MINERAL PROCESSING (SEPARATION, FLOTATION, CRUSHING, GRINDING, ENRICHMENT ETC.) : PRINCIPLES, TECHNOLOGIES AND INDUSTRIAL PRACTICE

In this paper a dynamic model of ore flotation is presented. The model has been conceived in such a way that its tuning is easily carried out by the use of commonly available information: Flotation kinematics experiments results (used in plant design process), plant dimensions and design throughput, valves and nozzles specifications, and some minor assumptions. The basic modeled module is a flotation cell with two phases: Slurry and froth. The phenomena involving the transportation of rich particles from the slurry to the froth by air bubbles is addressed. In spite of its simplicity, the model has proved to be highly effective for operator training, control system verification and commissioning, and plant design verification. The model is presented in detail along with an operator training case study.

The wide plant control integration of mineral processes poses many challenges. Flotation plants consist of complex interacting circuits where minerals are processed in different stages with recycling. Today, a common arrange are the RCS circuits, where a rougher circuit is combined with a cleaning circuit and a scavenger circuit. The global objectives of a flotation plant are to maximize the value metal recovery while the grade of the final concentrate is kept inside a narrow band. To achieve this, for any time variant feed attributes (flow rate, solid percent, grade, particle size distribution, pH, and chemicals), a capability of modifying the operation of each circuit, in order to achieve some local objectives, is demanded. For example, in a rougher circuit one can maximize the circuit Cu recovery while the mass and grade of rougher concentrate are constrained to some values. To achieve this one can find out which pulp level profile, along the flotation bank of cells, should be used. In case of forced air cells one can also find out which air flow rate profile should be used. These local targets are chosen in order to assure the produced concentrate stream can be adequately processed by the cleaning and scavenger circuits, to deliver a final concentrate meeting the product specifications. Furthermore, that will depend on how the flotation columns in the cleaning circuit and the cells of the scavenger circuits are operated. As one can see, the problem is far from trivial and the solution in terms of how the available resources in each circuit are set, will change according to the feed characteristics. Recently, Bergh and Yianatos have proposed an algorithm to change the set of a froth level profile in a rougher circuit aided by a rougher circuit simulator based on phenomenological models with parameters estimated by using industrial data, collected in experiments designed for that purpose. In this work, a simulator for the cleaning and scavenger circuits, including a regrinding stage is presented. This simulator is based on phenomenological models, with parameters estimated from industrial data. Details on the simulators and their use to provide insight on how to use the available resources in each circuit, to obtain some local objectives which are harmonized in a global control strategy, are discussed.

The circulation load of closed circuits calculation is often a problem when performing the mass balance of mineral processing plants. Iterative methods are a family of possible methods to be applied in the resolution of this calculation and consist in a finite loop where at each iteration the calculated solution is refined to produce a solution closer to the real one. The present work presents a simple iterative algorithm to calculate the closed circuit circulation load which allows the construction of reliable balances of mass, grade and water. The equations proposed in the algorithm were obtained through analyses of many circuits taking into account each process parameter and had been validated with industrial data acquired from a phosphate ore processing plant. Three different closed circuits, with different complexity levels, are presented to explain how the proposed algorithm works. The obtained results show the algorithm has converged for any industrial situation and it is able to solve the circulation load calculation with a few iterations and a small computational time.

The mining market is growing in such a way that getting enough specialized workforce for mining operations will be extremely difficult in the short term. As a result, technologies based on dynamic simulation are becoming a key pillar to educate and train inexperienced personnel at the pace required by this industry. Operator Training Simulator (OTS) systems have been widely used in the petrochemical industry, however the knowledge transmitted to the operators has not been "capitalized" in general. OTS systems are usually delivered as a hardware and software platform and not as a long term integral service. In this paper, an integrated solution for operator effectiveness, based on the conjunction of dynamic simulation, process knowledge, virtual reality and knowledge capitalization, through the creation of simulation scenarios and eLearning, is proposed.

Crushing plants are widely used around the world as a pre-processing step in the mineral and mining industries or as standalone processing plants for final products in the aggregates industry. Despite automation and different types of advanced model predictive control, many the processes are still managed by operators. The skill of the operators influences the process performance and thus production yield. Therefore, it is important to train the operators so they know how to behave in different situations and to make them able to operate the process in the best possible way. Different types of models for crushers and other production units have been developed during the years and the latest improvement is the addition of dynamic behavior which gives the crushing plants a time dependent behavior and performance. This can be used as a simulator for operators training. By connecting an Internet Human Machine Interface (WebHMI) to a dynamic simulator with the models incorporated, an on-line training environment for operators can be achieved. In this paper, a dynamic crushing plant simulator implemented in MATLAB/SIMULINK has been connected to a WebHMI. The WebHMI is accessible via the Internet, thus creating a realistic control room for operators’ training. In the created training environment, the operators can be trained under realistic conditions. Simple training scenarios and how they could be simulated are discussed. Apart from the increased level of knowledge and experience among the operators, the time aspect is an important factor. While a real crushing plant is still being built, the operators to be can already be trained, saving a lot of the commissioning and ramp up time.

Crushing plays an important role in the aggregates and mining industries by reducing the particle size of granular solids, such as rocks and ores. Nevertheless, the control of crushers has received a fairly little attention over the past decades. As a result, the main control objective today is still to regulate the crusher power or the closed side setting, not the actual size reduction or the product size. This paper presents two approximate methods for regulation of crusher product size distribution: Specific energy consumption (SEC)-based control and ratio control of selected product fractions. The basic idea behind ratio control is to regulate the crusher product size distribution by using a ratio of two measured product mass flows (e. G. Recirculated oversize fraction and total throughput) as a controlled variable. In SEC-control, on the other hand, the product size is not measured at all, but instead the disturbance rejection is achieved as a regulatory feature of a selected controlled variable. For both methods, the objective is still the same; Minimize the variation in the crusher output. The performance of the proposed methods is evaluated against currently used control methods in a simulation study. Moreover, the implementation of the proposed methods and their suitability for different process layouts will be discussed in detail. The paper will finally summarize the strengths and the weaknesses of each available control method and categorize the methods according to application and layout-specific suitability.

