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By J. A. Herbst

It is widely recognized that Semiautogenous Grinding (SAG) circuits require the use of effective process control techniques to achieve their full processing potential and to protect them from the harmful effects of overloads and grind-outs. This requirement is even more essential as the variability of the ore being processed increases. The new Chino Mines Company concentrator located near Santa Rita, New Mexico started operation in June of 1982. At least eight major rock types are mined and milled. Ore hardness, feed size, and specific gravity are quite variable. Typical feed rates per grinding line are 850-900 tph but extremes of 260-1200 tph have been encountered. Normal feed rate variations of between 400 and 1100 tph are encountered on a weekly and sometimes daily basis. Feed size varies with rock type from a maximum of eight inches for the harder ores to two inches for the softer ores. One somewhat unique characteristic of the Santa Rita ore body among major copper mines is the wide variation in ore specific gravity. Specific gravities of the major rock types range between 2.7 and 3.6. The specific gravity variations are due to large changes in magnetite concentration throughout the pit. The result of this is large variations in SAG mill throughput which can have a harmful effect on downstream ball milling and flotation performance. Due to these wide fluctuations in ore characteristics, it was recognized soon after startup that successful operation of the grinding circuit and the plant at large was dependent upon the development of an effective automatic grinding control strategy. Research at the University of Utah has suggested that control based upon critical but difficult or costly to measure variables would improve automatic control performance. A project team made up of the Chino process control staff, Kennecott's Process Control department and the University of Utah Metallurgy Department was established to assess these concepts at Chino. This paper describes the development and on-line plant implementation of an Extended Kalman Filter that uses simple models of the SAG milling process, to predict the volumetric loading, the rock mass, the water mass, and the ball mass within the SAG mills at Chino. The on-line estimation of these parameters is the first step in the development of an integrated SAG mill/ball mill control strategy which is hoped to L eventually maintain the grinding circuit at its maximum capacity, while balancing the grinding load between the SAG and ball mills. Examples of long term estimation with the models and filter are shown for typical operating conditions as well as a SAG mill overload and grind-out.

Jan 1, 1983

By R. Spring

Artificial intelligence, and especially expert systems, are currently receiving considerable attention. Of interest to the control engineer is the utilization of these tools for real-time process control applications. To evaluate this technology, a real-time expert control system was implemented in one of the grinding circuits at Brenda Mines Ltd. The performance of this micro computer based expert system compared satisfactorily to the proven supervisory control system currently in use. The study confirmed the expectations that expert systems have potential for real-time, supervisory control of mineral processing operations.

Jan 1, 1989

By J Moffatt, T Payten, N Spooner, L Teixeira, L A. Balzan, G Wilkie, G Tsiminis

Fluorine is a penalty element due to its reactive nature. In acidic environments many fluorine minerals dissolve to form hydrofluoric acid (HF), changing processing conditions. When smelted HF can be released, causing negative effects to nearby people and the environment, as well as potentially damaging the smelter. Sale of ore with high fluorine levels elicit a financial penalty or are banned outright. Real-time sensors create the opportunity for instantaneous decisions on ore processing due to changing conditions. A fluorine sensor would allow rises in fluorine concentration in a processing stream to be flagged, and decisions on processing conditions or diversion to stockpile before processing could be undertaken. As fluorine is a light element, it is difficult to detect with in-field XRF devices and does not work well with PGNAA. There are currently no existing sensors to quantify the presence of fluorine in real-time, and thus decisions based on fluorine grade cannot be made at minute- or even hour-scales. Sensors designed to measure the presence of minerals that contain fluorine are a possible avenue to enable the real-time detection of this element. Mineral-based sensing may also give an added advantage of additional information about how the fluorine will react under different processing steps. The authors were given a grant under CRC ORE II (project number P1–005) to search for mineralspecific signatures suitable for real-time analysis. The work focused on novel regimes and applications of fluorescence as a means to detect specific minerals. The aim was to exploit fluorescence responses unique to minerals of interest in mining systems in order to produce sensors that address gaps in existing capability. After the successful discovery of signatures specific to two major fluorine minerals an additional grant (P1–014) was funded to develop the research into a prototype on-belt sensor, in partnership with Scantech International Pty Ltd. This paper details the development of a sensor package through multiple Technology Readiness Levels (TRLs) through collaboration with government/industry grant schemes, academics from university, and a sensor-focused Mining Equipment and Technology Services (METS) company. We give a brief description of the new sensor technique and provide a case study of multi-disciplinary collaboration.

