Semi-autogenous Grinding Research Articles

Fuzzy Logic Control On a SAG Mill

The paper will present a case where fuzzy logic was the logical choice to improve performances of a semi-autogenous grinding (SAG) mill. The SAG mill stability had to be improved and throughput increased. The process is multivariable, strongly non-linear, and before implementing this system, the operators were actively manipulating many variables with varying success depending on operator experience and occurring disturbances.

A practical and rigorous approach for the integration of sustainability principles into the decision-making processes at minerals processing operations

In the mining industry, high-level commitments to adopt sustainability have been made at the corporate levels of mining companies, but there continue to be problems when attempts are made to adopt these high-level sustainability aspirations and translate them into appropriate targets and methods at the more-specific operational level. The integration of sustainability principles into day-to-day mineral processing operational decision-making processes has unique challenges that are not addressed adequately by current tools and methodologies.A proposed methodology to achieve integration of sustainability at the operational level will direct the systematic and rigorous identification and qualification of sustainability issues and opportunities in an operation. The methodology, starting from a sustainability point-of-view rather than an operational one, guides the identification of process issues (“problems”) and opportunities by examining the operation, unit-by-unit, similar to a HAZOP process. Each issue or opportunity is qualified according to its measurability, scopes of impact and consequences so that it may be understood fully and the correct engineering problems are formed.The methodology has been tested with two case studies at minerals processing operations. At one site, the methodology identified a dust issue which had considerable business risks (loss of valuable product) compared to conventional engineering analysis processes. The other site also benefited from using the methodology as an opportunity to improve the milling circuit between the semi-autogenous grinding (SAG) mill and flotation circuit was identified. The opportunity not only showed a potential to improve the operational efficiency of the units concerned, but also potential improvements in water and energy (both direct and embodied) efficiency. It was important to utilise the holistic approach of the methodology in the identification of opportunities at this site; the goals of the operation showed a strong coupling between water and energy issues which would be difficult to overcome using the operation’s current organisational model which deals with such issues separately of each other.

Characterization and Modeling of Semi-Autogenous Mill Performance Under Ore Size Distribution Disturbances

AbstractAdvance control of semiautogenous (SAG) grinding has become a major issue for mining companies. SAG mills are very complex systems involving important nonlinearities and unmeasured disturbances which make the process very difficult to control. In the last decades approaches varying from decentralized PID control to multivariable predictive control have been applied to control of SAG mills with variable success; at the same time, new sensors has been developed with the aim to provide real time measurements of important variables currently unmeasured. The recent availability of new measurements, such as ore size distribution, has faced control engineers with the problem of obtaining new models, and designing new control algorithms capable of both, providing mathematical relations describing SAG mills’ behavior, and incorporating the new measurements in determining the control law. In this work, real time measurements obtained using a WipFrag® visual sensor are used in order to obtain a qualitative characterization and a dynamic model of SAG mill's performance when faced to disturbances in the ore size distribution. Results obtained show that the two parameters of the Rosin-Rammler distribution, n and xc, delivered by WipFrag® are the best option for characterizing the ore size distribution. Modeling results show that including the information regarding ore size distribution reduces the mean absolute error from 2.91% to 2.33% with respect to the case when only the feed rate and the speed of the mill are used to obtain the model.

Time delay neural network modeling for particle size in SAG mills

Particle size is a very important variable in semi-autogenous grinding processes. It is desirable to measure the variable efficiently or even predict its variations in advance. In this paper, the time delay neural network model is developed to predict the feed particle size of a semi-autogenous grinding mill, and the Levenberg–Marquardt algorithm is used to train the network. Results show that the model predicted values fit well with the industrial operating data. The proposed model can predict the particle size in advance and allow adequate time to take corrective actions during abnormal operations, and therefore provide a great advantage in monitoring and control of the industrial processes.

