Bern Klein

This thesis aims to investigate the impact of automation on the mining industry’s labour force by analyzing the implementation of this technology in the Highland Valley Copper (HVC) mine operated by Teck Resources in British Columbia. The mining industry has entered Industry 4.0, which has redefined technology's role in the processing of minerals and metals. A popular technology adopted by mining companies is automation, which promotes the use of machines to assume human-led jobs. The shift in the way minerals and metals are processed because of technology has resulted in the mining labour market experiencing drastic changes in job descriptions. That is, entry-level jobs with manual, repetitive and physical characteristics, such as truck drivers, are at high risk of being replaced by automation with the adoption of autonomous haulage systems. The shift in the labour market has influenced the skills that mining companies are searching for, which now tend to be more technology-intensive and often require a high level of professional training. Through a case study analysis of Highland Valley Copper Mine and by conducting a series of interviews with strategic stakeholders who provided a deep and honest insight into their perspectives, this research found that automation strongly impacts mining communities’ ability to access jobs and enter the mining workforce. Although the benefits of increasing automation in mining operations are numerous, significant risks to the business and society must be adequately managed. The analysis provided recommendations for different stakeholder groups, such as government, mining companies, academia, and associations, unions and institutions, on their roles and responsibilities in supporting the mining labour force for a just, ethical, sustainable, and commercial transition to automation.

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Vertical Roller Mill (VRM) technology was developed more than four decades ago and has found applications mostly in cement grinding operations and in power plants for coal grinding. VRM technology has been well documented in literature to offer energy consumption reduction (from 15% to 30%) over conventional comminution units and circuits. These proven benefits of the technology have attracted the interest of the minerals industry.For this study, a prototype pilot-scale vertical roller mill with a ball race design was purpose-built and commissioned at Sepro Mineral Systems in Canada. Extensive bench-scale ore preparation and characterization tests, followed by pilot-scale VRM experimental programs, were conducted to determine the relationship between size reduction and energy requirement considering all critical operating variables. The effects of feed physical properties (top size, fines content), machine operating variables (applied compression pressure, table rotation speed, feed rate), and feed water content on product particle size and specific energy consumption were studied. Upon optimization of the feed and operating parameters, closed-circuit locked cycle tests were conducted to more accurately determine the energy consumption and ground product particle size distribution that simulates a production-scale comminution process flow sheet. Further work and recommendations were made based on a newly developed understanding of wet comminution using VRMs.

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Geotechnical characterization is a fundamental part of orebody knowledge. Traditional classification systems have been updated through the years and numerical models have been introduced to support engineers in gaining a better understanding and a more accurate prediction of mine deposit characteristics. However, current mining scenarios have pushed for a deeper comprehension of mine deposits, requiring more objective data to reduce uncertainty in the decision-making process. It has been observed that data collection programs present drawbacks affecting the representativity of the geotechnical data collected, to which predictive models and new digital tools have been presented as a solution. In this line, the novel Minpraxis tester (MPT), has been developed to expand the characterization by increasing the volume of data. The MPT is an instrumented roll crusher that can provide geotechnical information (IS50) while crushing exploration drill core samples that are prepared for metal assays.The purpose of this research is to propose a methodology to increase the spatial resolution of geotechnical characterization data using the novel MPT and some geological features. As part of the methodology, core logging techniques and traditional geotechnical tests, such as point load test (PLT) and uniaxial compressive strength test (UCS) are used. Also, a methodology to process the MPT results is developed to relate them to comparable geotechnical parameters.Results showed that the proposed methodology allows for relating the MPT responses to conventional geotechnical tests (PLT and UCS) at high levels of accuracy (±15%). Linear regression was found to provide models that are easy to implement and interpret. For a satisfactory application of the methodology, an accurate geological description was required to understand the MPT responses and to improve the geotechnical models. This research demonstrates that MPT provides the opportunity to improve geotechnical orebody knowledge. Unlike traditional tests, the MPT can increase the amount of characterization data while using samples that are not usually considered for collecting geotechnical data while capturing other sample characteristics (e.g., veins, texture fractures), reflecting on the rock hardness variability. The MPT can rapidly generate geotechnical data that can be easily correlated to standard geotechnical tests.

