Closed Side Setting Research Articles

Centralized Finite State Machine Control to Increase the Production Rate in a Crusher Circuit

Crushing is a critical operation in mineral processing, and its efficient performance is vital for minimizing energy consumption, maximizing productivity, and maintaining product quality. However, due to variations in feed material characteristics and safety constraints, achieving the intended circuit performance can be challenging. In this study, a centralized control strategy based on a finite state machine (FSM) is developed to improve the operations of an iron ore crushing circuit. The aim is to increase productivity by manipulating the closed-side-setting (CSS) of cone crushers and the speed of an apron feeder while considering intermediate storage silo levels and cone crusher power limits, as well as product quality. A dynamic simulation was conducted to compare the proposed control strategy with the usual practice of setting CSS to a constant value. Four scenarios were analyzed based on variations in bond work index (BWI) and particle size distribution. The simulation results demonstrate that the proposed control strategy increased average productivity by 6.88% and 48.77% when compared to the operation with a constant CSS of 38 mm and 41 mm, respectively. The proposed strategy resulted in smoother oscillation without interlocking, and it maintained constant flow rates. This ultimately improved circuit reliability and predictability, leading to reduced maintenance costs.

Application of design of experiments (DoE) in evaluating crushing-screening performance for aggregates production

The configuration and the interaction between the crushers and screens enable aggregate producers to produce products that are in accordance with the applicable product certification. However, the performance of the system is seldom optimized for the given conditions and market demand. This paper aims to describe the experimental work and the results of quantifying the crusher and screen performance by applying the design of experiments (DoE) in a full-scale tertiary crushing process of an aggregate production plant with both standard belt-cut sampling as well with continuous processes monitoring. The results show the application of a simplified modelling approach using the design of experiments for the evaluation of crusher performance and circuit performance using experimental data. The research output is able to demonstrate that there exists an interaction effect between the crusher closed side setting and eccentric speed that previously has not been identified with traditional methods. The quantification of interaction between crusher and screen individual performance to the process performance has been demonstrated with both belt-cut samples and continuous process monitoring. Using a DoE, digital experiments can be planned for mapping and quantifying the performance of aggregate production.

Crushing characteristics and performance evaluation of iron ore in a cone crusher: A numerical study

In this study, the DEM (Discrete element method) bonded particle model is constructed to simulate the crushing process of iron ore based on the Apollonian sphere packing (ASP) method in a cone crusher. The effects of operation parameters (eccentric speed (ω), closed side setting (lcss) and eccentric angle (α)) on the macroscopic characteristics (throughput, specific energy, crushing rate, product size distribution) and microscopic characteristics (mechanical behaviors between sub-particles and between meta-particles) are systematically investigated, and their quantitative correlations are established. Meanwhile, the corresponding mechanisms have been identified by analyzing the circulation time. The results show that with alterations in operation parameters, the variation trend between production size distribution and crushing rate is consistent, while opposite trend between throughput and crushing rate is formed. The crushing rate is higher and the mantle wear is more severe when the normal/tangential forces exerted on particles are larger. The effects of the eccentric speed on the residence time of particles in the crushing chamber can be indicated by its influence on the number of circulations, while the effects of the closed side setting and eccentric angle can be reflected by changing the volume of the crushing chamber. The increase of particle residence time is beneficial for improving the crushing rate, while it simultaneously reduces the throughput.

Optimizing processing parameters of stone crushers through Taguchi method

Present paper showcase the optimization of crushing parameters through Taguchi methods to improve the production yield of the aggregate produced. The main objective is to investigate the impact of various crushing parameters like feed rate to jaw crusher and eccentric speed of Jaw crusher, closed side setting and throw in cone crusher. For optimization, Taguchi Design of Experiment (DOE) have been perform by considering eccentric speed, feed rate, closed side setting & throw as the process parameters.L09 orthogonal array have been formed and ANOVA technique is used to evaluate the parameters which actually affect the objective function. The selected parameters are optimized to get the desired result using statistical method of Signal-to-Noise ratio. Results shows that closed side setting put the major emphasis on the production yield which are represented by cumulative weight fraction percentage in the work. Eccentric speed, throw and feed rate of rock aggregates does not have notable influence on same.

