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By A Deakin

It has been almost a decade since the release of the International Council of Mining and Metals (ICMM) Health and Safety Critical Control Management: Good Practice Guide (2015a). During this time the ICMM member companies, along with many others across industry, have been busy designing, deploying and enhancing their own critical control management (CCM) programs. So, what have we learnt? This paper discusses the scope, application and learnings from the implementation of CCM within the mining industry. What’s going well? What are the common challenges? What are the opportunities to strengthen the approach? What are the threats to successful implementation? The paper draws on the author’s experience as one of the key contributors to the development of the CCM Good Practice Guide and an adviser to many mining companies, including six of the ICMM members. The paper focuses on the practical (operational) application of CCM and the cycle of identifying, defining, implementing, verifying and improving critical controls at the frontline. The paper also includes a discussion on the safety performance of the ICMM member companies over the past decade and provides a recommendation for how CCM can be incorporated into a more proactive model to measure safety performance. The paper concludes with practical recommendations that mining companies, regardless of their CCM maturity, can consider as they look ahead. They are supplemented by three additional recommendations for consideration at the industry level.

Apr 16, 2024

By M Qiao, A Sugden, W Zong, J Hines, J Roberts, T Ren

Long-term exposure to respirable dust continues to present an occupational health and safety hazard to mine workers in underground mines. Workers who are exposed to mine dust can develop occupational lung diseases including coal workers’ pneumoconiosis (CWP) or ‘black lung’, progressive massive fibrosis (PMF) and chronic obstructive pulmonary disease (COPD). To demonstrate the exposure impact of certain working conditions and improve dust management in longwall development panels, this paper details the development of a computational fluid dynamicsvirtual reality (CFD-VR) based training tool. The tool has been developed as an educational platform to facilitate the effective communication of workplace health and safety (WH&S) dust control measures for continuous miner operators and engineers. The study introduces a promising approach to model ventilation and dust flow patterns based on site-specific data, employing computational fluid dynamics (CFD) for a detailed analysis and visualisation of these mechanisms. Additionally, an algorithm has been developed for processing the large and complex CFD data sets into a form amenable for visualisation within a virtual reality (VR) environment using standalone VR headsets with limited processing power. This training tool has been deployed to mine sites with the specific purpose of educating users on the hazards of dust emissions and the best practices for control.

Apr 16, 2024

By S Harrison

Work health and safety duties around Australia include duties to manage psychosocial health and safety (mental health) of workers engaged by businesses or undertakings and of other persons impacted by the operations of the business or undertaking. Persons conducting a businesses or undertakings must develop systems of work and policies and procedures for ensuring, so far as is reasonably practicable, the safety and health of workers and other persons. Officers have a duty to exercise due diligence and to ensure effective systems are developed, implemented and resourced. The developed systems will only be effective with worker’s co-operation and engagement. The duties placed on workers by work health and safety laws are an important part of the safety matrix of obligations. Supervisors and Leaders are workers and they play a critical role in delivering health and safety outcomes. To deliver these health and safety outcomes with respect to psychosocial safety Supervisors and Leaders need to understand their obligations and have a framework to use to assist them in understanding what workers require and what steps need to be taken to meet their duties. They also need to take steps to assist those workers that they supervise to meet their duties.