Aug 24, 2022

By A. F. van der Merwe, R-D. Taylor, M. Jacobs, F. H. Conradie

Total bound moisture (TBM) is a typical quality indicator of industrial-grade gypsum. This gypsum is comprised of three distinct phases, namely anhydrite, dihydrate, and hemihydrate, of which only the latter is of much industrial use. TBM analysis is a lengthy laboratory procedure, and an artificial neural network (ANN) TBM inference measurement is proposed as a fast and online alternative. An ANN inference model for gypsum TBM based on plant data was developed. The inputs to the network were primarily focused on the plant's calciner, and different network topologies, data divisions, and transfer functions were investigated. Furthermore, the applicability of the TBM value as a quality indicator was investigated based on a gypsum phase analysis. A strong correlation between TBM and the gypsum hemihydrate and anhydrite content was found, validating the plant target TBM of 5.8% as a quality indicator. A network topology consisting of one hidden layer with logarithmic-sigmoid (logsig) and pure linear (purelin) transfer functions showed the best performance (R > 90%).

Oct 3, 2023

By T Belligoi

Diamond cores and drill chips provide the only direct physical evidence for ore containing rocks. Early characterisation of cores and drill chips is important as it provides critical information for downstream processing. Traditional characterisation techniques include visual logging by a geologist or analytic and spectroscopic methods but they are time consuming and can miss some important textural or geomechanical features.The goal of this work is to evaluate the application of image analysis to iron ore cores and drill chips and to suggest improvements to existing core-scanning and chip monitoring systems. Two samples of massive ore differing by their mineralogy and texture, as well as two different batches of drill chips, have been imaged and analysed. Results are compared in function of the imaging system and the classification algorithms.As a conclusion, despite the necessity for more testing and improvements in calibration and lighting, it is obvious that image analysis technologies can bring a lot of useful information in the perspective of a geometallurgical mapping of the deposit.

Jul 11, 2011

An image analysis system has been built which automatically digitizes camera input of rock fragments, analyses the digitised data to determine the sizes and shapes of the rock fragments, and outputs the analysed data to a printer in the form of a histogram or a scatter chart. The high speed of such a system allows for direct collection of data from material thrown into the air by blasting, material travelling on a conveyor belt, and material free-falling on to a stock-pile or into or out of a rock-crusher. Data on the blasted, un-crushed material provides information on changes in the lithology and structure of the rock face as it is quarried or mined: flatter fragments may represent approach to a brittle, unstable shear zone, or a change from sandstone to shale; so that the informa- tion reflects the effect on the sizes and shapes of the fragments by the blasting process and/or by the rock structure. The size and shape distributions of rock fragments produced during blasting and during processing may now be continuously monitored. Such detailed analysis of the results of fragmentation is labour-intensive and expensive when the size and shape distributions are obtained manually, but is cheap and efficient when using this image analysis system. Such a system will enable the results of blasting, quarrying, mining and crushing to be cheaply analysed and correlated with current and changing indus- trial practice so leading the way to increased productivity.

Jan 1, 1988

By Hao Zhang

Site inspection is an important component of safety management system. In current practices, the inspectors evaluate the safety condition on a construction site with the assistance of a standardised checklist. However, the checklist emphasizes on evaluating the implementation of safety management system, but provides limited task-specific check items for assessing whether the individual construction tasks are conducted under safe condition and in a safe manner. To address this issue, the research presented in this paper aims to provide safety practitioners with comprehensive and taskspecific safety information to promote effective risk identification and facilitate strategic risk control during site inspection. Specifically, this research first builds a project-specific safety information database, which stores potential risks and control measures for each construction task. The research team then develops a mobile decision support tool to retrieve information from the database and support safer decision-making on site. The tool supports users in two ways: one is to provide daily risk checklists and risk control strategies to guide step-by-step inspection alongside the project schedule; the other is to let users input any safety-related keywords during the safety inspection process and the tool returns relevant safety information by applying text mining algorithms. It is ongoing research. This paper presents an overall research framework and discusses the progress in developing safety database and data retrieval concepts. The outcome of the project will help enhance safety management practices and reduce possible risky working conditions on a construction site.

