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By H. A. MEGRAW

THE meeting of the A. I. M. E. at Wilkes-Barre, Pa., Sept. 12 to 15, inclusive, celebrated the fiftieth anniversary of the Institute. It was at Wilkes-Barre, in 1871, that the foundation was laid for the great institution that now includes in its roster the greatest names. in mining engineering in every civilized country of the world. The founders of the Institute, with rare prescience, established a common ground upon which all mining engineers, whatever particular branch they might consider most pertinent, could stand securely, assured of a deep-seated interest from their brethren similarly minded in other localities. So wise and clear was the vision of the founders that every engineer connected with mining has found it beneficial, not to say indispensable, to maintain his connection with the Institute and to increase his technical enthusiasm through the medium of the valuable technical publications. The little coterie of 1871 has grown to a strong body of more than 10,000 members in 1921, reflecting the glory of the founders in the record of the accomplishments written on the pages of the fifty years of the

Jan 1, 1921

By A. Navarra

Peirce-Smith converting (PSC) is applied for roughly 50% of primary nickel and 70% of primary copper production. PSC cycles produce batches of ironfree sulfide matte (or blister copper, in the case of copper smelters), that are subject to further processing. However, the number of cycles that can be performed simultaneously is limited by the offgas handling system. Moreover, PSC suffers from variation in the yield and duration of the cycles. This variation is managed by conventional smelter designs, in which the upstream smelting capacity exceeds the nominal converting capacity; PSC is thus a major bottleneck in conventional nickel and copper smelters. Stabilization and standardization of PSC operations can therefore increase smelter throughput. The current paper presents a discrete event simulation (DES) framework to assist in smelter debottlenecking. It features random number generation to represent cycle variability, and time-adaptive finite differences to represent thermochemical complexity. Preliminary computations are presented.

By George S. Dulikravich

An advanced semi-stochastic algorithm for constrained multi-objective optimization has been adapted and combined with experimental testing and verification to determine optimum concentrations of alloying elements in heat-resistant and corrosion-resistant H-Series austenitic stainless steel alloys. The objective was to simultaneously maximize a number of alloy's mechanical properties. This research will result in a rigorous tool for the design of high-strength H-Series steels and other types of alloys unattainable by any means existing at the present time. Such a material-by-design tool will also be able to reduce or minimize the need for the addition of expensive elements such as Cr, Ni, Co, Nb, Ti, V, etc. and still obtain the optimum properties of an alloy.

Jan 1, 2003

By George S. Dulikravich

An advanced semi-stochastic algorithm for constrained multi-objective optimization has been adapted and combined with experimental testing and verification to determine optimum concentrations of aJ10ying elements in heat-resistant and corrosion-resistant H-Series austenitic stainless steel alloys. The objective was to simultaneously maximize a number of alloy's mechanical properties. This research will result in a rigorous tool for the design of high-strength H-Series steels and other types of alloys unattainable by any means existing at the present time. Such a material-by-design tool will also be able to reduce or minimize the need for the addition of expensive elements such as Cr, Ni, Co, Nb, Ti, V, etc. and still obtain the optimum properties of an aJ1oy.

Jan 1, 2003

By Peter I. Brooker

The semi-variogram, the basic tool of geostatistical estimation procedures, must itself be estimated from the available data. From a numerically simulated two dimensional deposit, with known variability expressed through its semi-variogram, the standard arithmetic mean estimator is used to calculate experimental semi-variograms. These are determined on a series of data sets obtained from the deposit with various sampling grids which cover different areas of the deposit and which have a wide range of available data. The orders of discrepancies between estimated and theoretical semi-variograms are determined in this idealized situation; and this provides a basis against which to assess experimental semi- variograms made on field data.