Apr 16, 2024

By S Flanagan, M M. Mete, A R. Tiryaki, M Guresci

First Quantum Minerals (FQM) operates the Cayeli underground copper mine in Turkey. In response to a lost time incident (LTI) that occurred at the mine in 2022, the mine management decided to introduce a new safety approach on-site. The initiative began with a comprehensive safety culture analysis conducted by Arti Consulting, involving focus group studies. Employees actively participated in candid discussions, sharing their insights on safety issues and offering solutions. These conversations were meticulously audio recorded, resulting in over 150 000 words collected from more than 100 employees. These transcribed narratives then underwent rigorous semantic analysis, with the assistance of a sociologist, to identify and dissect patterns of unsafe behaviour. This analysis found areas for improvement, particularly in near-miss and incident reporting, quality of safety toolbox talks and effectiveness of pre-work risk assessments. Subsequently, mine management deliberated on these insights and devised corrective actions. An emphasis was placed on involving all employees in the corrective actions through communication training, empowering them to own the decisions and changes made. These impactful measures were seamlessly integrated into FQM’s Think! Safety Program, which embodies FQM’s sensible health and safety strategy. FQM partnered with Strika Entertainment (Strika) to develop innovative visual-first safety communication tools that use illustration, animation and graphic design to simplify complex messaging into easy-to-understand edutainment. As part of this approach to safety communications, Cayeli and Strika revamped the safety toolbox talks to encourage employees to voice their concerns and receive feedback when their suggestions were implemented. The response from employees has been positive, with over 200 unsafe behaviours and conditions reported within the initial two months of launching the Think! Safety Program. Remarkably, the Cayeli Mine has not experienced any LTIs for the past 500 days as of 9 December 2023. This paper encapsulates the dedicated efforts to transform Cayeli into a safer mining operation.

Apr 16, 2024

By A. Chuma, K. J. Nyembwe, H. Simonsen, J. H. Potgieter

Different concentration techniques were evaluated for preconcentration of a mineral ore at a coarser size to avoid energy and resource wastage. Specifically, the aim was to reduce milling costs and energy required in the beneficiation of tin. In this study, cassiterite (0.17% Sn) was the mineral of interest in a pegmatite ore body associated with quartz (SiO₂ > 60%) and alumina (Al₂O3 > 20%). Three concentration techniques, namely dense media, shaking table, and flotation, coupled with characterization analysis, were used to assess the concentration response. The results confirmed that particle size and mineral liberation impact the separation process. High recovery and grade were obtained with gravity concentration methods (dense media and shaking table) for coarser (+300 to +212 μm) and intermediate (+150 to +53 μm) particle sizes. Lower recovery and grade were identified for much finer sizes (−53 to −38 μm). Flotation produced a high-grade product at a relatively low recovery and appeared to be only applicable to finer grains. Separation efficiency based on Schulz’s equation measured a segregation performance of 74.8% for dense medium separation and 60.7% for the shaking table for the coarse and intermediate particle sizes. Flotation only achieved a separation of 30%–40%. The results suggest that use of dense media separation as a rough preconcentration method prior to further grinding, and the utilization of a more advanced concentration technique for mineral recovery and upgrade, constitute a successful approach to improve process economics.

Apr 14, 2024

By V. W. Lumadi, S. Nyasha

The mining industry has yet to fully accept and embrace the strategic role of technology and innovation in successful business planning and execution. In this study, we empirically determine the factors that influence acceptance of technology solutions in the mining industry in South Africa, assess critical success factors influencing adoption of advanced technology in the South African mining industry, and explore challenges faced by the mining industry in South Africa in adopting advanced technology in its operations. Thematic content analysis is employed in the data analysis. Results show that critical success factors to the adoption of mining technology include learning culture, knowledge sharing, high labour costs, and behaviour of other firms in the industry; commonly identified challenges include inadequate engagement with external stakeholders, uncertainties, the cyclical nature of the sector, and high risk related to the adoption of unproven technology and performance systems focused on volumetric production. The study encourages mining companies to implement usage of technology. This can be properly done through regular engagement with the Minerals Council South Africa.

