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By C. C. Birch

Due to grade estimation uncertainty, two statistical errors can occur. The Type I error is where material is classified as ore and mined, despite the true value being below the break-even grade. This material is dilution. The Type II error is where the material is estimated to be below the cut-off grade and is classified as waste, although the true grade is actually above the break-even grade. This material is not mined and is lost. The uncertainty was assumed to follow a normal distribution in a previous study. For this study, estimated block values are compared to those determined after mining (the best estimate of the true grade). This actual data from four mines shows that the uncertainty follows a Laplace. There is no single solution regarding adjusting the cut-off grade away from the break-even grade, considering estimation uncertainty, that could be applied to all gold mines. However, adjusting the cut-off grade downwards (up to 22% for one mine) is noted when optimizing the profit considering grade uncertainties. This type of adjustment could open up significant mining areas and extend the life of the mine.

Jul 2, 2022

By M. A. Mahboob, T. Celik, B. Genc

Mineral Resources estimation plays a crucial role in the profitability of the future of mining operations. The conventional geostatistical methods used for grade estimation require expertise, understanding and knowledge of the spatial statistics, resource modelling, geology, mining engineering as well as clean validated data to build accurate block models. However, the geostatistical models are sensitive to changes in data and would have to be rebuilt on newly acquired data with different characteristics, which has proved to be a time-consuming process. Machine learning methods have in recent years been proposed as an alternative to the geostatistical methods to alleviate the problems these might suffer from in Mineral Resource estimation. In this paper, a systematic literature review of machine learning methods used in Mineral Resource estimation is presented. This has been conducted on such studies published during the period 1990 to 2019. The types, performances, and capabilities, of several machine learning methods have been evaluated and compared against each other, and against the conventional geostatistical methods. The results, based on 31 research studies, show that the machine learningbased methods have outperformed the conventional grade estimation modelling methods. The review also shows there is active research on applying machine learning to grade estimation from exploration through to exploitation. Further improvements can be expected if advanced machine learning techniques are to be used.

Nov 30, 2022

By M. S. Shishvan, J. R. van Duijvenbode

The results of dig limit delineation in open pit mining are never truly optimized due to gaps in the underlying data, such as insufficient sampling. Aside from the data uncertainty, there is also an influence on the final dig limit by either humans or by the heuristic character of an optimization method like simulated annealing. Several dig limit optimizers have been published, which can replace the manual dig-limits designing process. However, these dig limit designs are generally not adapted to account for this heuristic character. In this paper we present a stochastic analysis tool that can be used with the results of heuristic dig-limit optimization to increase confidence in the obtained results. First, an enhanced simulated annealing algorithm for dig limit optimization is presented. Then, this algorithm is tested on ten different blasts at the Marigold mine, Nevada, USA, as a case study. Finally, the results are analysed with a destination-based ensemble probability map and an analysis conducted of the final solution data distribution. The generated dig-limit designs of the algorithm include high revenue areas that are excluded in comparable manual designs and show improved objective and revenue values. The analysis tool provides block destination probabilities and box plots with the distribution of opportunity value for the dig limit. Furthermore, with the analysis tool, it is possible to make well-informed design decisions in areas of uncertainty.

Dec 13, 2022

By G. Asbjörnsson, E. Hulthén, P. Papadopoulou, C. M. Evertsson

Crushing plant managers need to assess, manage, and communicate the environmental impact induced by their crushing plant operations as a step towards the sustainable development of the company. However, performing reliable environmental impact calculations of crushing plants can be challenging when the availability of operational and emission data is low, and when the company’s environmental expertise is not adapted and connected to plant operations (or does not currently exist). To address these challenges, this paper proposes a practical approach where the lifecycle assessment methodology (LCA) is combined with process simulations in a web-based tool. To describe what functionality such a tool should have to be incorporated into a company’s workflow, the system that surrounds a crushing plant is analysed. Further, a case study with a three-stage crushing plant is introduced to showcase how the simulated power draw results produced with the beta version of the tool can be compared to measured sensor data from the crushing plant for one operational day. The results indicate that the simulation tool can provide an adequate estimation of the specific energy for the different material fractions and give an overview of the environmental impact of the process caused by electricity and explosives consumption. Plant managers and operators can use this tool to calculate the environmental impacts of their plant and simulate how different operational strategies influence them. Keywords: LCA, environmental impact, coarse comminution, crushing plant