To achieve a balanced and optimal production at a mine, three tasks at least must be considered. The first one is to have an optimal production plan, including a set of optimal production targets for all process units. And the second task is to make sure that all those optimal targets in the mentioned optimal production plan must be achieved at all process units by using all resources available. Furthermore, to achieve the mentioned two tasks, all measurements, equipment and systems at the mine must be running and available in real time, particularly those critical measurements such as weightometers, densitometers, ore types; Stockpile levels. With the advancement and applications of technologies in mineral processing industry, an automated mine optimization system is developed to include the following three functions: (1) mine production optimizer; (2) various dynamic controllers; And (3) a set of soft sensors. A large amount of work has been done to develop the system, started from forming the concept to testing and implementation at various mines. The system can potentially help improve the production throughput up to 30% for a mineral processing operation. The system can be applied to various mining operations, such as coal mines, chromite mines, manganese ore mines, iron ore mines, and diamond mines.

This paper describes a practical implementation of a control scheme for two impact crushers operating in parallel as secondary stage crushers in a large-scale aggregate production plant in the United Kingdom. The control is based on measuring crusher power draw, mass flows and the size distribution of produced rock. The size distribution is estimated using image analysis. The settings, i. E. Rotor speed and impact plate gaps, of the impact crushers are then automatically adjusted to produce the desired end products. The system compensates for crusher blow bar wear and changes in feed material properties. This is the first time that such a control scheme has been implemented in a production plant. This paper describes the methods and controls used as well as future developments including an optimizing control based on a second, already installed camera. Unfortunately the plant in question has lately experienced equipment breakages so an analysis of the observed benefits is not available in time for paper preparation deadlines. Such an analysis can be presented at the conference, however.

Stable operation of grinding plants is of great importance as it ensures improved efficiency and mineral recovery. The majority of current control solutions in mineral grinding plants are based largely on expert control systems which aim to maximize throughput while keeping operational variables within predefined safe limits and a stable process operation. Nevertheless, these systems are not without disadvantages: They tend to systematize bad operational practices; There are no clear procedures to tune them and they exhibit poor response to unmeasured disturbances. Strategies based on predictive control, on the other hand, allow the handling of operational constrains, unmeasured disturbances and coupling of operational variables. Additionally, they are comparably easier to tune and are less sensitive to modeling errors. This paper presents a comparative analysis of four control strategies applied to a mineral grinding plant. The tested controllers are: (i) single centralized MPC, (ii) decentralized MPC for SAG mills and ball mills, (iii) multi-level control with a higher optimization layer and a lower decentralized MPC regulatory layer and (iv) multi-level control with a higher optimization layer including a coordinating expert module and a lower decentralized MPC regulatory layer. These four control strategies are implemented using various Honeywell's Profit software applications. In order to analyze the strategies, several performance indices are defined and tests are performed using a MATLAB/Simulink-based dynamic simulator.

New hydro-electrochemical technology is designed for processing concentrates of copper sulfides of Kajaran and Kapan (Armenia) deposits in a special mode (know-how). New technology provides a high degree of extraction of copper, iron, sulfur and precious metals, an economic efficiency and satisfies modern ecological requirements. The essence of technology lies in the fact that the copper concentrate, without drying, is immediately subjected to electrochemical dissolution. As a result the copper in the form of powder is deposited on the cathode, and then gradually deposited on the bottom of the electrolytic bath, and the iron goes into solution and subsequently can be removed by crystallization. Part of the sulfur is separated in the form of elemental sulfur from the decomposition of chalcopyrite and remains in the undissolved mass. The process is environmentally friendly because no gaseous or liquid waste is produced: Electrolyte is circulated in closed cycle. Thermodynamic and kinetic parameters of the process are presented.

Copper recovery and acid consumption are two key variables in heap leaching operations. The main idea of this work is to estimate these variables based on historic data and the previous knowledge available in the plant. In order to tackle the problem three key tools are required; I. E. Data exploration analysis, fuzzy logic modelling and optimization techniques. The data exploration methodology is used to process the data and it considers classification, variable selection and data correlation. On the other hand, the empirical knowledge used by the operators, and described in terms of fuzzy rules, is included in the model in order to provide consistent predictions even though there is not enough data available to support such predictions. Finally, an optimization technique is used to solve the problem of adjusting the model’s parameters by considering both the data and previous knowledge. As a result, it is possible to obtain a model that can be used to estimate the recovery and the acid consumption with a low uncertainty compared with other methods such as the one normally used in practice; I. E., simple linear in the parameters correlation models. This modelling methodology is applied to model the operation of a real industrial heap leaching process. The results clearly show that the time evolution of the recovery mainly depends on the mineralogy, and acid consumption on the temperature and the acid feeding. In addition, they also illustrate that model can predict these variables over a wide range of conditions and time span.

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. The paper is divided into three main sections. The first section gives an introduction in which the characteristics of model-based versus expert systems and fuzzy logic control are examined: How to determine the best approach? How to decide between ruled-based approaches and model-based approaches? How to balance advantages and disadvantages, complexity and simplicity, investment and results? A decision tree is presented to select the right approach. The second section describes the approach selection and the SAG mill process. For the SAG mill process, fuzzy logic was the logical choice. The solution is robust, simple and is implemented in the actual control system, a programmable logic controller with fuzzy logic function blocks. Finally, the third section is devoted to the implementation, commissioning and optimization of the controller. This section will also touch on training, maintenance, improvements and results achieved. Specific energy reduction, improved stability and throughput increase are among the main recommendations and conclusions.