Apr 14, 2024

By Ahmad Rahbar-Kelishami, Zahra Karimi

When alumina is extracted from bauxite ore, one of the environmental pollutants created is known as red mud (RM). This study clarifies that the RM obtained from the Iran Alumina Company has a significant proportion of iron oxides (24%), alumina (19%), silica (17%), and calcium (21%), as well as trace amounts of other minerals. The elements in the RM can be removed and utilized again to reduce environmental pollution. Acid leaching is one of the best ways to selectively exclude some minerals from the RM. In this research, the RM is exposed to different inorganic acids, including HCl, HNO3, H2SO4, and H3PO4, and their binary mixtures. By comparing the results obtained from XRD, EDX, and SEM, it was discovered that CaSO4 crystals are formed by exposing the RM to sulfuric acid. Besides, phosphoric acid was only able to destroy the surface of RM particles. The XRD analyses of acid-washed residues demonstrated that except for the residue of HCl 5 N, all residues contain hematite, showing that inorganic acids cannot easily extract hematite from the complex phases of red mud. While the dissolution of RM with HCl or HNO3 will remove most of the calcium content of RM texture, increasing its iron oxide percentage, which may subsequently be utilized to make colors and pigments.

Mar 29, 2024

By Juan L. Yarmuch, Gonzalo Sepulveda

This article presents a novel approach to address the mining width-constrained open pit mine production scheduling problem in the context of medium-term planning. A mathematical formulation is proposed to incorporate mining width constraints into the production scheduling process, aiming to maximize the NPV of the schedule while ensuring enough room for the operation of mining equipment. To tackle the computational challenges posed by large-scale instances of the problem, we propose a method based on variable fixing and horizontal precedence generation. In this study, we apply the developed model to real-world scenarios from Radomiro Tomic short-term mine planning problems such as optimizing the timing of major truck maintenance and the impact of external factors, like the delay in the production of the Chuquicamata underground project. Remarkable improvements are observed with the mining width-constrained model. Specifically, the mining width satisfiability is enhanced from 2 to 60% compared to the traditional open pit mine production scheduling model, underscoring the significance of incorporating these constraints. The proposed method showed good results reaching optimality gaps within 5%.

Mar 28, 2024

By L. C. de Kooker, K. Esmaeili, I. Musonda, M. Ferentinou

A numerical investigation of the effect of pore pressure regime on the safety factor and the critical failure mechanism is presented for fly ash storage facility. Pore pressures’ measurements from standpipe piezometers and pore pressure estimated from seepage analysis are used to compare the factor of safety for a fly ash slope. This was applied for considering static and seismic scenarios. A probabilistic approach was applied to account for the uncertainties resulting from the limited data available and support a qualitative risk assessment evaluation. Slope stability analysis is conducted in two and three dimensions, adopting the limit equilibrium analysis approach, and also a finite element seepage analysis, to assess the stability of the slope. The two-dimensional cross-sections were extruded to three-dimensional models to estimate the factor of safety and associated shear failure. The results from the performed analysis suggest an increase in safety factor values of 5%.

Mar 27, 2024

By Abhiram Kumar Verma, Soumya Ranjan Mallick

Generally, waste such as soil and sandstone is used in mines for road construction or haul roads. In many such mines, it is challenging to design haul road pavement to match the dumper capacity. This paper investigates overburden soil to find its utility as a pavement material. It is found that overburden soil is unsuitable pavement material without stabilization; hence, nine composite materials are developed using overburden soil and RBI. Physical, mechanical and microstructural properties of unstabilized and stabilized soil are determined. Statistical analysis is carried out to assess the effect of soil type, RBI and curing period of strength characteristics of unstabilized and stabilized soil. ANOVA tests assess the influence of RBI percentage on soil geotechnical properties, and regression relations are developed. Two-way ANOVA shows the effect of RBI and soil type on soil geotechnical properties, whereas one-way ANOVA shows that the influence of soil type is more than the RBI. The regression relation is developed for CBR, UCS, Poisson’s ratio and modulus of elasticity with a good correlation coefficient. The performance of RBI is more with the finer material and reduces with an increase in the size of soil grains. The performance of the developed composite is better than the earlier developed composite based on overburden with fly ash, lime kiln dust, lime or clinker.