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Traditional geotechnical and geometallurgical tests are laboratory based, have strict sample requirements, and depend on the preparation of samples; due to these characteristics, traditional tests cannot realize rapid and real-time ore strength and hardness monitoring. Meanwhile, various sensors have been applied in mining engineering in exploration and operation, proving their mineralogical feature identification capabilities. The influence of mineralogy on ore strength and hardness has been widely discussed and defined as one of the major factors related to rock strength. To evaluate the capability and applicability of sensor scanning for ore hardness prediction and improve the efficiency and immediacy of geotechnical and geometallurgical tests, this thesis conducted a laboratory-scale investigation of X-ray transmission (XRT) scanning and a high-resolution strength testing response to copper-gold porphyry half core samples. The laboratory procedure included manual mineral identification, XRT scanning and strength measurement. The qualitative analysis results of XRT and high-resolution strength data showed that both the XRT and the high-resolution strength tester had apparent responses to major mineral veins and mineral assemblages. Metal-bearing minerals (e.g., sulfide, iron oxide) showed high energy attenuation values and high relative densities by XRT, while quartz gave low values on these two parameters by XRT. The high-resolution tester response was related to the Mohs hardness of minerals. Generally, soft minerals decrease the strength, while hard minerals increase the strength. The quantitative analysis between XRT and high-resolution strength data revealed that it was not possible to correlate with a simple mathematical equation. Two separate characteristic values of XRT and high-resolution strength were calculated to study their response to surface mineral composition, collected by micro X-ray fluorescence scanning, μXRF. Results showed that both XRT and strength data had a strong correlation with several minerals. A multiple variable linear regression model was developed to relate μXRF to XRT responses. However, the regression of μXRF to strength data was found not reliable. According to current results, mineral textures affect ore strength, and XRT has the potential to scan and indicate changes in ore strength, but it was not possible to predict strength using either the XRT or μXRF scans.

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The traditional approach to evaluating the metallurgical behaviour of different types of rocks considers testing samples under conventional methodologies. Results become the key parameters for geometallurgical modelling and plant design optimization. The costs of testing, the involved times, and the quantity of required samples are the main limitations to increasing the volume of data, impacting the decision-making process and consequently increasing uncertainty. The more challenging conditions of current mining projects have pushed the industry to develop alternatives to increase orebody knowledge. It has been identified that advanced core logging is fundamental to having a better understanding of the orebody. Based on the above, the purpose of the current research is to develop a methodology to generate support data for the geometallurgical modelling of grindability indexes and to evaluate if predictive models can be proposed by using a full-scale prototype of the novel Minpraxis Tester (MPT), which is able to characterize the strength of the rock along drill cores.Core logging is performed on full drill cores to identify geological features present in the samples and to establish geometallurgical groups. MPT of half cores and lump rocks and conventional grindability tests are performed on each group. Finally, a methodology is developed to manage the MPT results and compare them with conventional grindability measurements. Results show that MPT responses could be successfully correlated with the drop weight index as well as the Bond work index when testing half cores and lump rocks allowing nomination of potential proxies, and generating predictive models based on simple linear regressions that can predict the grindability indexes with no bias within ±15% and ±20% of error, respectively. It was also identified that the MPT responses depends on the geological conditions of the samples (microfractures and veins status), so accurate core logging is required to analyze results.This work shows that by using the MPT, there is an opportunity to produce data to support the geometallurgical modelling of grindability indexes and the grinding operation parameters by taking advantage of samples not usually considered for geometallurgical testing (e.g., resource drill cores and blast hole cuttings).

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The purpose of this study is to develop a model to assess the economic value delivered by deploying a new ore sorting solution in an open pit environment. ShovelSenseTM is a technology based on x-ray fluorescence sensors mounted on the bucket of the shovels in order to execute the ore sorting at the mining face in real time. This is a different application of the technology that was previously used in the mining industry on conveyors belts.The model was built using two steps. The first stage of this study was built using ExtendSim, a discrete event simulation software. This technology is widely used in the mining industry mainly modeling hauling and mineral processing systems. What was modeled in ExtendSim is a conventional open pit based on a shovel-truck system that has three possibilities or destinations (waste dump, heap leach and mill) to send the material extracted from the mine, where the destinations are constrained by a COG. Furthermore, the DES model is capable of reading the information coming from a resource block model via a text file.The second stage takes the outputs produced in the simulation (tonnage and grade distribution per destination) and applies a set of recoveries, metal prices and operating costs in order to model the economic case.The value delivered by the technology is estimated by running two sets of data in the form of block models, where one set is influenced by the technology and the other is not. Ultimately, the economic assessment compares the two options to determine which delivers the most benefit. Finally, the comparison shows a substantial economic value delivered by deploying ShovelsenseTM into the open pit operation analysed in this study. Furthermore, the unlocked value by the technology is the result of optimizing the material assignation to the different destinations in the system.