Jan 1, 1982

By N. J. Themelis, A. W. Last

Autogenous grinding, broadly defined as the self-comminution of ore in a cylindrical tumbling mill without using auxiliary grinding media, was first applied in the early 1930s in the so-called Hadsel mills (Hardinge, 1955) as seen in [Fig. 1], mainly used in gold mines on the US West Coast. A number of these mills were built in sizes of 6.1 to 7.3 m (20 to 24 ft) in diameter and 1.5 to 1.8 m (5 to 6 ft) in length but were later abandoned because of operating and maintenance problems. Further development of autogenous grinding led to the Hardinge wet grinding mill, the Aerofall dry grinding mill, and others. A tabulation of all known autogenous and semiautogenous installations around the world was sent recently to the authors by G. J. Kushner of Koppers Metal Processing Division. In the size range of 7.3 to 9.8 m (24 to 32 ft) in diameter, it lists a total of thirty mills used in the processing of copper ores. An additional 120 units are listed in the same size range for the processing of iron ores and other minerals. The largest mills in existence are 11.1-m-diam X 4.6-m-long (36-ft-diam X 15-ft-long) mills in Minnesota, powered by 8950 kW (12,000 hp) motors and used in taconite beneficiation. It is indicative of the phenomenal growth of this technology that none of the above 150 mills was in operation prior to 1964. Grinding rates in autogenous mills are very sensitive to variations in ore breakage characteristics and even with fairly constant ore type can exhibit large fluctuations in throughput. Autogenous grinding also depends on availability of a fraction of the ore to be ground in the form of "competent" rock which can withstand to a certain degree the tumbling and impact action within the mill. If the ore is uniformly "soft", it will soon be crushed into small size particles and further grinding, which depends on the existence of large size rocks in the mill, becomes impossible. This apparently is the case with most copper ores, as discussed by Bachman, Last and Nabbs (1970) who described pilot testing of a large number of ore samples from Kennecott 's Chino Mines. Under circumstances where autogenous grinding is impractical, it is possible to realize most of its benefits by utilizing large grinding balls in place of the "competent" rock and practice what has become known in the mining industry as semiautogenous grinding. In semiautogenous grinding (SAG), a grate discharge tumbling mill is fed the product of a primary crusher or run-of-mine rock. Forged steel or alloy grinding balls, in proportions ranging from 3.10% of the total volume in the mill, are used to complement the self-grinding ability of the ore. Semiautogenous circuits can be either designed for single-stage closed-circuit grinding which produces a final product for recovery processes, or for two-stage operation in which the SAG mill product is fed to a second stage of grinding in a conventional ball mill.

Jan 1, 1981

By F. N. Rhines

I. An Outline of the Theory of the Sintering of Pure Metal Powders SINTERING may be defined as the process by which powders bond themselves into coherent bodies, usually, although not necessarily, under the influence of pressure and elevated temperature. For the sake of clarity and simplicity, the present survey will exclude from consideration the sintering of mixed or alloyed powders, with attendant complications, but at the risk of overlooking information of general applicability. Sintering in the presence of a liquid phase is thus automatically eliminated. The sintering of alloys involves much additional subject matter and deserves separate consideration. Since the literature of the subject is extensive and widely scattered, it will not be feasible to consider the contributions individually. Instead, the subject matter will be classified according to experimental observations and theory, and will be presented in summary form. It should be noted that the appended list of references does not constitute a complete bibliography; it includes only those works quoted below. More extensive bibliographies are included in several of the references; see particularly references 7, q, 28, 34, 38, 50, 52, 54 a "Bibliography on Powder Metallurgy" published by the Library of Congress and a pamphlet published by the Metals Disintegrating Co. entitled "The Field of Powder Metallurgy and Bibliography." II. Summary of Experimental Observations The following classified list is composed of general statements of established fact derived from the experimental results reported in the published literature. A few contested observations are included, because of their potential importance; these are labeled as such. Any satisfactory and complete theory must be capable of explaining all of the uncontested facts. Obviously, some important facts may be missing from this list and these may hold the key to the correct explanation of the sintering process, but the possible lack of such material should not deter attempts to understand the subject on the basis of what is available here. A. The Initial Bond at Room Temperature a. To a limited extent uncompressed powders and massive metals adhere at room temperature.28 Clean tin powder forms a weak "cake" on standing at room temperature, the strength increasing with time. Clean gold surfaces adhere on light contact,"' as do those of many other substances, including nickel." b. Upon compression the strength of the bond is increased progressively.28 There is a limit of pressure

