produce a steeper final particle size distribution. Also, it appears that the new mills are more efficient, since they have higher calculated grindability indices. To better understand the differences between the sections, and the process implications of the new grinding section, a combination of Particle Texture Analysis (PTA) and the statistical method multivariate data analysis (MVDA) is used. It shows that it is possible to identify and follow systematic changes in the particle morphology of the mill products. Also, that there are differences in process mineralogical aspect between the old and new grinding sections.

Jhamarkotra phosphate ore processing plant

AbstractABSTRACT: Low grade phosphate ore of Jhamarkotra that analyzes 16.5% P~2~O~5~ is upgraded to 34% P~2~O~5~ by a two stage flotation process after size reducing the ore to 90% passing through 200mesh using conventional equipment such as jaw and cone crushers followed by ball mills. Re-engineering the flotation circuit reduced the power consumption from 55 kWh per metric ton of ore treated to 50 kWh. Incorporation of roller press in the grinding circuit resulted into further reduction of power consumption to 32 kWh per metric ton of ore treated.

Jhamarkotra phosphate ore processing plant

ABSTRACT: Low grade phosphate ore of Jhamarkotra that analyzes 16.5% P~2~O~5~ is upgraded to 34% P~2~O~5~ by a two stage flotation process after size reducing the ore to 90% passing through 200mesh using conventional equipment such as jaw and cone crushers followed by ball mills. Re-engineering the flotation circuit reduced the power consumption from 55 kWh per metric ton of ore treated to 50 kWh. Incorporation of roller press in the grinding circuit resulted into further reduction of power consumption to 32 kWh per metric ton of ore treated.

Characterisation and Pre-concentration of Chromite Values from Plant Tailings Using Floatex Density Separator

Classification is a method of separation of fines from coarse particles and also lighter particles from heavier particles. The conventional classifiers, such as, hydrocyclone or mechanical classifiers, decreases the efficiency of the grinding and concentration circuits due to their imperfect separation. In the process of improving the efficiency of classification, a device that has been gaining popularity in recent years is the teeter-bed or hindered-bed separator such as Floatex density separator. Generally for processing chromite ores, different types of gravity methods are employed after crushing, grinding followed by classification. The Tata Steel Chrome Ore Beneficiation (COB) plant is generating 50 tph of tailings assaying 17% Cr2O3. A critical review on practice of the plant operating personnel is concerned in the grade-recovery characteristics of unit operations. But separation insight and influence of different operating and process parameters are essential to understand and control the process. The objective of the present investigation was to study the effect of the important operating variables on floatex density separator and preconcentration of COB plant tailings for the further beneficiation process and found that significant removal of iron bearing mineral such as goethite and silica is possible using FDS in a single stage operation. The maximum of 83% recovery of chromite is possible with 22 to 23% Cr2O3 content and thus obtained FDS underflow is suitable for flotation circuit. A low teeter water flow rate with a high bed pressure removes iron bearing mineral like goethite efficiently in an FDS.

Implementation of a Multivariable Controller for Grinding-Classification Process

The operation and control of grinding-classification circuits is usually based on single PID loops, and although it is recognized as a multivariable process with strong interactions, mainly due to their slurry recirculation, it is a fairly stable process from the operational point of view. This paper describes the implementation of Robust Multivariable Predictive Control Technology (RMPCT) in Codelco Chile El Teniente Division, leading ultimately to the control of a grinding-classification circuit, using the sump that separates the ball mill and the classification stage as a transients disturbance filter as well as finding an optimal operating point based on an objective function for maximizing throughput with a specified product size. Additionally, the implementation is done based on closed loop process identification, given an initial “seed model” that was duplicated on similar grinding circuits, reducing the controller implementation time.

Grinding mill circuits — A survey of control and economic concerns

A worldwide survey on grinding mill circuits in the mineral processing industry was conducted. The aims of this survey are to determine how milling circuits are currently controlled, and to find out how key process variables are linked to economic benefits. The survey involves background information on the circuits, the choice of controlled and manipulated variables, the economic impact of the controlled variables, adopted control technologies and assessment of control performance. Sixty-eight responses were received. Survey results are contrasted to the milling control literature.