Several dynamic models are able to represent the phenomenological behavior of flotation. On the other side the interest in developing control strategies for large-scale processes has led to formulate novel methodologies which allow to consider the global behavior of a plant, facilitating the design, validation and evaluation of more complex optimizing control strategies. In this work, we first develop a dynamic hybrid model for a flotation rougher circuit with two production lines composed by four cell banks in series, connected by controlled valves. Each line is actuated by discrete valves, whose interaction with different bank pulp levels define several operation modes. The model was validated with data from an industrial plant. Subsequently, a hybrid model predictive control (HMPC) strategy is proposed, valid for the different operation modes established. This optimizing controller considers a hybrid prediction model obtained by applying identification techniques to the different scenario. Our simulation results show that the proposed methodology is suitable for modeling the global behavior of a rougher flotation circuit, representing its dynamic and providing a robust control for several operation modes of the circuit.

Hydrocyclones are devices worldwide used in mineral processing and used for desliming, classification, selective classification, thickening and pre-concentration. Versatile in application, the hydrocyclone is the standard classifier used in closed circuit milling in mineral processing plants. A hydrocyclone is composed by a cylindrical and a conical section joint together, without any moving parts and it is capable of perform granular material separation in pulp. The pulp is feed under pressure tangentially to the cylindrical section. The granular separation mechanism is complex and it´s mathematical modelling is empirical. The most used model for hydrocyclone dimensioning was proposed by Plitt (1976). Combining the first industrial database on cyclones generated at JKMRC (Rao, 1966) with his own laboratory data, Plitt developed an alternative general- purpose cyclone model. Over the years many revisions and corrections in Plitt´s model were proposed. In the present paper the influence of two operational parameters (percent solids in feed by volume and the pulp feed flow) in seven models based in Plitt´s models were studied in reference to the corrected classification size (d50c). To do so a hydrocyclone using Ritema´s geometry (10 cm of diameter) and iron ore pulp was used. The founded results allow the proposal a different value for Plitt´s model constant, resulting in another revision for the model.

Hydrocyclones are devices worldwide used in mineral processing and used for desliming, classification, selective classification, thickening and pre-concentration. Versatile in application, the hydrocyclone is the standard classifier used in closed circuit milling in mineral processing plants. A hydrocyclone is composed by a cylindrical and a conical section joint together, without any moving parts and it is capable of performing granular material separation in pulp. The pulp is feed under pressure tangentially to the cylindrical section. The granular separation mechanism is complex and its mathematical modelling is empirical. The most used model for hydrocyclone dimensioning was proposed by Plitt (1976). Combining the first industrial database on cyclones generated at JKMRC (Rao, 1966) with his own laboratory data, Plitt developed an alternative general- purpose cyclone model. Over the years many revisions and corrections in Plitt´s model were proposed. In the present paper the influence of two operational parameters (percent solids in feed by volume and the pulp feed flow) in seven models based in Plitt´s models were studied in reference to the corrected classification size (d50c). To do so, a hydrocyclone using Ritema´s geometry (10 cm of diameter) and iron ore pulp were used. The founded results allow the proposal a different value for Plitt´s model constant, resulting in another revision for the model.

SGS Advanced Systems and First Quantum’s Kansanshi Mine collaborated in a control project to stabilise and optimise the SAG milling process at Kansanshi’s copper concentrator in Zambia. This paper describes the method and results of the advanced control system that was implemented on the Sulphide milling circuit. The acceptance and performance achieved may be attributed to the approach in implementing the system, as well as the configuration of the fuzzy logic control strategy. The main conclusions may be summarized as: • The Fuzzy Expert Control system is a robust solution, which is evident from the utilisation which was more than 85% for the past year. • The acceptance of the system may be attributed to the level of participation of the entire team in constructing and tuning the expert logic. • The unique approach to handling the fuzzy rule base makes it easy for operators and engineers to understand and follow the expert logic systematically. It also reduces the room for error and facilitates the tuning of the system. • The stability of the circuit was increased, which also allows operation closer to the optimum. • Mill throughput was increased by 6%, which may be attributed to the stabilisation as well as optimisation of the multivariable system.

AbstractThe lack of integrated information with sufficient detail for analysis causes inefficient operation in metallurgical complexes. Defining the right context for information use is essential for sustainable operations. This being said, what are we doing to enable people to act upon information and to be aligned to optimize the use of resources like raw materials, energy, water and consumables for an entire metallurgical complex? Collaboration between all company entities is a key component of improving efficiency. Evolution of web technology and object modeling of enterprise assets enables collaboration across the whole business. Operational troubleshooting becomes faster as the organization acts on issues to reduce wasteful operation. This paper presents a real time software infrastructure with tools that give users the ability to sift through available data, transform data into information for business continuous improvement and optimization. We will introduce a distributed architecture for analyzing real time data, information and events using multidimensional analysis of information to detect anomalies based on the statistics of the data classified by time events to reduce the information into action. We will relate to the work at AngloAmerican Chile