Jan 1, 1946

By Emily Dieckman, Claire Kincaid

"When most people think “miner,” they picture an older white man in a dusty shirt and suspenders. He’s holding a gas lamp and a pickaxe, peering at the walls of a dimly lit cavern. This image, while steeped in heritage, is no longer representative of what mining is: a global, increasingly diverse industry.It’s an industry made up of individuals like Zambian-born Chushi Mwewa, PE, president of Southlands Engineering, LLC in the United States and managing director of Southlands Engineering Limited in Zambia; Navajo tribe member Peter Denetclaw, manager of environmental programs and Navajo relations at Freeport-McMoRan; and Chinese and Jewish Alyssa Hom, a project engineer at McCarthy Building Companies.According to the Austrian Federal Ministry of Science, Research and Economics, 168 out of the world’s 195 recognized countries have some mining or mineral resources activity, and the mining industry directly employs more than 25 million people across the globe.However, according to McKinsey & Company’s 2017 “Women in the Workplace” study, white males hold 67 percent of C-Suite positions and 70 percent of senior vice president positions in the corporate world, and mining is no different. This uniformity among leadership has been tied to lower levels of employee engagement, innovation and business growth. The bottom line is this: Diversity is good for business. The question industry leaders must now ask themselves is not “Will we promote diversity?” but “How will we promote diversity efficiently and permanently?”More than 80 industry professionals, consultants and students gathered to discuss this question and share stories at the “Developing Diversity in Mining” workshop organized by the University of Arizona’s Lowell Institute for Mineral Resources (IMR), held during the 2017 SME Arizona Conference in December 2017.Brad Ross, co-director of the IMR and one of the facilitators of the workshop, said he felt diversity was important to discuss because he has witnessed its benefits throughout his career in the mining industry.“By creating a team of people with different experiences and perspectives, a company is better equipped to see the big picture and to creatively tackle problems,” he said. Speakers from industry and academia,including Mwewa, Denetclaw and Hom discussed the challenges surrounding achieving diversity and inclusion as well as the roles and responsibilities of different stakeholders."

Jan 2, 2018

By D Connelly

As the resources sector becomes tougher with rising costs and cyclical metal prices, mining companies need to continue to reduce their costs and do more with less. Many new resource projects fail to come in under or on budget based on Feasibility Studies. Particularly, capital expenditure (CAPEX) proves difficult to achieve for resource projects. A number of resource projects have failed because of aggressive plant CAPEX cost cutting resulting in projects with no surge capacity and are unable to achieve design throughput. In addition, the plants are not operable because of the omissions. In recent times many businesses have also experienced the "costs" of simply implementing aggressive operating "cost cutting” measures as a strategy for solving business performance problems. This paper looks at technology driven, employment related, luxury cuts, department cuts and restructuring cuts. In the past companies used an incremental approach based on the use of past budget information as an integral part of the budget construction process going forward. The use of performance reports and Management Information Systems (MIS) is examined along with the role of continuous improvement in achieving sensible cost cutting.

Aug 8, 2011

Traditionally, the development of a mineral resource project goes through a fairly set pattern of decisions from what commodities to search for; where to look; how to locate; what are the reserves; how can they be exploited with optimum returns for all stakeholders; where are the markets and what will be the price received; what financing arrangments? However, due to the unique nature of most mineral resource properties, the relative significance of individual parameters on the ultimate development decision will vary from project to project. Sensitivity analysis in its formal sense is most frequently related to the economic analysis of a project particularly in conjunction with the ultimate development decision making process, and acknowledges the uncertainty of the actual values with their impact on the corporate decision making yardsticks. In many cases, this analysis merely adds more values to confuse the decision makers who may well opt for some subjective rationale to overcome the numeric confusion. However, sensitivity analysis should be used more frequently to exploit the development dollar to its maximum, THROUGHOUT the phases leading to the development decision. It is essential to identify the critical inputs to the various decision tiers in a project as early as possible and direct the funds to ensure that these parameters are determined as accurately as possible. Examples are used to illustrate the need for an even-handed quantification of the parameters which affect the outcome of decisions en route to the final one while minimising the risk in making an optimum assessment in relation to development funds Available.

Jan 1, 1983

By Joseph M. Chelini

The report shows the sensitivity that nine different cash-flow factors have on the discounted rate of return calculated from feasibiliity- studies on potenital open-pit orebodies of silver, copper, and uranium. Cash-flow factors of "grade", "market value", and "recovery" are. the most sensitive. This verifies the need of reliable estimates for these factors. The cost of evaluation of "preproduction cost" is the least sensitive. This gives credence to the fact that more consideration should be given to compiling sufficient data, as the largest financial losses are not in the cost of evaluation but rather in the abandonment of an unprofitable mining operation after a commitment of capital is made on the basis of an incomplete evaluation. Sensitivity analysis of cash-flow factors enhances evaluation programs by disciplining the collection of data and allowing more realistic distribution of evaluation monies.