Aug 1, 2013

By M. Buxton

"Advanced data acquisition and process modelling technology provides online data and decision support about different aspects of the resource extraction process. Real-time approaches have recently been applied to utilize the value of this information for improved production control in mineral resource extraction in different operational set ups including coal, polymetallic ore and gold deposits. The key concept of these approaches promotes the change in paradigm from discontinuous intermittent process monitoring to a continuous process and quality management system in the resource extraction process. The framework includes a real-time feedback control loop that rapidly links online material characteristics data acquired during extraction at the mining face, during material handling and processing with a sequentially up-datable resource model. This will allow near real-time optimization of decisions related to long-term planning, short-term sequencing and production control. The contribution reviews recent developments in the three main constituents sensor based material characterisation, rapid updating of grade control models and simulation based optimization for improved production control. Technological readiness is assessed and critical gaps for further technology development are identified. The value added is illustrated by means of selected case studies. INTRODUCTION With the depletion of known and established mineral reserves, the decrease in head grades and the continuing demand of mineral raw materials by the modern society, future exploitation will move towards extraction of deposits under geologically more complex conditions. Complex deposits are characterized by a low continuity in grade, presence of deleterious elements such as arsenic and high irregularity in the geometry of the ore boundaries. The profitable exploitation of such deposits becomes significantly more challenging. To be able to better utilize such unconventional mineral resources of the future, smart autonomous mining systems are needed, which integrate local exploration of spatially varying material characteristics in–situ and have the ability to follow and extract the pay zones in the ore body while minimizing dilution (Buxton and Benndorf, 2013). The main barriers to overcome for the successful economic exploitation are: • effective grade control which will maximize resource potential along the whole value chain, • minimization of handling zero-value material introduced by dilution, thus • reducing unnecessary expenditure of energy and financial resources and • management and control of the geological uncertainty due to limited information available,"

Jan 1, 2017

Falling asleep at the wheel of a moving vehicle is not only dangerous but avoidable. It is implicated in up to 30% of all road fatalities in general and up to 65% of mining incidents involving haulage trucks. These types of crashes normally result in serious injury and/or fatality due to the lack of breaking that occurs. However, when a 300 tonne haul truck has a sleep related crash it is not only the safety of the driver that has a high price but also the commercial impact on the mines? productivity and efficiency. We have been developing our ASTiD technology which stands for the Advisory System for Tired Drivers to seamlessly integrate in to Modular Mining?s Dispatch system to provide real-time early warning fatigue risk management. The benefits being driver shift optimisation, sustained productivity and of course less accidents. By monitoring the drivers alertness levels in real-time using ASTID, the Dispatcher becomes empowered to make critical, management decisions that will ultimately prevent serious injury or loss of life and the driver gets to stop when he needs to and not just when he is supposed to. This paper shows how this integrated solutions works.

May 1, 2011

By F. T. Cawood, M. N. M. Cudjoe

The ability to conduct real-time material tracking in mines has been a long-standing challenge. Technological innovations such as radio frequency identification technology (RFID) have over the years contributed to the effective tracking of material flow and reporting of metal content. This paper outlines the laboratory procedures and results from testing the suitability of microdot technology as a viable technique for real-time material tracking in mining. The paper clarifies the reasons for conducting the test and presents the material safety data sheet (MSDS) from a South African and Canadian perspective. Microdots from three aerosol systems were immersed in water, heated to 100°C, and crushed into coarse and fine material. These tests were used to ascertain if the technology could withstand mining conditions. A strength, weakness, opportunity, and threat (SWOT) analysis was used to evaluate and compare microdot technology with RFID. It was shown that microdot technology has some potential to track ore parcels because data integrity was retained after exposure to post-blast mining conditions. However, more improvement is required to digitally detect microdots before the technology can be implemented at scale in the mining industry.