Mar 19, 2024

By Hossein Ghaedi, Hadi Fattahi

Despite the significant role of coal in the economic progress of nations, the occupational and health risks associated with its mining pose a major concern for industry stakeholders. The occurrence of roof collapses in coal mines remains a critical factor leading to substantial loss of life and financial damages for miners. Therefore, accurately predicting the roof fall rate (RFR) holds paramount importance. However, the uncertainty surrounding rock parameters in mines hinders the application of conventional methods to assess roof collapse rates in coal mines. To tackle the challenges associated with predicting roof fall rates in underground coal mines, this study proposes a novel solution by leveraging the Rock Engineering System (RES) method. The investigation is grounded in a dataset comprising 109 data points, encompassing crucial input parameters like depth of cover (DOF), primary roof support (PRSUP), intersection diagonal span (IS), mining height (MH), and coal mine roof rating (CMRR). In the model construction phase, 80% of the data (87 points) were utilized to build the RES model. A critical aspect of this study involves the evaluation of the RES model’s performance against alternative regression techniques, namely linear, power, exponential, polynomial, and logarithmic regression. This comparison was executed using the remaining 24 data points (20% of the dataset) for rigorous evaluation. Employing key statistical metrics such as mean square error (MSE), root mean square error (RMSE), and squared correlation coefficient (R2), the study systematically demonstrated the superior accuracy of the RES-based method compared to other approaches. In conclusion, the outcomes strongly support the efficacy of the RES method in predicting roof fall rates, not only in the specific case studied but also indicating promise for its application in other underground coal projects. This underscores the potential of the RES method as a reliable and versatile tool for forecasting roof fall rates in the complex and critical context of underground coal mining.

Mar 19, 2024

By Xie Junjie, Li Shina, Ma Ruixin, Min Changli, Yin Zichen, Li Kang, Shi Zhuonan

Cesium and rubidium were effectively separated by zinc ferrocyanide coprecipitation method, and the effect of precipitant addition amount on the separation of cesium and rubidium was studied. Under the conditions of Zn/Cs molar ratio of 0.45 and Zn/Fe molar ratio of 1, the precipitation rate of cesium is 84.01% and the separation factor of Cs/Rb is 164.65. The thermogravimetric curves of the sediment were measured, and the effects of roasting temperature, roasting time, and leaching liquid/ solid ratio on the extraction of cesium were studied. Almost all of the cesium was extracted under optimal conditions: roasting temperature of 600 °C, roasting time of 3 h, leaching temperature of 25 °C, leaching time of 0.5 h, and liquid/solid ratio of 5:1 mL/g. After the leaching process, the leach liquor with high concentration of cesium of 80.17 g/L was obtained. Finally, the leach liquor was further purified by solvent extraction, and the purity of the cesium chloride product reached 99.66%.

Mar 17, 2024

By Christos Roumpos, Philip‑Mark Spanidis, Francis Pavloudakis

Coal mining operations are large-scale, long-term frameworks of high complexity. Mining organizations accumulate, develop, and leverage knowledge from diverse scientific and technological fields as a result of these operations. Both practical experience and existing literature indicate that knowledge management (KM) methods within the mining industry primarily target solving immediate technical challenges and operational requirements. However, they are not commonly regarded as strategic tools to enhance the performance and competitiveness of mining companies. Empirical evidence from the Greek mining industry suggests that the management of available knowledge is intricate, less effective, and dysfunctional. This paper presents a methodology based on the principles of quantitative research (QNR), collaboratively conducted with a group of mining experts, to assess the KM landscape in the Greek mining industry. The methodology involves a structured data collection framework using questionnaires, subsequent statistical analysis, a discussion on critical methodological aspects, and an interpretation of results focusing on key aspects useful for planners and designers of KM systems in the mining industry. Finally, the paper concludes by summarizing the methodology’s outcomes and proposing further perspectives for research.