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Industry and society are at the beginning stages of the 4th Industrial Revolution or in the case of mining, known as Mining 4.0. Among the multitude of drivers of the new revolution, automation and digitization will transform the nature of human capital within the mining industry. Skill polarization will occur with a reduction in repetitive, low skilled jobs while high skilled programming and engineering jobs will increase. This polarization will benefit those with degrees and access to education in urban areas while the local remote and Indigenous communities will face greater challenges in getting employment in the mines which will increasingly be run by complex smart integrated systems. Extended Reality (XR) encompasses Virtual (VR), Augmented (AR), and Mixed (MR) realities and these methods could provide learning benefits, remote learning/collaboration, and translate to considerable cost and time savings if used for the training of new workers or for the up-skilling of current employees. Despite the benefits of XR methods, there is limited adoption within the mining industry. In order to understand the reasons behind the lack of adoption, a Comprehensive Literature Review was conducted to identify experts and a cross sectional survey was designed and distributed. The research questions attempted to be answered were: what are the perceived advantages/disadvantages, barriers, and timeline for XR adoption? Results indicate that mining company management misunderstands the usage of XR, hardware for XR methods needs more development and software should be more available for companies. The timeline for adoption seems to be 1-3 years for VR, and 3-5 years for AR/MR methods, and recommendations were provided for implementation.

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The complexity degree of a mining plant’s comminution circuit is critical for allowing the processing of low-grade iron ore deposits. Considering that the comminution stage is responsible for most of the energy consumption in a mineral processing plant, the pursuit of energy-efficient technologies is a major challenge of the mining industry. The High Pressure Grinding Rolls (HPGR) have been applied for over 20 years and is widely recognized in terms of energy savings. However, the limited access to industry and academic studies about the HPGR performance and the lack of a widely industry accepted bench-scale laboratory test for sizing and modelling HPGRs are major hindrances that must be addressed in order to promote the machine acceptance and implementation.The research's main objectives were to evaluate the HPGR amenability to comminute iron ore in a two-stage HPGR circuit and extend the applicability of Davaanyam’s (2015) Direct Calibration and Database-Calibrated methodologies for predicting the energy consumption and size reduction of HPGRs through laboratory-scale piston-press tests. The HPGR performance and modelling evaluation for quaternary and quinary applications were supported by a combination of laboratory-scale testing, pilot-scale testing and modelling work.Results obtained from the research showed that the HPGR is suitable for comminuting iron ore in open circuit quaternary and closed circuit quinary applications. The performance evaluation revealed a strong linear relationship between the machine’s specific pressing force and net specific energy consumption. The size reduction also increased linearly with the increase of the pressing force. The ore moisture content revealed to be detrimental to the HPGR’s throughput at high concentrations but did not impact the performance in terms of size reduction. The Direct Calibration methodology was successfully applied to iron ore for quaternary applications, but the current Database-Calibrated regression models resulted in poor energy-size reduction predictions. because the variable levels for the quaternary application extended beyond the ones used for developing the current regression models. The results indicate that the database needs to be extended to finer sizes, higher moisture levels and possibly ore types.

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Producing mines and new projects are forced to mine lower grade and more complex ores. As a consequence, there is an increased need to monitor penalty elements. The penalty elements are the constituents that reduce the quality, and therefore the value of the concentrate. Many of these constituents are low atomic number elements that are not adequately detected with most existing sensors. The case study evaluated in this work, is an operating iron mine where silicon, aluminum, potassium, phosphorus, and sulfur are penalty elements.Real-time ore monitoring and Sensor-Based Sorting utilize different analytical techniques that serve as sensors. Many of the more studied and used analytical techniques, such as ICP (Inductively Coupled Plasma), XRD (X-Ray Diffraction), XRF (X-Ray Fluorescence), PGNAA (Prompt Gamma Neutron Activation Analysis), or XRT (X-ray Transmission), require long scanning times, time-consuming sampling procedures or cannot detect low atomic number elements.Laser Induced Breakdown Spectroscopy (LIBS) is a proven analytical technique that can analyze all elements in the periodic table in real-time. It had advanced significantly since its conception when it was a fragile laser technology. Especially after 2012 and 2021, LIBS received much attention when NASA successfully used it on the Mars rover to analyze soils and rocks at a distance. In this thesis, the experiments were done with crushed Run of Mine iron ore material to investigate the reconciliation between the bulk analysis by conventional techniques (assay) versus surface analysis provided by LIBS. Univariate and multivariate models achieved between 88 to 99% correlation with the assay results. The challenges presented during this research can be explained by low signal-to-noise ratios, self-absorption phenomena, low concentration of the element of interest, and the available low energy LIBS setup used in the study. The results presented indicate that LIBS can be used to accurately perform monitoring and sorting of crushed iron ore, with multiple economic and environmental advantages.