Jan 1, 1971

By M. D. Griffith

"Ventilation models are a vital tool to ensure ventilation designs can provide airflow to all work areas in a mine. Airway resistance and variations in natural ventilation pressures will affect simulated airflow and heat distribution through a mine. Validating ventilation model resistances and pressures to the exact underground conditions can be difficult and the variances can contribute to significantly different simulation results depending on the structure of the ventilation design. The study will use sensitivity analysis to explore examples of variability of simulated airflow due to small resistance, heat and natural ventilation changes and thereby help the user identify both trustworthy and potentially unreliable parts of a mine ventilation model. INTRODUCTION Mine ventilation network modeling is a vital tool for ventilation professionals and has become increasingly relied upon during the design and operation phase of mine ventilation systems. However, they provide only an approximation of reality, and caution must always be exercised when drawing conclusions or making decisions based on simulated data. Ventilation modelling should be performed by persons with a sound fundamental knowledge of ventilation and ideally should be validated with field data, but in large mines, or mines which are yet to be mined, accurate input of the simulation variables can be difficult, and errors and inaccuracies may be difficult or impossible to avoid. This study discusses and investigates the sensitivity of the mine ventilation simulation results to input errors. In addition, there are limitations to what steady-state airflow and heat simulations can model, regardless of the accuracy of the model inputs. In some situations, steady-state solvers cannot capture the dynamic changing behavior of a ventilation system. This study will also describe and apply techniques to analyze the natural variability of mine conditions on ventilation models. The consequences of poor accuracy in some parts of a mine model may impact on the health and safety criteria of ventilation designs. For example, if an airway is required to flow in a particular direction and quantity, then despite a ventilation model showing correctly designed conditions, small errors in input values may result in incorrect prediction of the direction or quantity of airflow. This may create unexpected buildup of heat or gases during operational activities, causing safety issues or operational delays. The ability to know which parts of a mine ventilation model have increased potential for poor simulation results will allow engineers to consider the ventilation design and make changes if required to better guarantee the required design flows."

Jan 1, 2019

By G. Danko

Ventilation and refrigeration for mine climate modification, contributes significantly to the operating costs of a deep hot mine. Mine climate simulation programs can be used to minimize the impact of these costs. There are several computer codes available including CLIMSIM?, to assist in this work. Whichever simulation program is used, it is the mine ventilation engineer who must supply the input data. This paper raises and answers the following question, namely: what accuracy is required of the basic input parameters, in order for a certain precision to be obtained in the predicted air temperatures? In the first part of the paper a new approach is described to estimate the dry and wet bulb temperature of the airflow, either in a dry or wet roadway. The calculation procedure allows an arbitrary temperature change with time, using Duhamel's superposition solution. Matrix-vector representation is applied to simplify the computational structure. In the second part of the paper the sensitivities of the dry and wet bulb air temperatures are analyzed to the changes of the rock thermo-physical properties, the heat transfer coefficient and the wetness factor.

Jan 1, 1988

By N McIntyre, J Smart, J Ossa-Moreno, D Rivera

Hydro-economics is a field of research that analyses water resources from a multi-disciplinary approach (Harou et al., 2009). These models generally include one component that describes the water resources of the catchment being analysed (e.g. the physical behaviour of water), an economic component that describes users’ water demand function (changes of willingness to pay relative to availability) and a coupling methodology. These models go beyond calculating cash flows for water investments and analyse the economic behaviour of users when facing water shortages or surplus. In other words, water demand curves are defined for each water user (e.g. urban, agriculture, mining, environmental and hydropower), and they are used to retrofit the water resources component. As a result, the model approximates the catchment scale response to droughts and wet periods, including the effects of water markets, restrictions, recycling, water sharing and any cooperative efforts by users to adjust to changing climate conditions.These models are usually focused on agriculture and urban users, the main water consumers in most catchments, but they have sometimes included environmental, industrial and hydropower users (Bekchanov, Sood, & Jeuland, 2015). Nevertheless, although a relevant user of water in several catchments, the mining industry has been rarely included. This paper is part of an ongoing project that addresses this gap by developing a hydro-economic model in the upper section of the Aconcagua River in Chile. The aim of the paper is to analyse the sensitivity of the outputs of the model to changes in input data, both hydrological and economic, and to develop insight on usefulness of such models for reducing water conflicts in mining regions.CITATION:Ossa-Moreno, J, McIntyre, N, Smart, J and Rivera, D, 2018. Sensitivity of a hydro-economic model in a mining region to changes in hydrological and economic inputs, in Proceedings Life-of-Mine 2018, pp 52–55 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 25, 2018