Geometric analysis of cone crusher liner shape: Geometric measures, methods for their calculation and linkage to crusher behaviour

This paper presents a set of related methods for performing a computational geometry analysis of a cone crusher shape that provides geometric information for use in understanding cone crusher flows and breakage and their variation with key crusher geometric parameters. Algorithms that are able to calculate geometric measures such as the variation of the cross-sectional area available for flow at each height in the crusher, open and closed side areas, geometry based reduction ratios, eccentric throw as well as the open and closed side setting are described. These are demonstrated in a worked example of a specific short head cone crusher showing how systematic variation in the cone vertical displacement and eccentric angle affects geometric measures. Both the OSS and CSS are found to vary almost linearly with cone height and eccentric angle. The eccentric throw is found to be nearly invariant for changes in cone height but to vary strongly with eccentric angle. There is close to a linear relationship between variation in choke area (representing throughput) and the CSS (representing maximum product size) when the cone height is changed. In contrast, the choke area is almost independent of the CSS when the eccentric angle is varied meaning that throughput and breakage top size are independently controllable. Linear and area-based estimates of the reduction ratio can be used to bound the likely breakage performance. This analysis can be used in conjunction with DEM models to help to guide the evolution of liner configurations.

DEM Simulation of Laboratory-Scale Jaw Crushing of a Gold-Bearing Ore Using a Particle Replacement Model

The Discrete Element Method (DEM) is a numerical method that is able to simulate the mechanical behavior of bulk solids flow using spheres or polyhedral elements, offering a powerful tool for equipment design and optimization through modeling and simulation. The present work uses a Particle Replacement Model (PRM) embedded in the software EDEM® to model and simulate operation of a laboratory-scale jaw crusher. The PRM was calibrated using data from single particle slow compression tests, whereas simulations of the jaw crusher were validated on the basis of experiments, with very good agreement. DEM simulations described the performance of the crusher in terms of throughput, product size distribution, compressive force on the jaws surface, reduction ratio, and energy consumption as a function of closed side setting and frequency.

Simulating a laboratory-scale cone crusher in DEM using polyhedral particles

Until now computer simulation has already successfully assisted in improving the design and operation of cone crushers in the mining and aggregate industries. However, simulations using the discrete element method, coupled to realistic breakage models, are the next step towards designing confidently these machines in a fully virtual environment. The work shows the application of a novel breakage model fitted using single-particle breakage information and polyhedral particles to simulate a laboratory-scale cone crusher. Simulations of crushing three materials with widely different characteristics were in good agreement with experiments for throughput and only reasonably good for specific energy and product size. Sensitivity of simulations to closed side setting, stroke and frequency showed good qualitative agreement to experience. Simulations of crushing of blends containing mixtures of tough and soft components then demonstrated that crusher throughput does not drop proportionally to the increase in the amount of tough material in the feed.

Machine learning approach to handle data‐driven model for simulation and forecasting of the cone crusher output in the stone crushing plant

AbstractGrinding and crushing of stones and other particles are associated with various significant applications. Different sectors have continuously evolved in this area. In the crushing industry, plants function under strict conditions, many of which involve grinding materials. Therefore, various factors are responsible for how the crushers perform. This research investigated the ability of the adaptive neuro fuzzy inference system (ANFIS) to simulate the effects of throw, eccentric speed, closed side setting, and the size of the particle on crusher output. The developed simulation model was adjusted and authenticated alongside the experimental data of the investigated parameters. The model's performance was computed by the use of several prediction criteria skills. The results of the study indicated that the developed ANFIS model could simulate the Cone crusher output and give a dependable forecast of the cumulative weight fraction. The researchers resolved that the model fostered was a suitable instrument for the onsite cone crusher assessment.

Evaluation and prediction of reliability on liner based on time-dependent theory

Considering the evolution of structure parameters of cone crusher, and based on the continuous-time and Ito Lemma, a model of evaluation and dynamic forecast on liner’s reliability is studied in this paper. The performance of liner is fluctuant due to the uncertain factors (such as wear and adjustment of closed side setting) and gradually degraded. The degradation will influence the safe usage and reliability of liner. Degradation process of liner can be described by stochastic process and is modeled in geometric Brownian motions (GBM), and it is predicted with experimental data from a PYGB1821 cone crusher. The results show that the deviation between the predicted value and the experimental data is 2.62%. The model is valid on assessing the reliability of the liner, and the liner can be designed with the specified reliability value at the given time.

Dynamic modeling and simulation of a SAG mill-pebble crusher circuit by controlling crusher operational parameters

A semi-autogenous (SAG) or autogenous mills (AG) circuit commonly comprises a pebble (cone) crusher to deal with the critical size particles. The pebbles crusher is often oversized, and thus not fully utilized. The hypothesis put forward in this paper is that active control of the cone crusher’s eccentric speed and closed side setting (CSS) can increase throughput and/or energy efficiency of the SAG circuit. To verify this hypothesis, a dynamic model of a SAG mill-pebble crusher circuit was implemented. The dynamic unit models are based on results presented by several different researchers, whose results here have been combined and implemented in Matlab/Simulink.Previous research shows that by controlling the cone crusher operational parameters, the product particle size distribution (PSD) can be altered during operation. However, few papers have been published about whether the changes of the pebbles crusher’s product PSD, lead to a higher performance of the SAG circuit. This paper examines the relations between the SAG mill and the pebble crusher in closed circuit while putting emphasis on controlling the pebble crusher in order to optimize the circuit throughput.