Mar 16, 2024

By R. J. Quevedo, Y. A. Sari, S. D. McKinnon

The large scale of cave mines leads to many challenges, including operational logistics and geomechanics design. In current practice, pillar stability assessment relies almost exclusively on stress analysis. However, stability is also affected by other factors including those related to operational aspects of the mining method, the effects of which are difficult to account for during the design stages. In this paper we present a case study of the application of a machine learning approach to evaluate the influence of these operational factors on pillar stability at the Chuquicamata underground cave mine in northern Chile. Due to the likely multi-factorial damage process leading to collapses and considering the different pillar conditions, a tree-based machine learning method was used and analysed to improve the understanding of the relative importance of the various contributing factors. Unlike stress analysis methods, it does not require any a priori knowledge of failure mechanisms, nor the calibration of associated controlling parameters. The proposed random forest model predicted pillar collapses with 80% accuracy despite limited samples to model from. The main contributing factors to collapses were found to be related to available pillar volume, cave front geometry, and time under abutment stress conditions. The effects and interactions of such factors were also studied, showing that careful and improved control over operational conditions can significantly reduce the likelihood of pillar collapses. These conclusions could not have been obtained from stress analysis alone, illustrating the complementary nature of conventional stress analysis and machine learning approaches.

Mar 14, 2024

By J. P. Gouvea

Back-analysis of two mining-induced tremors in 2011 was used to determine a modelling criterion for the entire Klerksdorp Goldfield (i.e., Vaal Reefs region). At that time, most mining operations in the region were owned by AngloGold Ashanti (AGA) and shared many geotechnical similarities. By 2018 AGA had sold off all its Klerksdorp operations to different mining companies, which continued applying the 2011 modelling criterion. As mining activities became more remote, scattered, and isolated, the extraction of isolated blocks of ground and remnants became increasingly necessary. However, the inherited criterion allowed only minimal or no mining activities at these areas. Keeping in mind that safety is the overriding consideration, an innovative numerical modelling approach, which includes the application of peak particle velocity designs, was developed to provide practitioners in the Klerksdorp Goldfield with a suitable criterion to justifiably and safely mine isolated blocks of ground and remnants. This would not always be possible if a conformist approach was used.

Mar 14, 2024

By S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By Christopher Mark

Six decades ago, the most dangerous job in the USA was mining coal underground. Roof falls were responsible for half of the deaths, killing about 100 miners every year. Fast forward to 2016 and zero roof fall fatalities. Just three miners were killed by roof falls during the following 6 years. How did the mining community achieve this historic goal? This paper starts by analyzing the roof fall fatalities in 1968, categorizing them by their fundamental cause. Then, it shows how each type of roof fall was reduced over time, using snapshots of the fatalities occurring in subsequent decades. Along the way, it evaluates the influence of the regulatory environment, changing mining methods, and better ground control technology. The study found that in 1968 more than half of roof fall fatalities at large mines were attributable to an inadequate safety culture. The immediate effect of the 1969 Coal Mine Health and Safety Act was to reduce the riskiest activities, like needlessly going under unsupported roof. Other hazards, like large roof falls, required technological developments before they were brought under control. Roof Control Plans, which the US Bureau of Mines had been advocating since the 1920s, played a significant role throughout the process.