Jan 1, 2020

By S. Chatterjee, F. Suparno, A. Paithankar

Estimating reserves and quantifying resources stand as pivotal and intricate endeavours within the realm of coal mining operations. Intricate geological formations compound the challenges in resource estimation, thereby complicating reserve calculations. The uncertainties tied to geological attributes of coal, encompassing parameters like tonnage and coal quality, wield significant sway over resource and reserve computations within coal mines. This research delves into the domain of geological uncertainties, with a specific focus on calorific value, aiming to numerically characterise resources and reserves within an open-pit coal mine situated in Indonesia. To quantify resources, the coal seam geometry underwent simulation via a multipoint geostatistical technique known as single normal equation simulation. A geologically established coal seam served as the training image for generating 20 equiprobable coal models. To simulate CV, 50 realisations were generated for each simulated coal seam, utilising sequential Gaussian simulation. Deviations of the simulated coal seams ranged from -0.07% to 5.48% in comparison to the training image. The CV simulation yielded an average value of 5,920.29 kcal/kg, accompanied by a standard deviation of 586.54 kcal/kg. However, the average CV spanned from 5,305.26 kcal/kg to 6,526.55 kcal/kg across diverse simulations. For reserve calculation within the context of geological uncertainties, an algorithm rooted in maximum flow graph theory was employed to construct the ultimate pit for the coal mine. Within this final pit, the average stripping ratio was 1.62, coupled with a CV value of 6,019.66 kcal/kg. When juxtaposed with the deterministic model, the findings underscore that the stochastic ultimate pit delineates a more expansive excavation, accompanied by a heightened undiscounted cash flow.

Oct 2, 2025

By Stuart Marsland

"Reference materials have always been important for validating and controlling analytical methods', They have recently become even more important as quality requirements have become more stringent and customer demands for properly verified and controlled results increase. Clients, especially from the resource exploration industry demand critical validation of all results reported. Mintek has been producing geological and semi processed ore references since the early 1970's and recently due to increase in demand other manufactures have entered the South African Market.This paper describes Analytical challenges from the customer's perspective. The customer being the metallurgist, mine geologist, environmental scientist and geologists from resource companies. Reference Materials and their appropriate use and good understanding of them can aid greatly in building confidence in the results, choosing the right Laboratory for a project, deciding which set of results arc correct and providing evidence to the customer's clients that the results obtained are the very best possible.Throughout the world there are hundreds of reference materials produced by over 80 organisations and these are mainly ores, rocks, semi processed ores, metals, and many more. Mintek is one of the top 10 producers with over 75 products. Many of these producers including Mintek and their respective standards organisations belong to the ISO REMCO committee and their respective work groups. This committee's main task is to draw up guide lines for the use, manufacturing and certifying reference materials. In South Africa a mirror committee has recently had its inaugural meeting the function is to give clear mandate to the South African representative on the main ISO REMCO committee, the South African delegate bas an opportunity to influence the contents of the guides.Tile SARM program has since the year 2000 increased its sale three fold, the question is why? There is more accountability needed in our world. That means Analytical results have to be the very best possible and risks associated to them must be well quantified. Consider that the risk of wrong results of wrong decisions made from a result is trivial to laboratory, in comparison to the laboratories customers. The consequence to a laboratory could be a loss of income or some one may lose their job. To the customer he may dig up 1000 of ton's of rock with nothing in it or worse still don't mine it when the grade is high enough. This is seriol1s money."