Optimization of a grinding and classification circuit of a magnetite ore processing plant through computer simulation

Computer simulation and mineral modeling was applied to the optimization of a grinding circuit in a plant processing 256 t/h magnetite. These tools were used to develop a grinding and classification configuration to decrease the grade of silica in the magnetite concentrate, which is produced by the plant. Empirical grinding and classification models were finely tuned using plant experimental data. The JKSimMet™ 5.0 software was used to simulate the grinding and classification units. By applying changes in the original circuit, a throughput increment of 100% was achieved with an important reduction in the energy consumption. The silica content in the magnetite concentrate can be decreased by regrinding the coarse fraction of fine screens into a separate ultrafine grinding unit instead of returning this flow to the ball grinding mills.

Detection and identification of ore grindability in a semiautogenous grinding circuit model using wavelet transform variances of measured variables

A reduced dimension dynamic model subject to random disturbances for a semiautogenous grinding (SAG) circuit is developed that is able to handle changes in the characteristics of the new feed ore. This dynamic model, which is adjusted using data from a large mineral processing plant, has been developed with the objective of being useful for design and testing of fault identification and detection (FDI) systems, soft-sensors, automatic control systems, etc. The reduced dimension is a requirement in order to be able to obtain in a reasonable time statistical results to evaluate such systems. In this paper this SAG circuit dynamic model is used to test a method for detecting changes and identifying the grindability of the ore being processed by the SAG circuit. The method used — based on the variance of the continuous wavelet transform of measured circuit variables — incorporates improvements of a previous method. Results show that a step change of new feed ore is detected in about 30 to 80 min depending on the grindability change. This result may be considered to be adequate when taking into account that the response time for the mill hold-up to attain a new equilibrium value after the ensuing transient is of about 3 h. Identification of grindability in stationary operation gives near 100% of correct classification under the analysed conditions. The sensitivity of the FDI method to changes in circuit characteristics is also assessed and acceptable results are obtained.

Modeling of grinding and classification circuits as applied to the design of flotation processes

This study reports on the preparation of linear models of grinding, grinding–classification, classification–grinding, and classification–grinding–classification circuits based on material balances supported by population balances. For these procedures, particles were described by size and chemical composition, and the parameter ϕ is introduced which represents the fraction of one class of particles which delivers material to another. An index is introduced to evaluate the effect of the proposed circuits on the characteristics of the floatability of the material. The methodology can be amplified to include other types of circuits, and the models can be used to evaluate, compare, and select grinding circuits with classification. As examples of their application, some of these models are used for the synthesis of flotation circuits, following the methodology employed by [Cisternas, L., Méndez, D., Gálvez, E., & Jorquera, R. (2006). A MILP model for design of flotation circuits with bank/column and regrind/no regrind selection. International Journal of Mineral Processing, 79(4), 253–263] with some variations, showing how the selection of these circuits can affect the design and yields of a mineral processing plant.

Energy considerations in compressive and impact crushing of rock

A cone crusher and a vertical shaft impact (VSI) crusher were operated in closed circuit to compare the performance of the two different crushing machines. The crushers were operated in closed circuit with a 9 mm final screen aperture size. A comparison of capacity, size reduction and power draw shows that the VSI crusher is significantly more energy efficient than the cone crusher, and it produces significantly more fine material. The study also shows that the recirculating load is higher with the VSI than with the cone crusher. Compared to the cone crusher, the VSI product contained 65% more material smaller than 1 mm while at the same time consuming less power. An alternative energy measure was introduced to assess the value of feeding a finer product to a grinding mill. This measure suggests that a VSI can save 2–14% of the energy consumed in grinding, depending on the energy model used and the final product size. This estimate is in agreement with an energy saving of 11.8% observed in an iron ore application where VSI’s were introduced as a crushing step preceding the grinding circuit.

Prediction of Concentrate Grade in Industrial Gravity Separation Plant – Comparison of rPLS and Neural Network

Control of the concentrate quality is usually one of the main targets in the operation of mineral concentrator processes. Availability of the estimates of end product properties in advance – based on upstream process measurements – offers an opportunity to develop higher level control strategies for the unit processes. Here, the recursive PLS and adaptive neural network models are compared in the prediction of the concentrate grade at a gravity separation plant. The methods are applied in the Outokumpu Tornio Works Kemi Mine plant data. The chromite concentrate grade can be predicted relatively accurately based on the slurry properties measured in the grinding circuit. Accordingly, the predicted chromite grade decreases about 0.2 %-units when the slurry D50 passing size is increased by 10 %. This enables further development of the grinding control, especially the control of the slurry particle size, to meet the concentrate specifications.