The implementation of a successful control operation for a vertical mill of an ore copper grinding plant has been historically, a challenging one. First, it must be capable of processing a variable rougher flotation feed without becoming a process bottle neck. It must also deliver an adequate quality product to the process downstream while keeping an adequate circulation load and making an efficient use of the available grinding power. Then, the vertical mill itself and its associated classification equipment have problems of their own; It must maintain adequate control of cyclone’s pressure and density while maintaining an adequate pump box level with only a few manipulated variables. Thus, it becomes a non-linear multi-variable type of process with multiple control objectives to satisfy simultaneously. On the long term also, it must try to extend vertical mill, pumps and cyclones performance and availability. To achieve that, many mines implement basic or conventional control or even better yet, expert systems. But due to the fast changing nature of vertical mill’s process conditions, Minera Los Pelambres believes that better and faster results can be achieved using a combination of MPC (Multivariable Predictive Control) and advanced control. Thus, such strategy was successfully implemented in two of its vertical mills, reducing considerably process variability while maintaining high throughput and keeping the process well within constraints limits. Regardless of their differences in processing capacity, a stabilizing-control strategy was developed, tested and tuned and their control philosophy, implementation process, main results and their key performance indicators are discussed here. This paper also discusses the impact and reaches of such advance control technologies for the mining industry, their implementation and support effort and their impact on best operational practices and long-term increased productivity.

Optimization deals with minimizing or maximizing a mathematical function whereas intelligence implies the ability to comprehend, reason and learn. An intelligent optimizing control system must have the ability to comprehend, reason, and learn about processes, disturbances, and operating conditions and use this knowledge to optimize process performance within operating and economic constraints. Factors that must be learned and understood include static and dynamic process characteristics, disturbance characteristics and equipment operating norms and practices. Implicit in the necessary system capabilities is the ability to improve or adapt over time as more experience is gathered by observation of past system operation and performance. Because of the non-linear and complex nature of material-processing applications, process models need to adapt over time if they are to be used effectively in an intelligent optimization system. Optimizing control of milling circuits are presented. Examples are provided from plant systems where an adaptive expert control system was used to model and control the circuits in real time. The expert system used is an intelligent, object-oriented system that can be applied with any combination of control equipment and sensors to adaptively control and optimize processes.

The circulation load of closed circuits calculation is often a problem when performing the mass balance of mineral processing plants. Iterative methods are a family of possible methods to be applied in the resolution of this calculation and consist in a finite loop where at each iteration the calculated solution is refined to produce a solution closer to the real one. The present work presents a simple iterative algorithm to calculate the closed circuit circulation load which allows the construction of reliable balances of mass, grade and water. The equations proposed in the algorithm were obtained through analyses of many circuits taking into account each process parameter and had been validated with industrial data acquired from a phosphate ore processing plant. Three different closed circuits, with different complexity levels, are presented to explain how the proposed algorithm works. The obtained results show the algorithm has converged for any industrial situation and it is able to solve the circulation load calculation with a few iterations and a small computational time.

Mass flow estimation in mineral processing applicationsTeemu Väyrynen, Pekka Itävuo, Matti Vilkko, Antti Jaatinen, Mika PeltonenMonitoring of mineral processing applications requires accurate, robust and cost-effective online mass flow measurements from the process. The mass flow measurement methods used today in mineral processing applications are designed for monitoring the overall production volumes of the plant. A belt scale installed on the main conveyor of the mineral processing plant is the most commonly used mass flow measurement equipment used today. Even though the belt scale provides an accurate mass flow measurement from the process, its high price prevents the installation of multiple belt scales to a single mineral processing plant. The main purpose of this paper is to present and evaluate different mass flow estimation methods for mineral processing applications. The different methods used in this paper are a power transducer, an ultrasonic sensor, a laserprofilometer and strain gauges. In addition to the individual sensors, 23 different sensor combinations are evaluated as mass flow estimation methods. The presented methods are compared against a belt scale working as a reference mass flow measurement during the experiments. Different mass flow estimation methods are evaluated mathematically and from the operational point of view. Results indicate that the same measurement accuracy can be achieved with the presented mass flow estimation methods as with the traditional belt scale. The unit prices of the presented sensor types are in order of tenth of a traditional belt scale, which allows monitoring of the whole mineral processing plant cost-effectively. Significant gains can be achieved due to increasing monitoring capabilities provided by the multiple mass flow sensors in terms of energy efficiency and end product quality optimization.

Potassium is an essential raw material for the development of plants, mainly as fertilizers. In fact, about 95% of world production is consumed in agriculture, in which 90% is in the form of potassium chloride, and the remainder is consumed by the chemical industry with diversified applications. In a Brazilian potassium chloride plant, after tilling and flotation, the wet concentrated material follows to drying, basically comprised of a fluidized bed dryer. This drying process is non-linear, complex and influenced by several factors, thus conventional control cannot be implemented properly. Advanced process control offers alternatives for that, mainly by using Model Predictive Control (MPC). The model is obtained by transient-response analysis and shows a good ability in predicting variations in temperature with changes in manipulated variables and disturbances. The linear model used by the MPC controller is periodically adjusted by an expert system with fuzzy logic accounting for the non-linear behavior of the process. A comparison is made with traditional feedback control and MPC with feed forward action.

The objective of the paper is the development and evaluation of a control strategy to improve coke addition in a concentration plant for the production of iron oxide pellets. The carbon content of green pellets is a critical variable affecting the performance of subsequent processing phases, notably sintering through straight grate furnaces. Reducing the variability of carbon content could lead to significant improvements in terms of higher product quality, reduced energy consumption, and process stability. The concentration plant involves many types of separation units, a lot of recycle streams, transportation delays, and coupled dynamics. Such a design makes the process efficient from a metallurgical point of view but causes difficulties for control applications. In fact, the prediction of the final material composition is not straightforward and direct measurement of carbon content across the process is rather scarce, infrequent, or unreliable. To handle this relative complexity, phenomenological and empirical models are developed to track material composition through the circuit. These models are first used to determine the achievable variability reduction of the final carbon content using minimum variance based indices. Then, two different control strategies are developed and evaluated in simulation. The first consists in an enhanced regulatory control approach combining algebraic PID, cascade, and feedforward controllers. The second relies on model predictive control. Results show that both control strategies are able to reduce the carbon content variability and produce valuable benefits.