INTRODUCTION In the preceding chapters we have discussed the various elements of mineral economic analysis, their interrelationships, and the most accepted and advanced techniques by which these elements are manipulated to provide the decision maker quantitative measurements for judging alternate investment opportunities. Regardless of how carefully the economic evaluation is made, and how comprehensive the study of economic parameters has been, uncertainty still remains a significant factor in the outcome of the analysis. The investor or money manager is acutely aware of the uncertainty factor. Many of the economic parameters are functions of economic forecasts and value estimates that can- not be known with any degree of certainty. The postulated DCF-ROR is based upon certain estimates representing "best guess" values, and a single point parameter DCF-ROR analysis represents a combination of "best guesses." The wise decision maker looks at such an analysis and asks the "what if" questions. What if the production cost is 10% higher than the estimate? What if there is an overrun in construction costs? What if the mineral price falls lower than expected? What will be the effect of a higher royalty rate? Many more such questions may arise in trying to assess the total risk involved in funding a mineral project. Prior to the advent of the computer it was difficult to answer all such anticipated questions because of the many laborious calculations involved. Now, with the aid of the computer, most of these questions can be answered by the analyst at the same time the original computations are made by using the process of sensitivity analysis. Sensitivity analysis shows the effect of critical parameter changes upon the DCF-ROR or other profitability measure. When probability of occurrence can be associated with the various parameter value levels, sensitivity analysis becomes probabilistic analysis, and the risk factor can be quantitized in terms of total probability. SENSITIVITY ANALYSIS The determination of the sensitivity of the profitability index (usually the DCF-ROR) to changes in the various economic parameters, taking them one at a time, is called sensitivity analysis. The analysis may be performed for any number of parameters involved in the DCF-ROR computation. Generally, in mineral evaluations the most sensitive and most tested parameters are: the metal or mineral price, the operating cost, the annual production grade, and the initial capital invest-

Jan 1, 1980

By Jacek Kolacz

A new sensor based sorting system has been developed, based on complex image analysis, where an image texture and a shape pattern is considered for identifying particles for separation. The sorting system employs different images generated by visual light and X-ray to provide maximal information about processed particles. Application of X-ray makes it possible to analyse the internal structure of the particles, which provides a 2D image with complicated texture, however, which contains valuable information. The advanced system for the texture and the pattern recognition is applied to analyse these images simultaneously, to provide the required identification of the particles for efficient separation. The mathematical models applied during identification and separation, are assisted by high speed calculations being specially optimised for this kind of process. This allows sorting with high capacity and high accuracy, which is critical for practical applications in mineral processing. The paper describes a number of tests during sorting of iron ore and coal with high separation efficiency.

Jan 1, 2014

By P Esteves, J L. Bechir, R Galery, C Senna, V Souto

The current moment experienced by the mineral industry is marked by a series of economic, social and environmental challenges. Among the main challenges, it is important to highlight the decreasing in ore grades with the gradual depletion of the existing deposits, the high volatility in international commodity prices and the operational inefficiencies in the mine, beneficiation, and metallurgical plants. In this context, mining companies are continuously looking for alternatives that minimize production costs and maximize overall production. In addition, recent tragedies involving tailings dam collapses in Brazil, reinforced the need for a more responsible, sustainable, and conscious mining, such as aiming the preservation and rehabilitation of the land environment. In this scenario, the Sensor-Based Sorting (SBS) technology is currently getting more space into the mining market. This separation technology aims the removal of gangue material in coarse particle size fractions, prior to comminution and concentration stages. As a consequence, the technology allows a smaller consumption of energy, water, chemical reagents and other inputs. Moreover, the sensor-based sorting is a dry processing technology and favors the reduction of fine material to be sent to the tailings. The aim of this paper is to provide information regarding the technical and economical evaluation of SBS technology applicability to a zinc silicate mining in Brazil. The project evaluation was performed in two stages: laboratory test work and the execution of a pilot plant. The execution of a pilot plant allowed the technology optimization, quantification of downstream process effects, such as a proper economic evaluation about the technology benefits. Keywords: Sensor-Based Sorting; Particle Sorting; Ore Sorting; Preconcentration; capital expenditure (CAPEX); operating expenditure (OPEX); zinc; comminution; dry processing.