Inferential measurement of SAG mill parameters V: MPC simulation

This paper discusses a case study application of inferential measurement models for semiautogenous grinding (SAG) mills and is the last in a five-part series on Inferential Measurement of SAG Mill Parameters. Inferential measurements of SAG mill discharge and feed streams and mill rock and ball charge levels, detailed earlier in the series, are utilised in a simulation environment. A multi-variable, model predictive (MPC) controller simulation is developed from plant data and utilised to investigate the potential of utilising the inferential models in a mill charge control strategy. An operating curve is generated and discussed in terms of possible utilisation in conjunction with an MPC controller. The results are encouraging and potential avenues for further research are discussed.

Inferential measurement of sag mill parameters IV: Inferential model validation

This paper discusses a case study application of inferential measurement models for semiautogenous grinding (SAG) mills and is the fourth paper in a series of five papers on inferential measurement of SAG mill parameters. The development of the inferential measurement models of SAG mill discharge and feed streams and mill rock and ball charge levels, detailed earlier in the series, is summarised here. The models are then tested on plant data for validation and analysis. Model characteristics are explored to highlight model sensitivity and relative uncertainty. The results are encouraging while limitations are noted and potential avenues for further research are discussed.

Alternative ways of coupling particle behaviour with fluid dynamics in mineral processing

Research in particulate multiphase hydrodynamics is especially important in mineral processing applications that involve complicated physical processes and complex geometry. Numerous numerical methods have been developed to address the coupling physics. However, there is no single solution for all applications, especially after considering computational costs and model accuracy.This article presents alternative numerical coupling approaches to capture the physics of interest. A one-way coupling of conventional grid-based CFD with discrete element method (DEM) is applied to simulations of slurry pumps. FLUENT is used to compute the fluid field in the pump, which is imported into our DEM code. The DEM is used to capture dynamics of the detailed behaviour of individual solid particles, including inter-particle collisions and particle impacts into structure (boundaries).A Lagrangian–Lagrangian multiphase model is proposed for simulation of dense particulate flows in a grinding mill. This work is motivated by developing totally meshfree approaches for particulate flows due to complex and rotating geometry in many pieces of equipment in the mining industry. The particle-based multiphase model is an integration of DEM with smooth particle dynamics (SPH). SPH is extended to the multiphase version where an extra variable, volume fraction, is introduced into the governing equation in order to account for interpenetrating multiphase fluid dynamics. The interaction between the solid particles and the fluid phase consists of three contributions: volume fraction, pressure and drag force. The time stepping scheme can be either explicit Euler for speed-up or lower order Runge–Kutta for more accuracy, and the time step is controlled by the Courant condition. The model is applied to a preliminary study of a semi-autogenous grinding mill.

Multivariable Model Predictive Control of a Simulated SAG plant

This work presents the dynamic simulation and a multivariable predictive control strategy for a semi-autogenous grinding (SAG) plant. Models for SAG Mill, crusher and hidrocyclones have been integrated to simulate a SAG circuit. Data obtained from an industrial cooper concentrator has been used to estimate the main parameters of the dynamical models. The control strategy considers two levels: stabilizing and optimizing levels. The stabilizing level is based on a Model Predictive Control strategy with restrictions. In order to solve the optimization problem posed by this strategy, a standard Linear Programming solver has been selected. The optimizing level maximizes Power Draw using an online gradient estimation of the non-linear function between Power Draw and mill Hold Up. The results show that is possible to operate the SAG Mill in the optimal zone, compensate unmeasurable disturbances and maximize throughput without violating operational constraints. Moreover, the proposed control strategy has a modular structure; therefore its implementation can be carried out by parts. All the work has been done using Matlab® and the simulation platform Simulink®.

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.

Dynamic modelling and simulation of semi-autogenous mills

This paper presents a dynamic simulator of the semi-autogenous grinding operation deduced from first principles coupled to an on-line parameter estimation scheme able to simulate industrial operations for control purposes. Model equations are based on conventional non-stationary population balance approach to develop the necessary dynamic model of the semi-autogenous mill operation. The model is able to predict the time-evolution of key operating variables such as product flow rate, level charge, power-draw and load position, as function of other important variables such as mill rotational speed and fresh feed characteristics. The set of ordinary differential equations was solved using MATLAB/SIMULINK as a graphic programming platform, a very helpful tool for understanding the grinding phenomenon. Using an on-line parameter estimator, the simulator was tested and validated at an 1800 t/h copper–ore mill showing the effectiveness of the system to track the dynamic behaviour of the variables. It is now being used for the study of advanced control schemes.