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High-pressure grinding roll (HPGR)-based circuits are increasingly applied to replace the semi-autogenous grinding (SAG) mill circuits due to their higher energy efficiency and lower operating cost. A novel HPGR circuit is proposed to replace conventional ball mills and extend the energy benefits for final grinding before the flotation or leaching circuit. However, the typical moisture of the ball mill feed is 20–35%, while the highest acceptable feed moisture to the HPGR is ~10%. Therefore, replacing the ball mill with HPGR technology requires a size classification and dewatering system. The purpose of this thesis was to assess the applicability of a variety of size classification and dewatering technologies to a novel HPGR comminution circuit. A ranking system was developed to identify the size classification and dewatering technologies with the most potential for the proposed circuit. The ranking matrix was developed using criteria essential for selecting equipment—with weighting factors assigned for each criterion. The ranking results for size classification equipment showed that the screw classifier scored the highest, followed by the high-frequency screens and the Derrick® Stack Sizer®. Based on the ranking results, test work was conducted to evaluate the capabilities of the selected equipment to process the material for the novel circuit. As a result, the size classification using the screen or screw obtained efficiencies of over 85%. For the dewatering equipment ranking, the dewatering screw scored the highest, followed by the pan filter and the dewatering screen. Based on the ranking results, test work was conducted with these three selected pieces of equipment. The vacuum filtration and the screw could achieve a moisture content below 10%. Therefore, both technologies were suitable for the novel circuit.With the ranking and test results, three combinations of equipment were suggested for the novel HPGR circuit for fine grinding: 1- Screens, follow by screw dewatering 2- Screws, follow by dewatering screw, and 3- Single-stage of screw classifier. The three proposed circuits could achieve the target moisture (less than 10%), but only the first to can achieve the target fine content (less than 5%).

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Current technology and simulation software used in the mining industry fail to factor in the effect of liner type and wear on ball mill grinding efficiency and throughput. This thesis provides a comprehensive analysis of key mill operating parameters and addresses the following key research question: how does liner type, lifter face angle, and liner wear affect mill grinding efficiency?The hypothesis is a lifter’s face angle drive a ball mill’s grinding efficiency and throughput independently of the type of liner used. To test this hypothesis, plant data and the profile and lifter face angle of the three most widely used liners are analyzed in terms of mill power draw using Morrell’s model C and MillTraj®.Results show the mill ball charge shoulder angle is strongly affected by the liner lifter’s face angle and that Morrell’s Model C could be improved by including a correction parameter that reflects the power draw of a mill along the service life of its liner. The correction parameter is to reflect the effect of wear on the shoulder angle. Results show that mill grinding efficiency decreases as the liner wears but that efficiency can still be maintained by adjusting the mill speed. The operating work index was found to be an effective tool for identifying increased grinding inefficiency along the liner’s service life.Further research is required to include a wear parameter that indicates the liner profile in Morell’s Model C power equations. It is also necessary to carry out additional research on variable speed drivers (VSD) for mill motors, which could potentially pay back the cost of adding a VSD on ball mills due to the increased grinding efficiency.

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The gravity-induced low speed stirred milling technology, commonly referred to as tower mills, are widely used for fine grinding due to their high energy efficiency compared to conventional tumbling mills. Moreover, the lower operating cost, shorter installation period and simpler operating strategy make it attractive for many mines. Researchers have attempted to develop an ore characterization method and mathematical models for tower mills. However, there is no well-established universal fine material characterization method for both the grindability assessment and modeling of tower mills.In this study, a modified Hardgrove mill fine material characterization method was developed for the tower mill grindability assessment. The test result was integrated into the fmat breakage model, which incorporates both the effect of specific energy and particle size. Several industrial tower mill grinding circuit surveys were conducted to provide the information regarding the operating conditions and grinding product size distribution. The ore breakage model, the size specific energy level model, internal classification model and tower mill power models were integrated into a mass-size balance model to simulate the tower mill performance. A sensitivity analysis was conducted to simulate the tower mill performance under varied stirrer speed and media charge.Results obtained from the model and simulation work show that the developed model is capable of predicting the tower mill grinding product size distribution with adequate accuracy. The sensitivity analysis indicated a new opportunity to control the tower mill performance by adjusting the stirrer speed rather than by the conventional media addition strategy.

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Mineral processing productivity relates to a range of operating parameters, including production rate, product grind size, and energy efficiency. Variations in ore properties and operating conditions change the comminution dynamics, resulting in a constant deviation from operational goals. Although most processing facilities currently use fixed speed grinding mills, variable speed drive is considered to provide an important control variable that can contribute to achieving operational objectives.This thesis examines variable speed ball mill performance under changing operating conditions to recommend operating conditions for the Copper Mountain Mine. JK SimMet, a very powerful predictive tool, was used to estimate grinding circuit performance and mill power consumption. Samples and operating data were collected directly from the Copper Mountain Mine to build a calibrated model. Appearance (breakage distribution) functions of different geo-samples were measured and used to predict plant performance under different ore property variations.The results indicate that higher mill speed and lower ball load operating strategies are preferable with respect to energy savings in variable speed ball mill operations. Ore characteristic variations at the Copper Mountain Mine are significant and can cause large oscillations within mill operations. Thus, ore blending in Copper Mountain should be done carefully and cautiously. However, in combination with traditional optimization methods, ball mill grinding speed can be used to control energy input and offset the influences of ore variability. Optimum ball mill operating conditions can be determined based on circuit design and operating dynamics for any given run-of-mine ore.

