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By E. Lutz, M. Momayez, K. W. Brown Requist

As real-time air quality monitoring becomes more prevalent in US underground mines, it is important to provide the highest data reliability with the fewest possible sensors. Real-time sensors remain costly, and these costs are not exclusively financial; the time required to install, calibrate, and maintain real-time sensors poses a large barrier to widespread implementation. Current atmospheric monitoring systems typically rely on displaying point-specific values. This requires operators to infer real-time airborne contamination distributions. Monitoring and control software utilizing mine ventilation network (MVN) solvers has been implemented in limited cases because of their ability to simulate ventilation systems quickly, but these solvers use a one-dimensional representation of the mine, limiting spatial resolution of estimated distributions. Computational fluid dynamics (CFD) has likewise been considered as a means to improve spatial resolution, but processing times prevent its use as a basis for monitoring and control. For the real-time monitoring of airborne contamination distributions, we propose a spatial interpolation method that can estimate the distribution of airborne contaminants in near-real time. This method provides a middle ground between fast processing times and increased spatial resolution. With the use of a pathfinding algorithm and optimization through absolute percentage error minimization, this method outperforms spatial interpolation with a Euclidean distance. By providing contamination distribution information to operators, this method and its derivatives stand to outperform current atmospheric monitoring systems.

Apr 16, 2024

By K. Hodgson, Cook. N. G. W.

Most structures are designed so that the possibility of failure is eliminated. However, some degree of failure in the rock around deep mine excavations is inevitable if mining operations are continued. The presence of failed rock constitutes a hazard the magnitude of which can be predicted by computer models from calculations of the energy change per unit area mined in stopes, or the field stress around service excavations. Empirical relationships between these calculable quantities and the incidence of rock failures and delays associated with them have been established. Experiments on the computer using different layouts enable the mining engineer to select the least hazardous of otherwise acceptable alternatives, and to predict the incidence of damage ahead of actual mining, so that appropriate measures to maintain an adequate degree of safety and productivity can be planned in advance.

Jan 1, 2014

By R. V. Peche

Since 1952, Bond’s equation has been used as a standard to predict the specific energy of grinding for a given duty. The Bond’s equation considers that the exponent is constant for all conditions. Hukki, in 1961, pointed out that the exponent is a function of the particle size, and concluded that the Bond’s equation applies successfully for an intermediate range of sizes; out of this range the Bond’s equation leads to high error as demonstrated in this paper. More recently, in 2004, S. Morrell presented a new formula in which the exponents vary with the feed and product size. This paper is based on Hukki’s approach and presents a new general formula, in which the exponent varies only with the feed particle size. This new equation has been proven in 82 observable cases in Peru and other countries around the world, involving ball mills and vertimills in different configurations over a wide range of feed and product sizes, work indices and mill diameters; in most cases, the predicted value has an error less than 10% with regards to the observed value and no need for any correction factor. Keywords: Grinding, specific energy, particle size, work index, variable exponent

Jan 1, 2020

By R. Castro, R. Gómez, F. Betancourt, M. Moncada

In block cave mining, rock fragmentation is a key parameter that influences the production level design and mine planning. Fragmentation occurs mainly by natural breakage during the caving process and in the draw column. The breakage that occurs within the column is known as secondary fragmentation. Secondary fragmentation has been successfully described using the block caving comminution model, which replicates the fragmentation mechanics between particles under drawn and vertical loads in a draw column. This model is based on a kinetic and population balance approach, in which non-normalized and normalized assumptions can be used depending on material and comminution system behaviour. In this paper, the non-normalized and normalized approaches are applied and compared to laboratory data to determine which assumption should be used for secondary breakage in block caving. Approaches are compared graphically, with the mean square error and the Fisher test with a false-rejection probability of 0.05. Based on a statistical analysis, the results show that the normalized model can be applied to all the rock types tested.