State and Ore Hardness Estimation in Semiautogenous Grinding

Semiautogenous milling is difficult to control both because of its non-linear behavior and the effects of overloading due to increases in the ore charge or variations in ore characteristics. Advanced control strategies and operational change detection methods are thus in need of strengthening using techniques such as state estimation. Non-linear state estimation is a complex task for which various solutions have been proposed, such as the extended Kalman filter, the particle filter and the moving horizon estimator. In this study we present firstly a quantitative comparison of these solutions using a dynamic model validated with mill data. The results indicate that in addition to its lower computational requirements, the extended Kalman filter delivers the best performance in robustness and estimation error. Next, we propose a method for estimation of changes in the hardness of the ore feed that we test by simulation. Finally, we show that this method also works with real data.

Utilizing 3D Height Measurement in Particle Size Analysis

This paper introduces a novel approach for performing non-invasive particle size analysis for a material stream running on a standard conveyor belt. The measurements, carried out with a 3D laser scanner and a measuring belt weigher, are accurate, robust and real world physical measures. The 3D data obtained with the laser scanner enables more accurate analysis than the spatial monochrome or colour images that are commonly used in this field. In this paper the proposed analysis method is used in mineral processing application to get information about particle size distribution of the ore flow from the mine to a screening station at the surface. This information can be used to optimize operation of a semi autogenous grinding station used in Pyhäsalmi. However, with certain limitations, the analysis method can be utilized in different kinds of applications.

Semi-autogenous grinding (SAG) mill liner design and development

SAG mill liner development draws primarily on practical experience from SAG milling operations supported by computer-based modeling of charge motion in SAG mills and on established good design practice. Liner design needs to respond to the process aspects of mill liner action that are critical to good SAG mill performance, i.e., the impact of shell liners on the grinding action and of grates and pulp lifters on pulp discharge. In recent years, the trend in large SAG mills has been to use wide-spaced shell lifters with large lifter face angles, primarily to reduce packing and ball/liner damage, and to use larger, hence fewer, mill liner parts to reduce downtime at liner change-outs.

Smooth particle hydrodynamics: status and future potential

SPH is a powerful mesh free method that is now able to solve very complex multi-physics flow and deformation problems in a broad number of fields. This paper concentrates on the use of SPH to simulate a broad range of complex industrial fluid flow problems. These include free surface fluid flow for the generation of digital content, geophysical flows such as volcanic lava flows and tsunamis, several types of die casting (gravity, high pressure and ingot casting), resin transfer moulding and flow in porous media, mixing of particulates in liquid, pyrometallurgy and slurry flow in semi-autogenous grinding mills. The strengths and weaknesses of SPH will be explored and future opportunities for using the method to make major modelling advances are discussed.

Flotation of fine particles of Egyptian ground calcium carbonate as added value of filler in some industries

A flotation process is presented and the work carried out to find optimum conditions to minimise the colouring material in ground calcium carbonate is described. The feed material is the overflow product from a hydrocyclone, which results from using a Denver attritioning machine with semi-autogenous grinding for 1 h at 1:1 ore/water ratio. By using sodium silicate as deprassant and oleic acid as collector with pH 9, the iron content (as colouring material impurities) is decreased from ∼0·9 in the original sample to ∼0·45 in the rougher concentrate. However, by cleaning the rougher concentrate, the iron content is decreased to 0·26%.