Analysis of cone crusher performance with changes in material properties and operating conditions using DEM

Discrete Element Method (DEM) simulation with non-round particles and including breakage has been used to understand the breakage behaviour and operating performance of an industrial scale cone crusher using a representative ore. The breakage model uses a replacement strategy and impact energy specific progeny size data from a Drop Weight Test (DWT). There is a strong variation in the breakage behaviour with height in the compression region as the differing profiles of the concave and mantle create five different regions with monotonically decreasing width and differing degrees of convergence between the surfaces. These control the rate of motion and the ability to load and break the particles, and determine whether high forces are generated via multi-particle stress chains or as single particle loading directly from the liner surfaces. The larger feed particles jam in the compression zone prior to breakage and cause observable obstruction to the flow of finer material and strong non-uniformity in the flow of product down the lower part of the mantle. Trends in the coarseness of product and changes in steady state throughput are identified with changes in material properties (rock breakage energy and friction coefficient) and crusher operating parameters (Closed Side Setting and crusher rotation rate).

Control oriented modeling of flow and size distribution in cone crushers

This work presents a dynamic model for prediction of flow and output size distribution of cone crushers. The main purpose of the model is for simulation of closed-loop control using the Closed Side Setting (CSS) and the eccentric speed (ω) as manipulated variables. The idea of modeling crushers as cascaded zones is adopted throughout this work. The capacity, the length, the stroke, and the compression ratio of each zone are taken into consideration. Simulation results are presented in the form of the Crusher Performance Map (CPM) and the dynamic response for production of different size classes to steps input in ω and CSS. The simulations also include operation with recycling of oversize output, as well as the input of mixed materials. As an example, closed-loop control of the ratio of the large-size output to the total size output was simulated.

Real-time algorithm for cone crusher control with two variables

Cone crushers are used in the mineral, mining, and aggregate industry for fragmentation of rock materials, minerals and ores. Systems used for controlling the Closed Side Setting (CSS) on cone crushers, and thereby the size reduction, are widely used to compensate for wear of the manganese crushing liners and to protect the machines from overloads. With a frequency converter also the eccentric speed in a cone crusher can be adjusted in real-time in addition to the CSS. The eccentric speed affects the dynamic interaction between the rock material and the crusher liners. Especially the number of compressions the material is exposed to is affected and also the local compression of the rock material is affected, thus the particle-size distribution of the product. Eccentric speed also affects crusher capacity. Real-time feedback data on the sellable product streams can be obtained by applying mass-flow sensors to the process. The adjustment of these two online parameters in real-time can result in an increased potential for production yield; however, a nontrivial optimization problem with a large solution space also arises. As the feed material also varies, the optimal setting for the parameters varies in time. Herein, we report the development of a monitoring and control system including a two variable online algorithm for the selection of the setpoint for eccentric speed with respect to the current CSS. The different product yields from the crushing plant were monitored by mass-flow meters and continuously evaluated by a fitness function. A model for the outcome of the crushing stage, with the two parameters eccentric speed and CSS, was fitted mathematically to the measurement data. However, since the process varies continuously, due to the wear of crushers and screens and feed material variations, the performance landscape is also continuously varying. Therefore, an Evolutionary Operation (EVOP) approach was adopted, wherein the variations are instead used to continuously find an operating point closest to the optimal. The developed algorithm was tested and evolved at a crushing plant for aggregates that produces around 400,000 tonnes aggregates per year. The algorithm was implemented in a computer that communicated with the frequency converter and retrieved data from ten mass-flow meters in the process. The operator was able to interact and supervise the system through a Human Machine Interface (HMI). The result is an algorithm that can determine the position and direction of a dynamic speed control to continuously improve the process-operation point. The magnitude of the improvement potential compared to a fixed speed operation is from 5% to 20%.

A comparative study between cone crushers and theoretically optimal crushing sequences

The supply of minerals, ores and aggregates are crucial for the continuous development of today’s society. With a rising world population, growing urbanization, and increasing standards of living, the performance and efficiency of existing crushers must be improved in order to meet the escalating demand on these products. The current paper thus presents a comparative study between existing cone crushers and theoretically optimal crushing sequences. Full scale experiments are conducted in order to examine the effects of Closed Side Setting (CSS), stroke, and eccentric speed on crusher output. The performance of the examined cone crusher is then compared against what is considered as theoretically optimal. The subsequent analysis shows that significant gains can be made in terms of both product yield and overall capacity by adjusting crusher operation depending on the conditions at hand, e.g. increasing the CSS while maintaining the same stroke or decreasing the eccentric speed. It is also shown that a mixture of breakages modes is more optimal than the sole application of one optimized breakage mode.