MODELING OF PULP pH CONTROL IN HYDROTRANSPORT SYSTEM FROM GRINDING TO FLOTATION PLANT Zoran S Markovic (1)*, Zoran Stirbanovic(1), Dragan Milanovic(2), Daniela Urosevic(2), Luka Z Markovic(3)(1) University of Belgrade- Technical Faculty Bor, Bor, Serbia(2) Institute for Mining and Metallurgy Bor, Bor, Serbia(3) University of Belgrade – Mining and Geology Faculty Belgrade, Belgrade, Serbia *Corresponding author ABSTRACTCopper mine “Cerovo” was commissioned 1993 as an open pit mine with crushing and grinding plants at its surroundings. Ground copper ore has transported by system of hydro transport about 13 km long, to the flotation plant Bor. Pulp retention time in preparing and transporting system is about 5 hours, but in the transport about 3 hours long. A significant drop of pH values in pulp have been noted between grinding and flotation plants. The values of those differences are mainly depended on initial pH values. Also, it was observed that the flotation recovery strongly depends on initial pulp pH values and its additional adjustment in flotation plant by adding pH regulator. Copper ore is porphyry type of ores with minerals chalcopyrite and chalcocite. Principal sulfide mineral is pyrite. Copper grade in ore is about 0.405% and sulfur about 2.56%. Applying reagents in flotation process are: Lime for pH adjustment, PEX (potassium ethyl xanthate) and S-7518 collectors and D-250 frother. In this paper, some main results from extending laboratory investigation work are presented in order to achieve the optimal results and minimize the lime consumption. Proposed model offers cutting lime consumption from 1.7kg/t (former) down to 1.2 kg/t of processed ore using lower initial pulp ph. The model is based on laboratory flotation tests and electrochemical measurements. And finally, it is needed to mention that the lower initial pH, besides of lower lime consumption, may prolong pipeline life due the lower scale of lime onto inner pipe walls.

Flotation and magnetic separation are well known processes for magnetic minerals. But application of magnetic field to flotation is new and there are only a few studies about this in the literature. Iron minerals are usually present as gangue minerals, especially in industrial minerals, and their separation is very important. The combination of these two methods has expected to make separation more effective and easier. A flotation cell in magnetic field is designed and FEMM has been used for modelling. In this study, magnetic flux lines in the cell and their effect to particle were simply shown by the modelling. Also the value of magnetic field in the cell and magnetic field intensity on the particle have been calculated. This modelling clearly explains the flotation process in the magnetic field.

The processes of milling and flotation of copper-molybdenum ores are characterized by significant fluctuations of all input, output, and intermediate parameters. Instability and not the optimal parameters of grinding and flotation cause from 3% to 6% of losses of the valuable component. In these conditions it is difficult to apply deterministic mathematical models of processes. On the contrary, the use of multi-level adaptive models allows to considerably optimize technological processes. Automatic process control milling uses the principle of maintaining a rational level of loading of the drum mill ore and balls. While the system is operating as input parameters are used energy and acoustic signals and the results of measurements of the size of the grains of the crushed ore. When managing the flotation, the principle of forward-looking estimation of grade of ore is used. While the system is operating as input data, analysis of ore in the x-ray and visible range are used. Application of modern systems of automatic regulation and control at the concentration plant Erdenet (Mongolia) helped increase the recovery of copper and molybdenum.

There are various technologies for processing pyrite concentrates containing non-ferrous metals, Au, Ag, Cu. Often these technologies are accompanied by undesired emission of sulfur dioxide into environment. We have developed a new technology allowing to obtain pure sponge iron and prevent SO2 release into atmosphere. Sulfur is obtained in liquid form of hydrogen sulphide, which can be easily converted into sodium sulfide, which is useful product for ore enrichment. Technology is based on high temperature treatment of pyrite concentrate in water vapor medium. The temperature regimes of pyrite concentrate processing and other technological details are presented in the paper as well as chemical composition of row material and final product. The technology is tested in pilot laboratory plant using concentrates of Kadjaran (Armenia) deposit.

Excellent particle size control is important in efficient mineral processing, but today many milling operations are controlled using techniques which only consider the minimum particle dimension and assume that shapes of the particles remains constant. Many process operations suffer from variation in efficiency which cannot be explained by conventional techniques such as screening and this can be as a result of process changes such as ore source causing a change in particle morphology, which is simply not detected when only the minimum particle dimension is considered. Image analysis data will be used to demonstrate the key principles behind particle size measurement and the reality of mineral slurry shape distributions. Unfortunately, the application of image analysis techniques to on-line analysis of mineral slurries is not a practical proposition for reasons of sampling, statistics and cleanliness. Therefore, alternative techniques must be used on-line to obtain reliable and process sensitive data. Ultrasonic extinction fulfils many of the requirements for on-line particle size analysis, being able to monitor vast numbers of particles at high concentration and since the technique responds to the area of the particles, a more process sensitive measure may be obtained. The OPUS ultrasonic extinction system uses 31 frequencies to measure a full particle size distribution from approx. 1um to 3mm and for the first time allows for parameters such as distribution width, fine particle levels and solids concentration to be measured reliably on-line in a single unit. Data will be presented to show the potential for better process understanding through utilisation of the full particle size distribution information.