Jan 1, 2014

By J. Saunders, N. Pretorius, G. Krafft, T. P. Katakwa

Imagine being able to see all the future planned mining activities in real time. This is exactly what SIMS (Short Interval Management System) will enable you to do. SIMS is a real time short interval control system that continuously measures and sets optimised plans for mining production processes. The system utilises algorithm-based software that takes resources (people, equipment, tasks, and workplaces) and gives you the best achievable plan. The algorithm was developed using methods found in the field of metaheuristics. A metaheuristic is a strategy to designed to efficiently search for optimal or near optimal solutions to problems that are very complex computationally. (Glover, 1986) There are several algorithms that have been developed to solve optimisation problems which are difficult to solve using traditional techniques. This has given rise to a field called evolutionary computing. (Simon, 2013) Examples of these techniques are genetic algorithms, particle swarm optimisation, and ant colony optimisation. These methods are used to solve problems in a variety of fields. As an example, Kok and Lane (2012) used particle swarm optimisation for equipment allocation in a mechanised underground mining environment. The first SIMS deployment took place in a platinum underground tabular mechanised mine near Burgersfort (province?) from 2017-2019. This included the development from a paper-based system to a fully operational online system. SIMS then moved to a second site and is currently being tested in a second platinum underground tabular mechanised mine in South Africa. Full deployment of the system is currently being phased in. SIMS was built in response to issues that have been plaguing the mining industry for years. These issues are all aligned into one major problem statement: how can we optimise mining production processes without compromising safety? This product was developed by combining years of mining experience with software development. SIMS is based on a four-pillar concept. Safety, productivity, accountability, and business improvement. SIMS uses a set of pre-configured mining and production rules, and with the resources that are available, to determine valid short term production plans. A background algorithm then determines the optimum plan to be executed. The system continuously produces a set of job cards that are pushed to respective operators on their allocated tablets. The management portal component allows you to view and manage all current and planned work on any connected device available. This allows real time visibility of completed, current, and planned work to operators, service departments and management, i.e., seeing into the future.

Sep 1, 2021

By R. Mumbi, M. Peart, E. Arinaitwe, B. Mbao, J. Zulu

Since 1925, xanthates have been widely used in sulfide flotation due to their low cost, ease of manufacture, and ability to float most value species. However, the industry's increasing need for safer and more selective alternatives, driven by low head grades, poor-quality, difficult-to-process ore with complex mineralogy, and stricter environmental regulations, has led to the development of Solvay's AERO® XR series of collectors. These custom-formulated products are based on greener chemistries and offer metallurgical benefits that are similar to or better than those of xanthates, without the safety concerns. Developed through Solvay's Flotation Matrix (FM) 100 approach, the XR series collectors are suitable for a wide range of applications, including the processing of Cu, Zn, and Cu-Ni, as well as the flotation of precious metals. This paper will highlight the differences between xanthates and XR series collectors, and present case studies of their successful commercial application at various global operations.

Jan 1, 2023

By J. O. Claassen

"A study conducted at 22 operating mines in the southern African region indicated that each mine employs about five management and improvement methods with roots in the manufacturing industry. All respondents reported the implementation of cost-saving initiatives, whereas 80% of the mines are affected by restructuring. TQM, Six Sigma, BPM, and TOC were found to be the most prevalent manufacturing management and improvement methods used. A mechanistic vs systemic evaluation of the suitability of these methods to bring about positive change in the industry suggested that complex, ever-changing mining systems are better served by a systemic flow-based approach, which is embedded in methods such as TOC, JIT, TPS, and Lean Production. These methods, however, lack industry presence, possibly because they do not effectively deal with the unique challenges associated with the mining environment. It is argued that successful mining business management and improvement depends on management’s ability to deal effectively with mining industry-specific requirements, the integration of the geologymining- plant system, and the implementation of systemic flow-based principles in all aspects of mining. IntroductionThe study aims to explore the use of manufacturing management and improvement methodologies in the southern African mining industry. Considering the unique challenges associated with mining operations, attention is given to the applicability of the most commonly used manufacturing methodologies in the tactical, operational, and strategic environments. The article endeavours to stimulate more research and debate in an unexplored field of study."

Jan 1, 2016

By M. Ataei, F. Sereshki, R. N. Masir

Given the inherent risks and disruptions in underground coal mining operations, strengthening the resilience of critical infrastructure has become a vital priority. This paper aims to evaluate the resilience of the underground coal mining environment using historical data and expert judgment. The study serves as a framework for optimising the utilisation of critical infrastructure to minimise operational disturbances. To achieve this, a practical methodology has been developed, incorporating nearly two and a half years of collected operational data, a hierarchical structure, and a systematic approach. Furthermore, a case study is conducted to demonstrate the real-world applicability of the proposed method. Finally, the resilience index isintroduced as a straightforward summation of ranked impact factors, providing a clear metric for resilience assessment.