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Sensor-based sorting is perceived as a feasible solution for some of the most critical aspects of mineral processing. There are two basic classes of sensors, 1. those that measure a property characteristic of the bulk of a particle; and 2. those that measure a property of the surface of a particle. For the second class, the surface measurement is then correlated to the bulk property of interest. The correlation does not only depend on how well the sensors can analyze the surface, but also on how well the surface correlates to the volume of the rock. The correlation is even more complex since only part of the rock surface is scanned by an actual sorter. Thus, the heterogeneity within each particle, defined as intraparticle heterogeneity, is an important variable to be characterized. The main objective of this work was to design and develop a method for rock surface mapping to assess intraparticle heterogeneity and to evaluate the correlation between surface grade and bulk grade for run of the mine or primary crushed rocks. The XRF mapping technique developed, and the procedure selected to analyze the mapping data, were described and applied to two porphyry copper ore samples. According to an univariate statistical analysis, for the samples analyzed, copper and iron data distributions did not follow either normal or lognormal distribution. Median and median absolute deviation were proposed as the best parameters to summarize the surface grade and the intraparticle heterogeneity, respectively. The median value of the surface grade data showed the best correlation to the bulk grade of the rock for both elements.For the copper ore used in this work, with mainly vein type mineralization, the one-dimensional heterogeneity assessment showed a high degree of intraparticle heterogeneity. This characteristic of the ore might generate poor reproducibility in the results of an XRF sorter when sensing only one face of each rock. The variogram was evaluated as a measure of heterogeneity in two dimensions. Two-color mapping method was selected to display the data collected in the XRF mapping for both samples analyzed.

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Currently, there is no standard recognized bench-scale laboratory test for sizing or modelling a high pressure grinding roll (HPGR) in hard rock mining. As a result, metallurgical studies are prohibitively expensive and not economical for early-stage projects. To be adopted as a standard industry test for the HPGR, a bench scale test must: 1) use the same breakage mechanism as an HPGR, 2) produce results that are reproducible by independent metallurgical laboratories, and 3) apply to full-scale HPGR in a non-proprietary manner for engineering design.In 2015, the Piston Press test Database Calibrated and Direct Calibration methodologies were developed at the NBK Institute of Mining Engineering at the University of British Columbia. These methodologies can calibrate Piston Press test results to the HPGR performance using a UCS machine to define energy breakage relationships. This thesis developed a multi-stage program for facilitating the transfer of these methodologies to industry. This program formalized Piston Press test into a standard operating procedure by examining the effects of moisture, sample preparation, and material porosity. The results of the program demonstrated the Piston Press test to be reproducible. In addition, the results validated the Piston Press test Database Calibrated and Direct Calibration methodologies for a full-scale HPGR closed circuit.The program results indicate that an increase of moisture 1.5% to 5% during high-pressure compression breakage results in improved reduction ratio performance and has a negligible effect on the specific energy consumption of the sample. Material porosity was found to be an indicator of ore amenability to high-pressure compression breakage. Duplicate test-work conducted at UBC and at an independent laboratory demonstrated the Piston Press test is reproducible and can be adapted to varying piston press machine configurations. Both the Database Calibrated and Direct Calibrated methodologies are suitable for simulating full-scale HPGR. The simulation methods developed in this research can be easily applied and adopted by industry.

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With sensor-based ore sorting attracting more attention among the industry leaders, and in an effort to show the potential for sensor-based ore sorting technology, this research takes a particle sorting approach and looks at sorting low-grade and waste rock stockpiles to concentrate the misplaced mineralized rocks and generate value.The results from the optical sensor showed that where there was a visual distinction between the mineralized and gangue material, this sensor managed to identify each group well. Despite using a multivariate linear regression (MLR) analysis, the electromagnetic sensor did not predict the grades effectively.The X-Ray Transmission (XRT) sensor performed quite well for both base metal and gold samples. One recurring problem was the presence of iron minerals such as pyrite that, due to their relatively high atomic density, tarnished the sorting results.With elemental distinguishing capabilities, the X-Ray Fluorescence (XRF) sensor boasts great potential for ore sorting. Both single and multivariate linear regression analysis were used to analyse the results from the XRF sensor. Although, while overall satisfactory results were obtained from the XRF sensor, sensor capabilities in actual dynamic sorting cases need to be assessed.Recommendations for future work can be on different aspects of this work. One would be to try to improve the static, bench-top testing facilities so they represent dynamic sorting scenarios better, such as use of a conveyor-type platform where rocks can pass under a sensor. If a similar study is to be performed, it is highly suggested to focus the efforts on one mine, one size fraction (preferably -50 mm +37.5 mm) with a larger number of particles.In terms of continuation of this work, it would be best to take these tests to the next level and perform bulk sorting tests to determine how these bench-scale tests correlate with bulk dynamic sorting results. Also, a detailed economic analysis based on these results would yield valuable results.