Pellet plants use physical gravimetric treatment processes for iron concentrates in the early stages of preparation for the induration process. The gravimetric systems used are hydraulic classifiers. These systems, though providing acceptable performance in terms of recovery by weight of iron units are nevertheless poorly instrumented components of the entire process. The control rules that support these systems are thus influenced and limit the desired performance improvements. This article presents various stages of analysis carried out at the pellet plant at Port-Cartier on a hydraulic classifier and focuses on the comparison of different, mono and multivariable control methods and eventually lead to a new approach, namely that of

This paper presents a new instrument for real-time detection of excessively coarse material in the overflow pipes of individual hydrocyclones using a non-invasive acoustic measurement technique. The hydrocyclone is an important device used in mineral processing beneficiation circuits for classification of mineral slurries by particle size. It separates a single input stream into two output streams; An underflow of coarse particles that undergo additional grinding for further size reduction, and an overflow stream of finer particles that typically goes directly into a flotation circuit for recovery of the desired mineral. However the hydrocyclone is a major piece of equipment in the beneficiation process that has no instrumentation for directly measuring its performance. The parameters currently measured – inlet pressure, feed flow rate, feed flow density – are common to the entire hydrocyclone cluster which typically has three to twelve hydrocyclones. Thus no information is available to detect individual hydrocyclones that are operating poorly. The system described in this paper detects the presence of unwanted excessively coarse material in the overflow stream of a hydrocyclone using sensors mounted to the exterior pipe surface. It provides real-time monitoring, trending and alarming of the coarse material level. This enables operators to identify poorly performing hydrocyclones, and enables corrective action to reduce or eliminate the coarse material discharge. Improving the classification efficiency of individual hydrocyclones will improve the overall classification efficiency of a hydrocyclone cluster. This leads to less variation in the particle size distribution and slurry density in the flotation feed, which will in turn improve overall mineral recovery. The reduction of unwanted coarse material in the flotation feed reduces the accumulation of that material in flotation cells. This can lead to equipment damage, and unplanned shutdowns due to events such as blocked dart valves.

Libyan Iron ores reserve estimated to be > 5.0 billion tons, with 48-55% Fe& 1.0% P& Libyan Previous detailed investigation by FSG& IRC was not sufficient& did not adopt any technology to remove P), (Si) & alkaline. Due to price increasing of iron ores in global markets, gave potentials to treat high (P) iron ores in economical ways. Recent global treatment of high (p) iron ores results may be adopted to treat the Libyan ores & the predication may be fruitful. A Preliminary QEMSCAN analysis of Libyan iron ores samples was conducted at (advanced mineralogy research center- CSM), to determine phosphorous phases, locking and liberation characteristics of the phosphorous phases and mineral associations. Determination shows that 61 % Fe as Oxide/Hydroxide, 31 % quartz, 5 % apatite, and other traces. Fe occurs in fraction -300/+150 μm. Highest concentrations of apatite occur in the coarsest fraction assay shows 1.0 % P and 39 % Fe & most of Fe found in coarsest size fraction. Size fractions of P < 0.5 mass %& elemental deportment of (P) is present in apatite, in fraction -75 μm &0.3 mass % P occur in monazite.68 % of apatite is liberated; The majority of liberated apatite 62 % can be observed in the -75 μm fraction. The fruitful findings may give an excellent encouragement to perform preliminary floatation& leaching experiments as long as the phosphorous existed as apatite phase& it can be separated by many different promising techniques as well.

A parameter estimation method for an online flotation process simulator is described. The applications of an online process simulator include soft sensor implementations, process trajectory predictions and advisory feedback to the operator, which have potential to improve the process efficiency and minimize the risk of disturbances to the process or the environment. The online simulator uses a detailed and dynamic model of an actual industrial flotation process, and therefore accurately corresponds to the process phenomena present at the plant. Parameter estimation is required for the flotation kinetics in order for the simulator to adapt to changes in the process conditions. A relatively simple parameter estimation algorithm is developed and tested with a dual simulator setup. The particular requirements and limitations of adapting an online simulator are discussed, and modifications to well-known estimation algorithms are presented as a possible method of meeting the requirements and overcoming the limitations. The results show that online parameter estimation and simulation model tracking is possible with the chosen method, and point out areas of further development for application when the simulator is used alongside the real process. [This paper focuses on the adaptation method in the online simulator. Another paper (Kaartinen J., Pietilä J., Remes A.: ”Using a Virtual Flotation Process to Track a Real Flotation Circuit”) that describes the general structure, functionality and applications of the simulator system will also be submitted to this conference. ]

A bubble detection and measurement technique based on Circular Hough Transform (CHT) has been implemented for bubble size distribution (BSD) determination in two-phase (gas-liquid) systems. This technique allows the detection of large single bubbles as well as clusters. A high resolution CCD camera is used to capture the images of bubbles. The obtained images are automatically pre-conditioned to eliminate the background, eventual noises and to enhance the contrast. Tests were carried out in a laboratory flotation column using different concentrations of frother and air flow rates. Results were compared against manual (visual) counting, as well as the as the most currently used BSD detection method based on circular particle detection (CPD). The CHT technique allows proper detection and measurement of bubble lusters, large bubbles and also bubbles on the edge of the image. Results are highly correlated to manual counting. Compared to CPD algorithms, the CHT approach significantly improves D32 estimation (error of ~5% instead of ~18%) with a comparable processing time. Different parametric and non parametric methods to represent the resulting BSD are explained. Using a parametric approach, the BSD is estimated as a function of a log-normal distribution. Results are compared with manual estimation, showing a good representation of the distribution.