Dec 15, 2025

By R. G. Votteler, A. C. Brent

"The first in this series of two papers, on the potential of renewable electricity sources for mining operations in South Africa, investigated the internal structure of mining corporations to evaluate feasible alternative electricity sources that were identified as through earlier research. The purpose of this paper is to combine current knowledge about the external macroeconomic and the internal environments to produce a clear picture of how renewable sources of electricity could perform from the perspective of mining corporations in South Africa. The multi-attribute value theory (MAVT) approach was adapted to structure the research and results. The model was fed with real-time data provided from five different energy companies and four mining corporations operating in South Africa. The results show that the performance of hybrid versions of the currently used electricity sources (diesel generators and Eskom grid connection) with solar PV and onshore wind is favourable compared with the current sources alone. The advantage of diesel generators is significantly greater than that of the Eskom grid connection. By combining the macroeconomic influences with the MAVT results, hybrid solar PV versions are identified as having the greatest potential. In second place are hybrid wind solutions, which have the shortcoming that good wind conditions occur only in coastal regions where there are fewer mining activities. Geothermal hybrid versions are the least favourable owing to the lack of service infrastructure and high initial investment costs.IntroductionRecent developments in the macroeconomic environment necessitate an investigation of the internal structure of mining corporations to evaluate possible alternative electricitygenerating sources (Roehrl and Riahi, 2000). To be able to combine current knowledge of macroeconomic factors and the internal structure of mining corporations, the research process is presented in two papers. The first paper (Votteler and Brent, 2016) investigated the internal structure and argued that a strategic tool should be used to evaluate electricity sources from the perspective of mining corporations. The multi-criteria decision analysis (MCDA) approach was selected as the most appropriate strategic tool. Based on a literature review of previous similar MCDA approaches in energy planning, it was concluded that no adaptation of MCDA methods could be found from a corporate, mining, or South African perspective. Finally, the paper investigated the internal evaluation structure in collaboration with mining corporations, by identifying the criteria they use to evaluate electricity sources."

Jan 1, 2017

"SAMPLING: THE IMPACT ON COSTS AND DECISION MAKING1. INTRODUCTIONFor years those in the minerals industry have been taking samples to assist them in making decisions; whether they be about investing billions of rand in a new mining operation, or simply whether a truck load of mineralised material should go to the mill or the waste dump, - we need a sample to help us make our decisions. This paper emphasises the importance and significance of sampling as a process, some of the associated technical problems and some of the advantages, especially in the light of traditional approaches that has usually left mine sampling to the least educated and lowest paid individuals on the mine. Perhaps the most important aspect that requires attention is the variability, usually measured in terms of precision, that tends to infect the sampling procedures. Francis Pitard 12 has stated: ""There is no such thing as reliable feasibility studies, unbiased ore grade control, accurate environmental assessments or effective process control, if you cannot identify and minimize the seven (ten) major sources of sampling variability. "" It is these ten sources of sampling variability and the way they arise that are briefly investigated. Variability is measured in terms of variances and rather than being self-compensating, there is good evidence to indicate that they are in fact additive at every step in the sampling and analytical process."

Jan 1, 2014

By C. O. Aksoy, G. G. U. Aksoy, A. Fisne, I. Alagoz, E. Kaya

Coal produced in underground mines is transported to the surface by means of conveyor belts throughout long roadways. The combustion of belts puts a large number of employees at great risk. Underground collieries differ from other underground mines -due to the combustible nature of the product. The most prevalent cause of belt fires in underground coal mine is spontaneous combustion due to oxidation of the coal, which also enables the conveyor belt to burn over time. In 2014, a belt fire in an underground coal mine in Manisa-Soma, Turkey caused 301 fatalities. A study has been conducted on this accident for approximately 3 years, consisting of combustion tests in a purpose-built research gallery, comparison of the test results with mine records of the accident, and CFD modelling of the mine environment. The intensity of the fire was sufficient to redirect the air flow underground, causin large amounts of toxic gases to fill almost the entire mine in approximately 15 minutes. It is recommended that CFD analysis be used in planning emergency action strategies in underground mines.