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Prediction of cave fragmentation has been one of the biggest concerns for caving operation, since the inadequate assessment can potentially result in loss of project value and safety. The spatial variability of the natural fracture network holds significant implications with respect to block cave mine fragmentation. In this thesis, an in situ fragmentation model is generated, based on Discrete Fracture Network (DFN) models. The volumetric fracture intensity value (P₃₂), derived from the DFN model, is used as an indicator of the rock mass’ structural character, and it provides a direct link to rock mass fragmentation. Major structures were included in the model in a deterministic manner, and the spatial variability of the fracture intensity was analyzed to derive a geostatistical model of rock mass fragmentation. The fragmentation ‘block model’ was then superimposed onto a PCBC draw schedule model, in an attempt to link fragmentation and height of draw.Poor data can potentially compromise DFN analysis, and may result in flawed validation and understanding. At the same time, it is important to define clear and objective methodologies, when analyzing field data, and when deriving input for DFN models. Piecewise Linear Interpolation and recreation of the conceptual DFN model are both used to study the influence of fracture intensity interval length and role of human uncertainty, on the final DFN-derived 3D spatial model. The results show that interval lengths are related to a resolution that can be effectively used in large-scale 3D continuum models, to represent the Representative Elementary Volume (REV) for the rock mass. A digital image processing technique is applied in order to assess caved ore fragmentation. Validation of this method has been gained from the study of lab experiments. Furthermore, a conversion factor for relating 1D image-based measurement to 3D objects is calculated, since the DFN-based in situ fragmentation model yields volumetric size distribution, whereas image processing techniques yield equivalent spherical diameters. Finally, by using the above-mentioned input data analyses, this thesis investigates the possible links between natural fragmentation, secondary fragmentation, height of draw, and observed over-sized material and hang-up.

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With extraction of low-grade and high throughput deposits, elimination of tonnes of uneconomic material is highly desired to reduce energy consumption and water usage in the mine/mill production cycle. Even though technologies such as sensor-based sorting has wide application for pre-concentration purposes, effectiveness of sorter systems and key parameters for sortability of a material are still in the developmental stage. Number of factors such as grade variability, mineralogical alteration and ore blending scenarios during material handling will significantly affect contents of a material resulting in unforeseen changes in downstream processes. For these reasons, the ‘ore heterogeneity’ parameter is studied to evaluate sortability of an ore material under varying mine production scenarios.Production data, drillhole data and representative drawpoint samples were provided from the New Afton copper-gold mine located near Kamloops, BC. The New Afton mine utilizes the block caving method for extraction of ore from the copper-gold alkali-porphyry deposit.The distribution heterogeneity (DH) parameter is estimated for the data sets and the quantity of potentially removable material ahead of delivery to mill is studied. The DH is defined by variation of grade of a group of samples that constitute a lot, i.e. a group being an equal tonnage of material drawn from a drawpoint and the lot being the drawpoint. With this approach, the DH is analyzed across drawpoints, vertically within a drawpoint and along drill holes with changing vertical intervals of 0.5m – 10m. The DH values are compared with copper grades and an inverse relationship is found. This finding indicated that sortability of ore material can be defined by a heterogeneity parameter, especially the information can be obtained earlier from drillcore samples. The drillcore information can indicate a measure of heterogeneity and related copper grade of an in-situ material in advance of assay samples or sensor detection where a certain degree of mixing has occurred.Overall, 27% of the sample data from the New Afton historical production record has grades less than 0.4% Cu, which is the current cut-off grade, and it correlates with relatively high heterogeneity and presents an opportunity for sorting and feed grade upgrade.

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High pressure grinding rolls (HPGR) are becoming an increasingly popular energy efficient solution for comminution of hard rock ores. A significant barrier to the increased adaptation of HPGRs is the current requirement for large amounts of sample for pilot testing.The primary objective of the research was to develop a DEM based computer model for an HPGR to analyze the particle behavior in the unit and to predict its sizing information. EDEM, a DEM based software, was used to model the pilot scale HPGR unit and single particle compression test was used to evaluate the particle breakage and then used as an input parameter for the simulations. The results obtained from the simulation were then validated with the results from the pilot scale tests.Results obtained from the simulation suggested that a DEM-based model can be used to identify the pressure/force distribution profile for an HPGR roll surface that can then be used to design the appropriate piston geometry to match the HPGR pressure profile. Also, the developed HPGR model was used to estimate the critical sizing information for certain samples and machine operating conditions. The model generated similar trends as the pilot scale test with a lower magnitude of m-dot and specific energy consumption primarily due to the absence of a packed particle bed.The HPGR model, combined with powerful computers and larger sample masses for simulation, can be used as a procedure to size and select an industrial HPGR unit and to analyze the equipment behavior under various operating conditions and feed characteristics.