Mar 12, 2024

By Yao Yevenyo Ziggah, Victor Amoako Temeng, Solomon Evans Kweku Koomson

Tyre hours/life deficit is a major operational challenge facing the mining industry which adversely affects materials production and costs. An accurate forecast of the tyre life is key in addressing this menace. This study for the first time employed the hybrid intelligent technique by utilising three metaheuristic optimisation algorithms, including particle swarm optimisation (PSO), genetic algorithm (GA), and whale optimisation algorithm (WOA), as trainers for the parametric weights and biases to optimise multilayer perceptron neural network (MLPNN) for enhancing prediction of on-site dump truck tyre life in the mine. Four hybrid models known as PSO-MLPNN, WOA-MLPNN, GA-MLPNN, and BP-MLPNN were developed using a total of 157 tyre dataset records obtained from a surface mine in Ghana. In assessing the prediction performances for the models developed, five statistical performance metrics of variance accounted for (VAF), Nash–Sutcliffe efficiency index (NASH), coefficient of determination (r2), mean absolute percentage error (MAPE), and correlation coefficient (r) were utilised. Moreover, ranking, uncertainty analysis and Bayesian information criterion (BIC) techniques were utilised to establish the most effective hybrid model, whereas sensitivity analysis was conducted on the input parameters. Results achieved showed that PSO-MLPNN was the best for prediction because it had the least MAPE value of 1.196% and relatively high values of VAF (99.642%), NASH (0.996), r2 (0.996), and r (0.998). Besides, PSO-MLPNN had the best selection criteria values of 6, 7.1725, and 444.834 for the ranking, uncertainty analysis and BIC respectively. Hence, PSO-MLPNN is recommended for the prediction of on-site dump truck tyre life for the studied mine.

Mar 11, 2024

By Xin Wang, He Shao, Wenpu Li, Yiyi Zheng, Xi Chen, Yurong Gao

This study utilized experimental and numerical simulation methods to investigate and analyze the atomization characteristics of three internal air–water mixed atomizers under different operating conditions. By comparing the research results, the effective dust control working parameters for the application of the selected atomizer in the engineering field were determined. Firstly, the atomization characteristics of the three atomizers were studied using a customized experimental system. The results indicated that nozzle 2 had a wide atomization range, a small atomization distance, and small droplet size; nozzle 3 had a narrow atomization range, large droplet size, and fast atomization speed; and nozzle 1 not only had a large atomization range but also could produce droplets of dry mist size with fast atomization speed, meeting the dust reduction requirements of the Majiliang Coal Preparation Plant. Secondly, Fluent software was used to simulate the atomization process and particle size distribution of the three internal mixed atomizers, determining the working conditions of the atomizers, the required number of atomizers, and the application angle of the atomizers in the internal mixed dust removal system. Finally, the atomized dust control system was applied on-site, achieving a total dust removal efficiency of 90.72% and a respirable dust removal efficiency of 89.75%.

Mar 9, 2024

By Tuanhui Wang, Qiwei Wang, Quanrui Liu, Jianhui Xu, Chao Wang, Yu Liu, Yuefeng Li

Rockburst is a highly destructive geological hazard that can cause casualties and equipment damage. To achieve highaccuracy discrimination of rockburst intensity, this article proposes an improved model that addresses the inefficient maximum membership principle used in traditional rockburst fuzzy evaluation models. The stress coefficient σθ/σc, brittleness coefficient σc/σt, and elastic deformation energy index Wet are selected as evaluation indicators for rockburst classification. Subjective and objective weights are obtained using the Delphi method and entropy weight method (EWM). Three types of membership function distribution forms are then used to obtain the membership degrees of each indicator to rockburst grades: trapezoidal membership function (TMF), normal membership function (NMF), and quadratic parabolic membership function (QPMF). Finally, six traditional models and six improved models are established using the maximum membership principle (MMP) and weighted average-maximum membership principle combination evaluation principle (WMP), respectively. Based on the analysis of 100 sets of rockburst field data, the accuracy, precision, recall, and F1-score of the improved evaluation model are increased by 11.3%, 0.097, 0.068, and 0.089, respectively, compared to the traditional model. The Delphi-NMF-WMP model is selected as the best model, with four performance indices reaching 97.0%, 0.979, 0.979, and 0.978. The best model is applied to evaluate the rockburst intensity of the Cangling Tunnel, Dongguashan Copper Mine, and Jiangbian Hydropower Station Diversion Tunnel, with evaluation results consistent with the actual situation, demonstrating the reliability and scientificity of the model.

Feb 28, 2024