Dec 13, 2023

By A. Marek

The safe and optimal installation of roof support remains one of the biggest challenges in underground mining today. Traditional hand-held, roofbolt installation in conventional mining has been replaced, in a lot of mining operations, by mechanized equipment. This was a first step to moving the operators out of the unsafe working environment and a start on the trend toward a changed support regime in mechanized mining. However, the challenge of handling of the drill steel itself, as well as inserting resin cartridges and bolts, remains a major hazard and the cause of many lost-time injuries. The paper describes and discusses developments in this area, of mechanized bolting and on-board automation, presenting solutions to known problems, achievements to date, and future developments. The solutions presented will identify with addressing customer needs while touching on possibilities for further technology changes, keeping focus on the safety aspect for operators and the need to bring the operators even further away from the unsafe working environment. The-state-of-the-art technology in mechanized bolting equipment is presented and a brief outlook on the past, current, and future developments is given.

Jan 1, 2012

By N. Theron, R. F. Meeser

The global emphasis on conserving energy resources has led to the adoption of hybrid power systems in vehicles. Optimally applied, hybrid systems can save up to 40% on fuel costs. To optimally manage a hybrid vehicle's energy flow it is necessary to know, in real time, all the energy requirements to complete a given route. The energy consumption depends mainly on the vehicle mass, speed profile, and route topography. Of these, the topographic profile is the one factor that is only route-dependent and not influenced by the vehicle or driving styles. The heading vs. distance profile is also an example of a route characteristic not influenced by the vehicle or driving style. In this study the topographic and heading profiles are used to identify routes, and are easily measured by means of digital barometric pressure and compass sensors. Correlations between the current route and previously travelled/stored routes are performed based on their topographic and heading profiles in a point-by-point manner. Above-ground tests were first performed using a road vehicle and six routes to evaluate the system. The system consistently and correctly identified a 20 km route within the first 4 km. It also proved to function correctly in underground tests through the implementation of an instrumented hand-held surveyor's wheel. This system finds direct practical application in optimizing the energy management of an underground hybrid locomotive used by the mining industry in South Africa, but can also be of benefit in applications where route identification is required and using GPS is not feasible.

Jan 26, 2023

By L. J. Gerber, O. D. Eniowo, L. D. Meyer, S. R. Kilambo

Artisanal and small-scale mining (ASM) operations continue to grow across sub-Saharan Africa and serve as a source of livelihood to many rural communities. Owing to safety, health, environmental, and social concerns, the occupation has been regarded as a menace in several sub-Sahara African countries. Recent studies in the field of ASM prescribe formalization as a way to tame its excesses while enhancing its potential. This paper explores the concept of formalization as it relates to ASM and how it is being affected by the funding situation. The paper seeks to address the question as to whether formalization of artisanal mining operations can achieve the desired results in view of the lingering credit constraints in this mining subsector. It is recommended that, as a way of extending the scope of formalization, focus should be placed not only on access to credit in ASM but also towards optimizing the creditworthiness of ASM firms, with the goal of improving the viability of the operations.

Mar 2, 2022

By F. Wang, P. Rosario, A. Vazirizadeh

Advances in data science, machine learning, and artificial intelligence are transforming mining and mineral processing, and making them more algorithm intensive. The paradigm is shifting from one of detection and control to one of prediction and optimisation. To build up reliable prediction and optimisation models these steps should be passed: collect, aggregate, cleanse, and process large amounts of complex, structured, and unstructured data as a first stage. Next, the right tools must be used to extract meaningful features from the operational data for the build-up of a prediction model. A grinding circuit is one of the challenging areas in terms of determining its overall efficiency and the prediction of product quality. In a processing plant, some of the KPIs are typically unmeasurable or infrequently measured for real-time application, e.g. ore grindability and grind size. However, these variables are required to calculate the grinding circuit efficiency and to model the operation performance. In this paper, advanced analytic tools have been used to extract one selected KPI (cyclone overall P80 or final grind size) and its relationship with measured variables for an industrial dataset. The results illustrate that the performance of the grinding circuit can be predicted for real-time monitoring by means of measured data. Keywords: Grinding circuit, data-driven, machine learning, process modelling, hybrid modelling