Apr 2, 2022

By Kevin L. Gering

A detection method and apparatus have been developed to perform real-time measurement of aqueous free cyanide, C-. A laboratory prototype can measure cyanide ranging from 5 micrograms ,per liter to 100 milligrams per ?liter for analysis times as short as 2 minutes per measurement. Sample size per measurement is typically only a few mI, thus? minimizing the waste volume produced from spent samples. The basis for this detection device is a quantifiable, stable affinity between the electrode material and free cyanide in the sample; The electrode exhibits piezoelectric behavior, allowing it to be used as a microbalance. This technology 'has experienced two generations of laboratory prototypes, and has been thoroughly tested to determine the operational sensitivity toward process variables such as pH, competing reactions, etc. The speed and ,accuracy of this method make it superior to conventional wet chemistry methods used for quantifying cyanide levels in water. A device based on this technology could be useful in areas involving process monitoring and environmental compliance, .particularly in the cyanide-based leach mining industry. Interest for this detector has been shown by the gold mining industry and others. Patent application is in progress.

Jan 1, 1998

By D Chalmers, C C. Harb

The detection and control of gas levels in mining is a continuing challenge for the industry. Standard detectors have many problems that could be overcome with laser based spectroscopic instruments, but to date these systems have not been suitable for mining conditions. This paper reports the development of a new digital data extraction scheme to modernise traditional cavity ring down spectroscopy (CRDS). CRDS is a direct cavity enhanced laser based absorption technique, which is used to allow the identification of an unknown substance by their molecular fingerprint; this unknown substance is identified by analysing the ring downtime of the light exiting the optical cavity. Traditional CRDS has many issues when analysing substances in hostile environments, or when multiple species may be present. This presents an alternative approach, called real-time CRDS (rtCRDS) that has the potential to overcome many of these issues and produces systems that could be used in the mining industry. The system utilises newly developed widely tuning quantum cascade lasers combined with improved optical cavities and novel digital data extraction to produce spectra over a 1500 nm range in a few seconds. The ring downtime measurements produced are accurate and have high sensitivity and maximum signal to noise ratio. This paper discusses the technique, illustrating the advantages compared to traditional systems and show real-time spectra for a set of molecules of interest to the mining industry. This paper also provided an analogy between this approach and that used in digital communications systems, and shows that this scheme is ideally suited to provide a network of sensors in hostile environments.CITATION:Harb, C C and Chalmers, D, 2015. Real-time methane detection – modern digital laser spectroscopy for hostile environments, in Proceedings The Australian Mine Ventilation Conference, pp 161–166 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 31, 2015

By N Jeannee, L Rattmann, M W. N Buxton, A deJong, K Nienhaus, A Soares, P Graham, A Korre, J Benndorf, D Buttgereit

The flow of information, and consequently the decision-making along the chain of mining from exploration to beneficiation, typically occurs in a discontinuous fashion over long timespans. In addition, due to the uncertain nature of the knowledge about deposits and the inherent spatial distribution of material characteristics, actual production performance often deviates from expectations. Reconciliation exercises to adjust mineral resource and reserve models and planning assumptions are performed with timely lags of weeks, months or even years.The key concept of real-time mining promotes a change in paradigm from discontinuous intermittent process monitoring to a continuous process and quality management system in the resource extraction process. The framework includes a real-time feedback control loop that rapidly links online data acquired during extraction at the mining face, material handling and processing with a sequentially updatable resource model. This will allow near real-time optimisation of decisions related to long-term planning, short-term sequencing and production control.The proposed framework integrates the following building blocks in a holistic manner: automated sensor-based material characterisationonline machine performance measurementsunderground navigation and positioningunderground mining system simulation and optimisation of planning decisionsupdating techniques for resource/reserve models.This paper introduces the real-time mining concept and the building blocks and provides a review of the state-of-the-art. Technological readiness of necessary building blocks is assessed, and critical gaps for further technology development are identified. The value added is illustrated by means of a case study.CITATION:Benndorf, J, Buxton, M W N, Nienhaus, K, Rattmann, L, Korre, A, Soares, A, deJong, A, Jeannee, N, Graham, P, Buttgereit, D, Gehlen, S, Eijkelkamp, F, Mischo, H, Sandtke, M and Wilsnack, T, 2015. Real-time mining – moving towards continuous process management in mineral resource extraction, in Proceedings Third International Future Mining Conference, pp 37–46 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