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Stirred media mills are relatively new to mining industry, and several new technologies have been developed such as the VXPmill (vertical stirred mill). There is little technical understanding of optimizing and scaling-up of the VXPmill. This thesis addresses both of these issues and therefore supports commercial applications of this vertical stirred mill. Stirred media mills are influenced by a great number of operating variables. A study was conducted to understand the influence of mill speed, feed particle size and, slurry density and rheology on the VXPmill performance. For scale-up, a study was conducted to compare the batch recycle and the pendulum testing procedures. A scale-up demonstration study was also done utilizing the pilot-scale (VXP10) mill and the full-scale (VXP2500) mill to validate the procedure.The following are the main findings from this work:There is an optimum tip speed such that if too high (12 m/s) results in energy losses due to mechanical friction and heat. If too low (3 m/s) there are insufficient stresses to promote breakage. The optimum tip speed was found to be about 7 m/s.Feed particle size is an important variable when predicting the energy-size reduction relationship. A coarser feed requires more energy than a finer feed to achieve the same grind size. The batch recycle testing procedure overestimates the energy consumption as compared to the pendulum test over a broad range of grind sizes. Therefore, it should not be used for scale up applications. However, the pendulum test can be used to predict energy requirements for scale-up.By utilizing the VXP10 mill, the stress intensity of grinding beads and specific energy input control the grind size for the comminution of feldspars-quartz ore. At optimum stress intensity, the energy utilization is maximum. For the effective and accurate scaling-up of stirred media mills, it is extremely important that both the pilot-scale and the full-scale mills are operated at relatively similar operating conditions, and treating similar material of the same feed particle size. However, both mills should be operated at their optimal flow rates.

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In the past 20 years, the energy-efficient comminution technologies, including high pressure grinding rolls (HPGR) and high speed stirred mill, have been developed and adopted in the hard-rock mining operation in order to reduce the energy consumption and improve the process performance. The combination of HPGR and stirred mill in a single flowsheet without tumbling mills has been demonstrated to be technically feasible. This research focused on the energy and cost comparisons of the existing AG/SAG ball mill circuits with two proposed comminution circuits, including an HPGR - ball mill circuit and a novel HPGR - stirred mill circuit.The main objective of this research was to advance the understanding of the potential benefits of the proposed HPGR stirred mill-based comminution circuits for low-grade, high -tonnage base metal operation. Samples and operating data were collected directly from the existing SAB/AGBC/SABC circuits to establish a base case for comparison. To support the base case, the existing circuits were fitted and simulated using a JK SimMet® model. Specific energy requirements for the proposed HPGR - ball mill circuit and HPGR - stirred mill circuit were determined from a pilot-scale HPGR and stirred mill test, in association with a JK SimMet® simulation.Results obtained from the research showed that the HPGR - ball mill circuit and HPGR - stirred mill circuit achieved a substantial reduction in energy, with considerable cost advantage over the existing SAB/AGBC/SABC circuits.

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The throughput capability of a high pressure grinding roll (HPGR), a critical process parameter, has been found to heavily depend on the sample type being processed. Existing HPGR test methods require the use of pilot machines and large sample quantities to assess the throughput characteristics of a certain ore type. Addressing the need for a laboratory scale HPGR test, a laboratory procedure was proposed to assess the throughput capability of mineral samples. Existing procedures were adopted from the fields of terramechanics and soil mechanics, and used as a basis for predictive HPGR throughput models. The applicability of the proposed tests was assessed through the comparison of predicted throughput with observed values from pilot HPGR testing. Results showed that outcomes of the proposed laboratory scale tests were statistically significant when used for the prediction of HPGR throughput. Primarily, the frictional properties of feed samples, as characterized by a direct shear box test, were found to be of particular significance. An approach to modelling the pressure profile which occurs on the HPGR roller surface was also proposed for potential use in a force-based model. Based on the results, an approach to HPGR testing requiring a reduced amount of sample was presented. Further work on characterizing the frictional properties of mineral samples was recommended. Analysis of HPGR outcomes indicated that strong relationships exist between power, throughput and roll gap, hence holistic approaches to HPGR modelling may be most appropriate for future predictive models.