The petrographic and Geochemical study for the Xenoliths associated with the Quaternary alkali bases at Tell Habran showed large petrographic differences that reflect various balance conditions, origin and different formation phases being derived either from the lower crustal or the upper mantle origin. Most Quaternary lavas in Syria contain a wide variety of mafic and ultramafic Xenoliths of the lower crustal and the upper mantle origin. The host rocks, however, are mainly alkali olivine basalt and basanite. The Xenoliths suite have been classified into three main group based on their quantities, texture, mineral component and chemical composition. The first is Cr-diopside Group, which is the dominant group (65%). It is characterized by protogranular or equigranular texture and is subdivided into Spinel, Lherzolite, Hazburgite, Dunites and Wehrilites. Secondly, augite group represents 25% and is mostly characterized by fine to medium grained igneous and/ or mosaic texture and is subdivided into Websterite, Pyroxenite, Pyroxenite, Kaersutite and Kaersutite Megacrysts. Finally, the Mafic lower crustal xenoliths Group represents only 10% and is characterized by fine to medium grained, igneous cumulate texture and is subdivided into Pyroxen, Granulite, Spinel and Gabbro and Gabbro. The content, location and composition of the minor and major chemical element for the Xenoliths of the upper crustal proved those were formed as a result of partial crystallization after the formation of basalts- Xenoliths indicate similar composition to broadly gabbroic (tholeiitic) and its enrichment in rare element (REE) was attributed mostly to the effect of retained solution and the metasomatism that occurred without direct tectonic relation.

Any mineral belongs to a certain subsystem of multicomponent system. The task is to define the borders of this simplex in the topological complex. Usually the adjacency matrixes are used for the multicomponent system polyhedration: A polyhedron with triangulated faces is presented as a non-oriented graph with enumerated vertexes; Zero elements of the adjacency matrix are multiplied with regard to the absorption law; An inversion is applying to the multiplication result. As a result, the simplexes list of the polyhedron is formed. However, this algorithm cannot divide the polyhedron with inner points and with competition of inner diagonals and inner planes. Therefore, the new algorithm has been elaborated. It uses interrelations between the number of inner planes (the simplexes borders) and non-zero elements of the adjacency matrix (edges), and it consists of three steps. Firstly, all connections, including all possible inner one-dimensional diagonals, are written. Then, all possible planes of three types are formed: Planes on faces, inner planes without inner one-dimensional diagonals on the polyhedron faces and inner planes, connected with the possible inner diagonals. The last type of planes is analyzed in accordance to formulas, which estimate all probable variants of polyhedration. All selected at the second step planes may form the tetrahedrons of two types, with and without the inner diagonals. The new algorithm recognizes all possible variants of polyhedration at competition of inner diagonal elements (e. G. Line and plane in the 5-top hexahedron). It may be applied for polyhedration of multicomponent systems with more high level of dimension. As a result, all variants of polyhedration are identified, including situations when the old algorithm cannot “recognize” some simplexes. After analyzing of different variants of polyhedration, the last step is to find out experimentally which of inner diagonal is present.

It is well known that mineral processors can improve mining operations by using the best available control technology such as advanced process control (APC). It can not only help reach higher production, but also improve “process controllability”, reduce process variability, help adaptation to fast changing process conditions and in general terms, increase plant stability. The application and integration of new technology and process knowledge in innovative ways is the key in building such a supporting structure. However, it is not clear when and how to deploy such strategies and what technology, or perhaps, combination of tools, should be used. Careful consideration of the goals to be achieved, process knowledge available, implementation and support effort and available resources must be exercised. But this is not enough yet. The correct selection and deployment of new technology, the timely presentation of processed data and meaningful information to decision makers and operators and the development of KPIs (key performance indicators), alarms and graphics are key elements to a successful process operation. Under the guiding vision of “Operational Excellence” at Minera Los Pelambres, we have combined the APC technologies, the process control strategies, the process modelling and simulation, the best automation practices, the visual performance management tools and the operators training under the concept of “Operational Intelligence”, meaning by that not only the application of state-of-the-art automation and computing tools, but rather the assembly and management of the above listed structuring factors to support continuous seeking for optimal performance and safe operations. Thus, this paper discusses some of the key tools and process control strategies implemented for a Copper Grinding and Flotation Plant, their assembly, their performance results and the path taken for the integration of process knowledge, control tools and presentation of meaningful information. In addition, successful case studies are presented to highlight the procedure and the benefits of such comprehensive and encompassing approach that deviate from the traditional mining “expert systems” control approach. Also, a word is given on the need for innovating in the design of control strategies and on best automation practices for long-term reliable operation that will contribute to improve mineral processing and, although unmeasured, will lead to a better overall performance of all people involved.

Zeolites are minerals based on silicate origin. One of great importance is natrolite. There are different names for zeolites. According to its origination, different chemical composition, structural characteristics and application they form a group of silicate minerals within subclass Tectosilicates. Clinoptiolite-heulandite tuffs are of the greatest economic interest. Clinoptilolite series structurally belong to HEU-type zeolites, with commoner framework topologyEnvironment becomes pressing issue whereas fundamental criterions of life quality are disturbed. To succeed, eventually, in control of criterions disturbance, strategies of industrial development are defined. It affected process of institutionalization i. E. Standardization of management in protection of environment. Keywords: Mineral, future, application environment

A phase diagram of system MgO-Аl2O3-SiO2 has wide applications and can be used in the metallurgy and silicate production at investigation of castable properties. The aim of this work is to simulate the computer model of phase diagram of system MgO-Аl2O3-SiO2 and to examine processes of crystallization on its base. The full construction of phase diagram are restored using the spatial scheme of mono- and invariant equilibria on the basis of experimental information about the structure of primary crystallization surfaces. Analysis of concentration fields obtained by the projection of phase regions onto Gibbs triangle allows to establish the boundaries of phase regions (located above the considered fields), the sequence of phase transformations and microstructural elements in crystallized initial melt at the equilibrium condition. Concentration fields can be analyzed from the order of intersected surfaces and phase regions as well as the scheme of phase transformations and resulting set of microconstituents. Based on this technology, the research identifies concentration fields with coinciding sets of crystallization scheme and microconstituents and the fields with individual characteristics.