By Preben Ingerslev

Control of the reheating of ingots is based either on surface temperature measurements using optical pyrometers or on furnace set points and reheat time determined empirically. This paper presents a real-time mathematical heat flow model, named BESTT, which calculates the temperature distribution in an ingot cross section when reheated or cooled. The model runs on a 486 PC in less than one minute for a variety of ingot cross sectional shapes such as circular, square and with some considerations octagonal and heavy-cornered square. Initial temperatures can either be uniform or nonuniform while accounting for temperature dependent thermophysical properties. The model was developed and verified using 718 alloy ingots in box type furnaces. When integrated with on-line pyrometric measurements, BESTT can provide for improved feed back in the reheating control loop. The use of BESlT will assist in reducing energy costs, and improving product quality and consistency. EPD Congress 1994 Edited by C. Warren The Minerals, Metals k Materials Sodety, 1993

Jan 1, 1994

By J. P. McDonald

Exposure to particulates containing metals and metal fumes (PCMMF) is a potential concern in ore refining and smelting. Some metals of primary interest are arsenic, cadmium, copper and lead, which have been linked to various adverse health effects. The current National Institute for Occupational Safety and Health (NIOSH) sampling method for metals in particulates requires the use of a filter, precision airflow pump and laboratory analysis. A major concern with this method is the one-to-two weeks? wait before laboratory results are available for use in determining if additional controls are needed to assure adequate exposure protection for workers. Particulates containing these metals were sampled during sixteen sampling events at a copper smelter using the traditional NIOSH methods. Monitoring of particulates was simultaneously conducted using a TSI 8520 Dust-Trak real-time aerosol monitor with a 10-µm-cutpoint sampling inlet. NIOSH analytical methods related to particulates and metals (methods 0500, 0600 and 7300) were used to determine particulate mass and individual mass contributions of metals on sample filters. Linear regressions with y-intercepts forced to zero were developed to determine the relationship between the PM10 measurements recorded by the DustTrak and laboratory-reported total particulate mass, PM10 and respirable arsenic, cadmium, copper and lead concentrations. These linear regressions yielded correction factors that can be applied to DustTrak readings to obtain total particulate mass, PM10 and respirable concentration estimates for each of the four metals. The R2 (coefficient of determination) values from the linear regressions ranged from 0.65 for total lead to 0.91 for total copper. These results suggest that the DustTrak may produce real-time data useful in providing estimates for airborne concentrations of arsenic, cadmium, copper and lead in copper smelter particulates.

Jan 1, 2011

By D Matthews

With the increasing demand for quality-specific ores, coupled to the reality of even more complex minable iron ore reserves, there is a growing need for real-time online material analysis of plant feed and product. For a full system mass balance, the combination of conveyor weight scales, flow and density transmitters are required. This alone does not guarantee product grade. For optimal process control and material blending, real-time online elemental scans in combination with the mass weighting is becoming more than a ‘nice to have’. These elemental scans located at key positions, enable the mining and plant operators to make informed decisions timeously, therefore ensuring product outcomes and optimising operations where material grade and the control thereof are important. Typically, these units follow the mining and primary crushing circuit as well as on the product conveyors, low-grade conveyors and tailings lines. Deployed after the primary crushing circuit, an analyser acts twofold:1. guaranteeing mining production, and2. processing facility feed blends.The analysers on the product conveyors guarantee saleable product. The analysers on the low-grade conveyor and tailings line complete the elemental balance and identify the potential of the low-grade and tailings for future processing. The system losses (accumulation) are calculated to determine the amount of material ‘lost’ during the processing stage which does not report to any of the aforementioned and can be used as a measure of the efficiency of the plant. A further advantage of the real-time online analysis of material is that immediate intervention can be taken in the event that the product is not of saleable product grade requirements. In the Khumani Iron Ore mine, Northern Cape, South Africa, run-of-mine (ROM), product and control analysers were included. Run-of-mine and product stockpiles are certifi ed, low-grade material is not currently directly measured, but calculated from the internal control loops. Iron units are reconciled between product and feed material.