Slurry flow in mills with TCPL — An efficient pulp lifter for ag/sag mills

The difficulties associated with slurry transportation in autogenous (ag) and semi-autogenous (sag) grinding mills have become more apparent in recent years with the increasing trend to build larger diameter mills for grinding high tonnages. This is particularly noticeable when ag/sag mills are run in closed circuit with classifiers such as fine screens/cyclones. Extensive test work carried out on slurry removal mechanism in grate discharge mills (ag/sag) has shown that the conventional pulp lifters (radial and curved) have inherent drawbacks. They allow short-circuiting of the slurry from pulp lifters into the grinding chamber leading to slurry pool formation. Slurry pool absorbs part of the impact thus inhibiting the grinding process. Twin Chamber Pulp Lifter (TCPL) — an efficient design of pulp lifter developed by the authors overcomes the inherent drawbacks of the conventional pulp lifters. Extensive testing in both laboratory and pilot scale mills has shown that the TCPL completely blocks the flow-back process, thus allowing the mill to operate close to their design flow capacity. The TCPL performance is also found to be independent of variations in charge volume and grate design, whereas they significantly affect the performance of conventional pulp lifters (radial and curved).

A multi-input-single-output smith predictor for feeders control in SAG grinding plants

The accurate control of feeders in semiautogenous grinding(SAG) mills plays an important role for obtaining good operational results. This brief presents the design of a Smith predictor for multi-input-single-output (MISO) systems, representing a set of feeders in a SAG plant. The design considers the special characteristics of the application, as well as issues like performance and robustness of the proposed controller. Experiments carried out at an industrial plant, under several operational conditions, demonstrate the effectiveness of the proposed strategy compared to the one based on a single proportional-integral derivative (PID) controller.

Methodologies for the evaluation of grinding media consumption rates at full plant scale

Due recognition of the significant impact of the cost of grinding media on the overall economics of comminution facilities worldwide has created the need for reliable, practical methodologies to compare—over extended control periods—different operating conditions, arising from eventual changes in ore type, ball supplier or simply, a trial of new products from the same supplier. The current publication describes the main aspects to be considered in the planning and execution of a full scale evaluation campaign, the actual data to be recorded and the required calculation routines, including the theoretical framework justifying their applicability. The Linear Wear Model, herein described, provides a theoretical framework for the best estimations of comparative grinding media wear performance (in the absence of ball breakage) in any given application, on the basis of the Specific Wear Rate Constant, k d E (μm/(kW h/ton)), derived from the Specific Consumption Rate (gr/kW h), corrected by actual make-up ball size (mm). When significant ball breakage is to be expected—as in semiautogenous grinding (SAG) applications—an expanded, conceptual model, based on pilot Drop Ball Testing (DBT) results is gaining acceptance as a way to incorporate breakage as a possible media consumption mechanism. Ideally, evaluations should be conducted in parallel grinding sections, in order to have the option of establishing multiple sequential, concurrent or cross-reference comparisons. The evaluation period should cover at least 6 months after the complete ‘purge’ of the string of balls being substituted, which may well take from 3 to 6 months. As a result, the evaluation period required for reliable conclusions should typically exceed 9–12 months of fairly undisrupted, normal operation. The methodologies here proposed make intensive use of Moly-Cop Tools, a software package developed by the international Moly-Cop Grinding Systems organization (formerly, ARMCO Worldwide Grinding Systems) with the specific purpose of helping process engineers characterize and evaluate the operating efficiency of any given grinding circuit, following standardized methodologies and widely accepted evaluation criteria.

Inferential measurement of SAG mill parameters III: inferential models

This paper discusses inferential measurement models for semiautogenous grinding (SAG) mills. Inferential measurements of SAG mill discharge and feed streams and mill rock and ball charge levels are obtained utilising process measurements and recognised process simulation models. Inferential models of recirculating load and cyclone underflow split are also presented. Results for the mill inventories and process streams are validated against reference simulation model data. Uncertainty analyses are conducted to assess the influence of the various model parameters. Mill weight based estimates for mill inventory are shown to be the least uncertain. The results suggest that regular calibration of oversize crusher and primary cyclone feed instrumentation, regular measurement of the SAG mill discharge screen aperture, oversize crusher gap setting and process water specific gravity and careful fitting of the SAG mill discharge grate model parameters will minimise uncertainty in the inferential models.

Application of a rock abrasion model to pilot-plant and plant data for fully and semi-autogenous grinding

(2002). Application of a rock abrasion model to pilot-plant and plant data for fully and semi-autogenous grinding. Mineral Processing and Extractive Metallurgy: Vol. 111, No. 1, pp. 39-43.