According to the properties of a complicated refractory copper-lead-zinc sulfide ore, experiments adopted the flowsheet of mixed flotation of copper and lead, and separation flotation of copper from lead and then flotation zinc from copper and lead tailings. Sodium sulfide, sodium carbonate and zinc sulfate were combinedly employed as depressors, and Z200, sodium butyl xanthate and Dithiophosphate BA as collectors for mixed flotation process, CQS mainly consist of CMC and sodium sulfite as depressant for copper-lead separation flotation process after using activated carbon to remove the collectors absorbed on the copper-lead concentrate. In zinc flotation process, copper sulfate was employed as activator and sodium butyl xanthate as collector. Excellent separation indexes were obtained with copper concentration contained 28.23% copper and copper recovery of 84.87%, lead concentration contained 68.12% lead and lead recovery of 92.20%, zinc concentration contained 45.10% zinc and zinc recovery of 81.45%. Solution chemical calculation and electrochemical research were conducted to study the reasons for the inhibitory action of CQS to galena.

The search of effective reagents for the selective hydrochemical extraction of valuable metals from oxide and sulphide raw materials as well as the determination of the kinetic parameters of these dissolution processes with the aim of the choice of optimal technological conditions are the important directions of physico-chemical investigations in hydrometallurgy. A novel approach to the investigation and the description of the kinetics of dissolution of oxide and sulphide minerals using a rotating disc method and a factor experiment design is proposed. This approach consists in the determination of the power and exponential dependences of the specific rate of mineral dissolution on the most important influencing factors – concentration of reagent, temperature, disc rotation frequency, and duration of measurements. The obtained adequate kinetic models allow calculating the specific rate of the metal cations transfer from disc surface to solution at any combination of the values of influencing factors within the selected region of investigation. As a result of the physico-chemical interpretation of these models, the values of dissolution rate constant and activation energy as well as the orders of the studied processes with respect to reagent and disc rotation frequency can be determined. The complex analysis of the obtained kinetic parameters allows establishing modes of proceeding of the processes, determining their macromechanisms and revealing the limiting stages of dissolution. This approach appeared to be effective both for not complicated (kinetically or diffusion-controlled) and mixed modes. The obtained dependences of the specific rate of dissolution of selected oxide and sulphide minerals on the most important influencing factors as well as the revealed details of reaction mechanisms can be used for the determination of the optimal conditions of realization of the existing technological processes of metal extraction from ores and concentrates, and as the database for the development of perspective technologies.

Data reconciliation is widely applied in metallurgical plants for steady-state estimation of process variables. Algorithms are mainly based on mass and energy conservation equations that could mostly be extracted from process flow diagrams. An important difficulty is to characterize uncertainties about the plant behavior. Usually, the Gaussian context is assumed and a maximum likelihood estimator is retained. In practice, tuning the weighting matrix, i. E. Selecting the variances of modeling and measurement errors, is a challenging task that is sometimes overlooked. The objective of the paper is to illustrate the impact of correctly choosing uncertainty covariance matrices. Effects of both the matrix structures and numerical values are investigated to assess the sensitivity of data reconciliation to uncertainty. Analyses are supported by simulation of basic case studies including a combustion chamber, a hydrocyclone, and a flotation unit. Results show that the adjustment of the uncertainty covariance matrix has a significant influence on the precision of estimates. A correct selection is highly valuable for subsequent uses of reconciled data. Practical guidelines are given to validate the covariance model adequacy.

Hydrocyclones are widely used in the mineral processing industries to separate particles of different sizes in slurries. Internal flow in hydrocyclones is complex and control of these devices is there not well-established. However, in recent years, progress has been made with the online measurement of the underflow in hydrocyclones, particularly by use of image analysis. The spray angles of the underflow can serve as an indication of the state of the cyclone. In this paper, previous studies on the measurement of the underflow of hydrocyclones are extended to include estimates of particle size distributions from the appearance of the slurries in videographic images. This is accomplished by extracting textural features from slices of the images and the construction of models to relate these features to particle sizes in the flow streams. As indicated by case studies with several different ores, reasonable estimates of the particle sizes can be obtained by making use of co-occurrence matrix methods and neural networks, and this could form the basis for improved monitoring and control of hydrocyclones

This paper presents a novel way of using a dynamic flotation process simulation environment for concurrent simulation alongside a real flotation process. Previously the research group has developed the general structure of the environment intended for training purposes in off-line simulation scenarios (Roine T., Kaartinen J., Lamberg P.: "Training simulator for flotation process operators", 18th IFAC World Congress, August 28 – September 2, 2011, Milano, Italy.). This work has been continued in order to be able to facilitate on-line simulations, where the simulation environment is actively adapted to a real flotation process. This yields new possibilities on the usability of the simulation model. For example, virtual measurements can be introduced that provide completely new variables or increased fault tolerance through redundancy. Another option is to provide feedback for the process operators in the form of textual reports. These reports contain e. G. Shift-specific performance indices that can be compared against reference data. Furthermore, by speeding up the simulation, it is possible to make prognosis on the effects of different control actions before actually making them. [This paper describes the general structure and technical details of the system, including the necessary details of the copper circuit in Pyhäsalmi Mine that is used as a test case in the project. Another paper (Pietilä J., Kaartinen J., Reinsalo A-M: ”Parameter Estimation for a Flotation Process Tracking Simulator”) covering the details of the adaptation techniques will be submitted also to this conference. ]

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