Jan 1, 2020

By J. van der Walt, W. Spiteri

Flyrock remains a significant threat to the health and safety of mine employees and integrity of infrastructure, as well as to the safety of the neighbouring communities and their property. This investigation was motivated by the general lack of fundamental research and mathematically quantifiable data in the literature regarding the relationship between blast design parameters and their impact on flyrock. The focus was to develop a concept that can be used to mathematically quantify the trajectory of flyrock resulting from a blast, which can be used for future research. The ultimate goal for this technique, once it has been fully developed, is to: ➤ Enable mining operations to generate a database with accurate historical flyrock measurements resulting from their blasting operations ➤ Allow research teams to conduct scientific investigations into flyrock and the impact of various blast design parameters ➤ Generate point-cloud data to visualize blasts and flyrock in a virtual reality environment for training and education purposes. This paper summarizes a conceptual technique and preliminary fieldwork that was carried out to determine the technique’s feasibility and motivate further development. The results show conclusively that a modified photogrammetric technique is capable of capturing flyrock data for further processing and analysis. The data acquisition procedure can, at this point, be used to meet the first aim of the project, namely to gather a field database of historical flyrock generation. Further development of the technique is ongoing and it is envisioned that the scientific-based technique will provide a method whereby future flyrock studies will be comparable and that assumptions will be limited.

Apr 5, 2023

By S. Fazluddin, K. C. Sole, M. R. Serwale, T. Coetsee

The CSIR-Ti process employs lithiothermic reduction of titanium tetrachloride feedstock to produce titanium sponge. The product is therefore contaminated by a range of lithium and chloride species. In this study we examine the effects of particle size, temperature, and HCl concentration as input leaching variables on the removal of chlorides from the crude titanium sponge. A review of the aqueous chloride chemistry of Li and Ti provided initial conditions for leaching of impurity species from the sponge. Experimental results confirm that the effectiveness of leaching and removal of dissolved impurities from the sponge are dependent on leaching kinetics, which are influenced by temperature, particle size, and morphology. Of the variables tested, reaction temperature had the strongest influence on the oxygen content of the leached product. The HCl lixiviant concentration had a negligible effect under the conditions tested. Leaching of crude titanium sponge (−10 mm size fraction after crushing) at 14°C in either 1 M or 0.032 M HCl yielded a titanium sponge product that met the ASTM standard specification for commercially pure Grade 1 titanium, i.e., oxygen content < 0.18 mass% and chloride content < 0.15 mass%.

Dec 13, 2022

By T. Bohmer, L. Auret, N. Pillay, Z. Horn, P. Rambalee, A. Haasbroek

As part of a broader digital technology-enabled transformation programme, a major mining company is systematically implementing Advanced Process Control (APC) solutions and associated instrumentation throughout their operations. This paper highlights the approach and benefits of this holistic approach for a specific instrumentation installation, and APC installation at a South African coal processing plant. For the coal processing plant under consideration, a systematic approach was followed. Process sections/units are considered from upstream to downstream processing. APC solutions are designed for each process section and each process section is interrogated in terms of availability of sufficient process measurements to ensure stable, capable, and ultimately, optimised performance. Where insufficient process measurements are available, instrumentation upgrades are implemented. Finally, APC solutions are implemented, and evaluated in terms of productivity, safety, health, and environmental benefits. For the flotation section, an opportunity was identified to install froth sensors. The installed froth sensors provide measurements on froth velocity, bubble size, height, colour, and stability. The improved visibility that the froth sensors provided on the flotation process resulted in quick gains in terms of productivity: for example, instability in the feed to the flotation section could be quantified. This resulted in targeted process troubleshooting in an upstream thickener, and subsequent improvement of process stability, and reduced feed variance. The measurements from the froth sensors were further integrated in an APC solution. Proportional mass pull contributions per cell and per line can be inferred from the froth sensors, serving as controlled variables, while pulp level set points serve as the manipulated variables. On-off tests indicated that the advanced process control solution provided increases in yield and product quality.

Sep 1, 2021