Modeling and Simulation of Cone Crushers

A generic structure for dynamic models of cone crushers is presented, in the form of a partial differential equation depending on both time and a spatial variable as well as the size distribution of the particles. Assumptions on the size classification of the flow through the crusher and the velocity of the particles enable modeling the effect of the main manipulated variables, i.e. closed side setting and rotational velocity. It is also shown how the model may be discretized and approximated by an ordinary differential equation. Simulations show that the model exhibits the expected behavior of a cone crusher. Notable is the effect of changing the rotational speed, which suggests that this variable is potentially valuable for improving the control of the crusher.

Algorithm for dynamic cone crusher control

Cone crushers are used in the mineral, mining, and aggregate industry for fragmentation of rock materials. Control systems for cone crusher settings are widely used for compensating for wear and protecting the machines from high pressure. However, these systems focus on the crusher and not the crushed products. By applying measurement devices on the process the crusher can be run optimally from the saleable products point of view (unlike most existing systems which only protect the machine) in each time. The measurement devices can be mass flow meters, e.g. conveyor belt scales. To analyze data from the process and convert them to a desired CSS value, an algorithm was developed. The developed algorithm is tested and evolved at a real crushing plant for aggregates. The algorithm was loaded into a computer which could communicate with the crusher control system, read data from three mass flow meters, and also interact with the operators. The computer was reachable over the Internet by the researchers at Chalmers and the algorithm was tuned and improved on-line. The result is an algorithm which was capable of providing CSS set-points to the automatic setting regulation system. The amount of saleable product from the crushing stage improved 3.5%, when not limited by the hydraulic pressure, compared to when a fixed closed side setting is used. The use of the algorithm automatically compensates for changes in the feed material and it also decreases the need for calibration of the underlying system.

Gyratory crusher model and impact parameters related to energy consumption

The objective of this research was to develop a mathematical model for gyratory crushers to help in the prediction of energy consumption and to analyze dominant parameters that affect this energy consumption. The development of a gyratory crusher model was achieved in the following three main stages: mathematical representation and coding of the crushing process; building an amperage constant model to derive an energy-scaling formula; and modifying the amperage constant model to represent a full-scale model. Due to their significant influence on feed-size distributions, two blasting parameters, i.e., burden and spacing, were considered. The crusher parameters that affect energy consumption were also identified. A case study of an operating dolomite mine was performed. The results indicated that by changing the burden, spacing and crusher closed-side setting, the overall (blasting and crushing) costs could be reduced by 4.7% to 7.9% annually. It can also be concluded that burden and spacing values have a linear positive relationship with the crusher energy consumption, while closed-side setting values have an inverse linear relationship with the energy consumption.

An empirical model for predicting flakiness in cone crushing

A fundamental understanding of the factors influencing particle shape is of central importance for optimisation of the output quality from crushing plants for aggregate production. The literature reports that the wear on and setting of a cone crusher influence particle shape, The fact that wear on and the setting of a cone crusher influence particle shape is considered common knowledge and is also reported in the literature. To date, no mathematical model for predicting particle shape has been presented. A novel model capable of predicting aggregate shape is presented in this paper. The particle flakiness model has two parameters: the average particle size of the feed and the closed side setting (CSS) of the crusher. A common method used for controlling the process flow in a crushing plant is also demonstrated. Detailed process knowledge is important in order to minimize the circulating load whilst still maximizing product quality. The model shows that the flakiness of the product can be estimated with knowledge of the following two parameters: CSS and the average particle size of the feed. Additional investigations are needed to improve the precision of the model.

Prediction of power consumption and product size in cone crushing

An investigation of the parameters affecting the performance of laboratory scale cone crushers is presented. This work forms part of a rock characterisation initiative undertaken by Pegson Ltd. and the Camborne School of Mines. The effect of feed size, closed side setting and rock strength on the power consumption and product size is examined. Rock strength is characterized via a series of tests used in mining and associated areas. Certain rock strength parameters have been found to correlate closely with power consumption and product size. These parameters are then combined with closed side setting to produce predictive equations. These equations are capable of predicting power consumption and eighty percent passing size of product for a range of closed side settings. The predictive equations are presented as a series of three dimensional graphs. The graphs allow the design engineer to envisage the variation in power and product size with variation in operating parameters. In addition to predicting the eighty percent passing product size, a method of predicting the full product grading is presented. This method is based on the Rosin-Rammler-Bennett distribution. The prediction of power consumption and product size/grading is based on a geotechnical approach developed by Pegson Ltd. and applied to the design and selection of crushing circuits.