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Automatic sensor-based sorting is a clean preconcentration technique that can be used to separate valuable ore rock from waste rock based on the difference of the detected physical properties. This research evaluated the amenabilities of a Mississippi Valley type lead-zinc ore sample from Pend Oreille Mine to X-ray Fluorescence Sorting, X-ray Transmission Sorting, Optical Sorting and Microwave-Infrared Sorting using laboratory-scale bench-top sensing systems. A methodology for laboratory-scale quick evaluation of the amenability of an ore sample to automatic sensor-based sorting using bench-top sensor systems was generated as reference for future study.The preliminary testwork results showed that the two X-ray methods exhibited the best sorting results. About 37.7%~52.8% of the feed mass could be rejected as waste while above 95% of the lead and zinc was recovered in the product. The sorting feed (-37.5+26.5 mm) could be upgraded by a factor of 1.5~2. The optical sorting method seemed not as effective as the X-ray methods. Only 18.8% of the sorting test feed (-37.5+26.5 mm) was rejected to maintain above 95% metal recovery in the product. The test feed was upgraded by a factor of 1.2. Microwave-Infrared sorting results demonstrated that carbonate gangue mineral does not heat when exposed to microwave heating, while lead-zinc bearing sulfide does. Factors such as particle size, heating time and quantity of particles being heated at a time would influence microwave heating of rocks. Sorting feed of -19+13.2 mm presented the best segregation results after 10s of microwave heating. Above 95% of lead and zinc was recovered in a mass yield of 70% to the product. The test feed was upgraded by a factor of 1.4.The preconcentrate of X-ray Fluorescence sorting had a bond work index 12% smaller than that of the feed ore. The overall metal (lead and zinc) recoveries and grades in the flotation products were also improved after XRF sorting. The costs of both the grinding and the flotation reagent could also be reduced due to the reduction of the feed mass by rejecting the dolomitic gangue minerals up to 50%.

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The mining industry will be faced with new challenges as the need to develop lower grade ore deposits expands to meet the rising demand for raw resources. Low-grade deposits require a substantially increased tonnage to achieve adequate metal production and have caused the consumption of energy in mining practices such as comminution to rise dramatically. If improvements could be made in the processes employed for metal extraction, the mining industry could remain sustainable for future generations. This research focused on the development of a novel comminution circuit design to addresses these issues. The circuit design incorporated two, known energy efficient technologies, the High Pressure Grinding Roll (HPGR) and the horizontal high-speed stirred mill, and examined the technical feasibility of a circuit operating without the need for a tumbling mill.The main objectives of this research were to setup pilot-scale research equipment and develop the design criteria necessary to operate an HPGR / stirred mill circuit. Testing consisted of using a copper-nickel sulphide ore from Teck Limited’s Mesaba deposit to evaluate a circuit comprised of two stages of HPGR comminution followed by stirred mill grinding. To evaluate the potential energy benefits of this novel circuit arrangement, energy consumption related to comminution was calculated for the circuit using power draw readings off the main motor and the throughput recorded during testing. To provide a basis for comparison, the energy requirements for two conventional circuits, a cone crusher / ball mill and an HPGR / ball mill, were determined through HPGR pilot-scale testing, Bond grindability testing and JK SimMet® flowsheet simulation.Results from this research showed that operating the first-stage HPGR in open circuit and the second stage in closed circuit with a 710µm screen, resulted in a circuit energy requirement of 14.85kWh/t, a reduction of 9.2 and 16.7% over the HPGR / ball mill and cone crusher / ball mill circuits, respectively. To assist in future HPGR / stirred mill studies, a refined testing procedure was developed with a reduced sample commitment and the ability to perform an energy comparison with a Semi-Autogenous Grinding (SAG) mill / ball mill circuit.

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The weathering behaviour of waste rock is being evaluated using field cell experiments at the Antamina Mine. The results presented here are a component of a larger study that is being conducted in Antamina, whose objective is to understand the geochemical and hydrological behaviour exhibited by different waste rock types, and their potential operational and post-closure impacts on the environment, in order to identify and implement prevention/mitigation measures. The waste rock is currently classified into three classes based on metal (zinc, arsenic) and sulfide contents: reactive (A), slightly reactive (B), and non-reactive (C). This thesis presents the analysis only of Class B marble and hornfels material. Particle size was measured through the standard sieving method and Elutriation techniques, and surface area through geometrical estimation and the BET methods. The data gathered was correlated with chemical assay results and complemented with the mineralogical and mineral availability for leaching data obtained using a Mineral Liberation Analyzer. Minerals containing copper, lead, and zinc, and all sulfide minerals were examined. Seven field kinetic cells were installed with samples having particles of less than 10 cm in diameter. Metal leaching, elemental production rates and release rate trends from two years of data are presented. The relationship between mineral availability and field cells drainage data was investigated. A refined waste rock classification system for Class B was recommended including the incorporation of lithology, mineralogy, mineral availability for leaching, and sulfur-sulfide content.The diopside marble samples were found to be coarser than the black marble and gray hornfels samples. Large surface were reported in the black marble, this was because a relatively higher proportion of clay minerals were found in this sample.Acid-base accounting testing reported that all samples were non-acid generating. However, Cu, Pb, Zn, and Sb were reported in higher concentrations in the leachate from the field cells. Solid phase concentrations of these elements were found to increase as the size fractions decreased, but in two diopside samples, Cu, Pb and Zn minerals were available for leaching in high proportion from the coarse particles. The main sources of these elements were chalcopyrite, galena, and sphalerite.

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