A method for predicting the specific energy requirement of comminution circuits and assessing their energy utilisation efficiency

This paper presents a new approach for determining the specific energy requirement of tumbling mill (grinding) circuits. It is used to demonstrate that there is no significant difference between the energy utilisation efficiency of any of the grinding circuits of the plants studied. Laboratory test results are also presented which indicate that classifier efficiency and recycle load in closed ball mill circuits can have a significant influence on the apparent energy utilisation efficiency. The experimental data indicate that this is achieved through changes to the gradient of the size distribution of the final product.

Expert system based adaptive dynamic matrix control for ball mill grinding circuit

Ball mill grinding circuit is a multiple-input multiple-output (MIMO) system characterized with couplings and nonlinearities. Stable control of grinding circuit is usually interrupted by great disturbances, such as ore hardness and feed particle size, etc. Conventional model predictive control usually cannot capture the nonlinearities caused by the disturbances in real practice. Multiple models based adaptive dynamic matrix control (ADMC) is proposed for the control of ball mill grinding circuit. The novelty of the strategy lies in that intelligent expert system is developed to identify the current ore hardness and then select a proper model for ADMC. Compared with the various nonlinear DMC strategies, the approach can synthesize and analyze as many variables and status as possible to adequately and reliably identify the process conditions, and it does not introduce additional computational complexity, which makes it readily available to the industrial practitioner. Simulation results and industrial applications demonstrate the effectiveness and practicality of this control strategy.

Influência de variáveis operacionais no desempenho de classificador aerodinâmico

A classificação dinâmica a seco ocupa uma posição de destaque em circuitos de moagem de cimento e de diversos minerais industriais. Uma importante aplicação recente desse equipamento tem sido na adequação da proporção de material pulverulento (< 75 µm) contido em agregados miúdos (areias) para a construção civil, produzidos por britagem. O presente trabalho investiga a influência de uma série de variáveis no desempenho de um classificador Sturtevant, que opera em escala-piloto, visando a fornecer subsídios para a modelagem matemática. É demonstrado que o seu desempenho é significativamente influenciado pelo teor de umidade, pela freqüência de rotações e pela posição dos elementos de rejeição, sendo, apenas, marginalmente, afetado pela forma de partícula e taxa de alimentação de sólidos, dentro do intervalo estudado.

Application of model predictive control in ball mill grinding circuit

Grinding circuit needs to be stably controlled for high recovery rate of mineral ore and significant reduction of production cost in concentrator plants. Ball mill grinding circuit is essentially a multi-input–multi-output (MIMO) system with strong coupling among process variables. Simplified model with multi-loop decoupled PID control usually cannot maintain a long-time stable control in real practice. The response tests between four controlled variables (namely, product particle size, mill solids concentration, sump level and circulating load) and four manipulated variables (namely, fresh ore feed rate, mill feed water flow rate, pump speed and dilution water flow rate) are carried out to construct a four-input–four-output model of grinding circuit. Based on this modeling, constrained model predictive control (MPC) is adopted to handle such strong coupling system and evaluated in an iron ore concentrator plant. The variables are controlled around their set-points and a long-term stable operation of the grinding circuit close to their optimum operating conditions is achieved. More than three years’ operation in industry demonstrates the effectiveness and practicality of this control strategy.

Adaptive soft-sensors for on-line particle size estimation in wet grinding circuits

On-line particle size soft-sensors play an important role in the efficient operation of control systems in many industrial grinding plants. To cope with disturbances and changing operating points it will be necessary to adapt the soft-sensor parameters to the new conditions. This work proposes the use of constrained parameter estimation algorithms, in order to take into account some process prior knowledge and enhance the performance of the soft-sensor. Several experiments, using data taken from an industrial grinding circuit, illustrate the benefits of the proposed approach.

Supervisory expert control for ball mill grinding circuits

Stable control of particle size in ball mill grinding circuits is of great importance for the recovery of the valuable minerals, and the maximization of mill capacity is another main consideration in concentration plants. A supervisory expert control strategy is proposed to control product particle size and to improve fresh ore feed tonnage in grinding circuits. Expert control in supervisory level is developed to optimize the set–points for controllers in regulatory level. Mill solid concentration variable–ratio control, sump dilution water flowrate single–loop control and sump level loose control are carried out in regulatory level to reach the control targets. While the set–point modification by expert control for dilution water controller demonstrates good dynamic performance, the set–point adjustment for feed rate controller ensures a long-term stableness of particle size even ore hardness has changed. An increase of 10% in feed tonnage was achieved relative to other grinding circuits of similar capacity, running in parallel. More than four year’s operation demonstrates the control strategy’s practicality and reliability.