Nov 10, 2020

By M W. N Buxton, M S. Shishvan, J Benndorf

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 in terms of produced ore grades and quantity and extraction process efficiency often deviate from expectations. Reconciliation exercises to adjust mineral reserve models and planning assumptions are performed with timely lags of weeks, months or even years.With the development of modern information and communication technology over the last decade, a flood of data about different aspects of the production process is available in a real-time manner. For example, sensor technology enables online characterisation of geochemical, mineralogical and physical material characteristics on conveyor belts or at working faces. The ability to utilise this additional information and feed it back into reserve block models and planning assumptions opens up new opportunities to continuously control the decisions made in production planning to increase resource recovery and process efficiency. This leads to a change in paradigm from a discontinuous method to near real-time reserve reconciliation and model updating, which calls for suitable modelling and optimisation methodologies to quantify prior knowledge in the reserve model, process and integrate information from different sensor sources, back propagate the gain in information into reserve models and efficiently optimise operational decisions in real-time.This paper introduces the concept of an integrated closed-loop framework for real-time reserve management, incorporating sensor-based material characterisation, geostatistical modelling under uncertainty, modern data assimilation methods for sequential model updating and mining system simulation and optimisation. The effectiveness of the framework and the value added will be demonstrated in an illustrative case study.CITATION:Benndorf, J, Buxton, M W N and Shishvan, M S, 2014. Sensor-based real-time resource model reconciliation for improved mine production control – a conceptual framework, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 223–234 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By M. R. Robben

Carbonates have gained significant economic importance for the human kind. On one hand over a hundred uses are listed for carbonates. On the other hand, carbonates host base metal deposits. Although the carbonates play a significant part in the development of those deposits, in the mineral processing they consume acid and cause selectivity problems during flotation and leaching. Carbonates also accompany other industrial minerals as waste rock. For all those cases it necessary to find a technique to separate carbonate as early as possible in the processing chain. In this paper, the applicability of near-infrared spectroscopy (NIRS) sorting for the separation of carbonates is discussed. NIRS sorting is a sensor-based sorting technique, in which particles are singularly detected by a sensor and then rejected by an amplified mechanical, hydraulic or pneumatic process. This technique can for example be implemented in the process as a pre-concentration step for coarse particle sizes up to 300 mm. NIRS sorting discriminates among materials based on the difference that exist between their spectral properties in the near-infrared (NIR). Vibrations of molecular bonds in carbonates cause characteristic spectral properties in the NIR, which makes carbonates detectable, possible to identify, distinguish and separate from other rock materials. The spectral properties can also be used to distinguish between different carbonate minerals and mixtures. If the spectral variations are large enough for detection, sorting based on NIRS is possible. Feasibility studies on sensor-based separation of carbonates in the processing of talc, borate, fluorite, marble, zinc-oxides, copper sulphide and iron ore as well as the discrimination of calcite and dolomite mixtures are conducted and indicate the high potential of NIRS sorting in the minerals industry. Keywords: carbonate separation, sensor-based sorting, near infrared spectroscopy, NIRS sorting

Sep 1, 2012

By C. Bergmann, V. Ross

The concept of underground ore processing, in which valuable ore and waste are separated at a coarse particle size to improve the economics of operations and minimise the environmental impact, seems attractive from a sustainability perspective. Perceived benefits of such an operation include energy and cost savings due to a reduced hoisting load, a reduced footprint of surface operations, and using material for backfill that has not been contaminated by process chemicals. Progress in the South African mining industry in this area has however been below expectation, and opportunities for underground processing in deep, narrow reef operations were therefore explored by an Excel-based simulation with sensor-based sorting (SBS) as concentration technology. Various PGM mining scenarios incorporating factors such as the mining rate, depth of operation, and effects of dilution and particle size on the metallurgical efficiency, were compared. Whilst these initial results can be regarded as indicative only, they have shown that the economics of such an operation are driven by selective mining at significantly higher rates than achievable with conventional methods. Also, the cost of preparing, conveying and placing rock backfill will need to be lower than that of hoisting waste and depositing it on a surface dump. Another aspect to be addressed is whether ore sorting machines would be able to operate under harsh conditions underground and what provision would need to be made to ensure their efficient operation. Further investigations should focus on refining costs, incorporating environmental considerations in the modelling of economics and sustainability, and compare greenfields with brownfield scenarios. Keywords: Ore sorting, hoisting, backfill, mining rate, economics simulation

Jan 1, 2020