Jul 11, 2011

By C. L. Karr

Establishing suitable control of pH, a requirement in a number of mineral and chemical industries, poses a difficult problem because of inherent nonlinearities and frequently changing process dynamics. Researchers at the U.S. Bureau of Mines have developed a technique for effectively controlling such systems. This technique successfully combines the process control capabilities of fuzzy logic and the search capabilities of genetic algorithms. Fuzzy logic offers an effective mechanism for handling nonlinearities, while genetic algorithms can provide fuzzy logic controllers with real-time adaptive capabilities. This Bureau-developed technique is applied to a laboratory acid-base neutralization experiment. Nonlinearities in the laboratory system are associated with the logarithmic pH scale and the changing process dynamics are due to alterations in pH and buffering capacity input solutions. Results indicate fuzzy logic controllers augmented with genetic algorithms offer a powerful alternative to conventional process control techniques in such nonlinear, rapidly changing systems.

Jan 1, 1992

By Adrian Moore, Alan Richards

A real-time system for prediction of the effect of meteorological conditions on airblast overpressure levels has been established in the Hunter Valley Coalfield in Australia. Real-time meteorological data from continuously operating sounding equipment and a predictive meteorological model is input to an atmospheric refraction model that enables the effect of meteorology on airblast overpressure levels in the area surrounding the blast site to be evaluated. Graphical outputs from the model, which are superimposed over a scaled airphoto of the mine and surrounding area, show the extent that airblast levels will be increased. When combined with inputs that quantify the effect of blasting specifications, the airblast levels that will result in the surrounding area from the combined effect of blasting specifications is determined. The model permits those responsible for blasting to make more accurate decisions on suitable times that blasting may take place to conform with applicable airblast limits.

Jan 1, 2009

By C. L. Karr

Researchers at the U. S. Bureau of Mines have developed a technique for producing adaptive control systems using fuzzy logic and genetic algorithms. These controllers can be used to efficiently manipulate complex systems in real-time. Furthermore, they can achieve an acceptable level of control despite limited feedback in the problem environment. The control systems that result from the implementation of the Bureau-developed technique are able to recognize when changes have occurred in the problem environment, evaluate the magnitude of these changes, and alter the strategy being used to control the problem environment. Fuzzy logic is used to provide the controller with a rule-base that mimics the "rule-of-thumb" approach generally adopted by humans in the area of process control. Genetic algorithms are used to provide the controller with the adaptive capabilities necessary for the control of complex time-varying processes popular in the minerals processing industry. The effectiveness of this technique is demonstrated on a laboratory pH titration system. The pH system includes a changing setpoint, titrants with varying concentrations, and the possible addition of a buffering solution.

Jan 1, 1993

By Werner Klein

The utilization of production facilities in an optimum way, with reliable due date fulfillment, reducing raw material and energy consumption, are challenges iron and steel companies are facing in their business every day. By using an APS system such goals can be achieved to increase the competiveness of iron and steel producers. A sophisticated APS supports the overall planning process by applying complex rules based on product and order mix, its production routings with corresponding processing and transport times and resource availability. Specific technological as well as steel grade and energy related constraints are also considered to meet company specific KPIs. A core feature of APS solution is to react online on deviations to plan during the production process. Deviations such as nonconformance of intermediate material attached to an order, sudden production delays, unavailability of important production resources, makes it necessary to update the production plan. In general the task of APS is to support the preferred work-to-order concept, by assigning work-orders to available production facilities along the product specific process route and generate optimized material sequences for critical work centers.

Aug 17, 2017