Nov 1, 2021

By J. Y. Foley, K. Eden, A. E. Grosz, C. J. Giles, J. E. Grosz

"Portions of the Icy Cape placer Au district have been described and exploited since the early 1900s. Industrial studies of Au-bearing garnetrich intervals established a 3.5 million troy ounce resource in the western half of the district. This estimate is not compliant with CIM and SME definition standards for Mineral Resources and Mineral Reserves. We note high variability in the textures of sediments and their heavy mineral (HM) content and composition in the district, probably as a function of the depositional environment. Sediments are medium- to fine-grained sands with a valuable HM assemblage that averages 26.0% in a range of 1.1– 72.6%. Valuable heavy minerals (VHMs) garnet, magnetite, ilmenite, rutile, and zircon, but excluding Au, average 7.9% in a range of 1.0–37.6% of the HM assemblage. Trace quantities of uraninite, thorite, monazite, xenotime, and others are noted. Garnets have an average Y content of 726 ppm with a range of 0–2150 ppm. Energy-dispersive X-ray fluorescence confirms compositions commensurate with Ca, Al, and Mg silicates. We provide empirical analytical data and note high variability in the textures, HM content, and compositions as a probable function of depositional environment. Icy Cape District land and resources are owned by the Alaska Mental Health Trust Authority and managed by the Trust Land Office (TLO). IntroductionThe Icy Cape Heavy Minerals (HM) District in Alaska subtends more than 200 km2 fronting the Pacific Ocean and backing to the foot of the Robinson Mountains at about 1700 m above sea level. We classify the district into geomorphic provinces; the eastern region as deltaic (Figure 1) and the western region as coastal plain (Figure 2), based on geomorphologic expressions. The coastal plain is entirely built up of unconsolidated outwash sediments and ancient beach sand deposits."

Jan 1, 2017

By J. Y. Foley, K. Eden, A. E. Grosz, C. J. Giles, J. E. Grosz

"Portions of the Icy Cape placer Au district have been described and exploited since the early 1900s. Industrial studies of Au-bearing garnetrich intervals established a 3.5 million troy ounce resource in the western half of the district. This estimate is not compliant with CIM and SME definition standards for Mineral Resources and Mineral Reserves. We note high variability in the textures of sediments and their heavy mineral (HM) content and composition in the district, probably as a function of the depositional environment. Sediments are medium- to fine-grained sands with a valuable HM assemblage that averages 26.0% in a range of 1.1– 72.6%. Valuable heavy minerals (VHMs) garnet, magnetite, ilmenite, rutile, and zircon, but excluding Au, average 7.9% in a range of 1.0–37.6% of the HM assemblage. Trace quantities of uraninite, thorite, monazite, xenotime, and others are noted. Garnets have an average Y content of 726 ppm with a range of 0–2150 ppm. Energy-dispersive X-ray fluorescence confirms compositions commensurate with Ca, Al, and Mg silicates. We provide empirical analytical data and note high variability in the textures, HM content, and compositions as a probable function of depositional environment. Icy Cape District land and resources are owned by the Alaska Mental Health Trust Authority and managed by the Trust Land Office (TLO). IntroductionThe Icy Cape Heavy Minerals (HM) District in Alaska subtends more than 200 km2 fronting the Pacific Ocean and backing to the foot of the Robinson Mountains at about 1700 m above sea level. We classify the district into geomorphic provinces; the eastern region as deltaic (Figure 1) and the western region as coastal plain (Figure 2), based on geomorphologic expressions. The coastal plain is entirely built up of unconsolidated outwash sediments and ancient beach sand deposits."

Jan 1, 2017

By M. J. Little

Potgietersrust Platinums Ltd is Anglo Platinum?s only open pit operation and annually extracts 57 million tonnes of rock from 2 open pits. Over the past 3 years ~220 km of exploration drilling has been done, ~1000 km of rock face have been exposed for face mapping and over 7000 laboratory and field tests have been conducted. This has produced large amounts of geotechnical data to be utilised for feasibility studies, initial slope design and ongoing slope optimisation. It was necessary therefore to develop geotechnical databases to manage the vast amounts of data collected. SABLE and MineMapper 3D databases were created for logging and mapping respectively, with rock testing data incorporated into both. A pit inspections database was developed in MS Access and the existing groundwater and slope monitoring database was improved. The databases were linked to AutoCAD and Datamine to ensure that the latest geotechnical data is used for planning, draughting and modelling. The use of geotechnical databases ensures that no data is lost, standards are maintained and analysis can be easily performed. This increases the confidence of the analysis and allows the geotechnical engineers to optimise slope designs and blast designs on a regular basis. This reduces the risk of slope failure thus making the open pits more economical and safe.

Jan 1, 2006

By J. Petersen, T. Moyo, J. Dinga

The leaching of chalcopyrite in ferric sulfate media is notorious for its slow and inhibited kinetics. Different methods have been proposed to improve the kinetics, including the use of organic compounds as additives to the leaching media. In this study, the enhancing effect of methanol, ethanol, 1-propanol, and 2-propanol on the leaching of chalcopyrite in aerated acid ferric sulfate solutions using different reactor systems was investigated. The results revealed a clear improvement of copper dissolution by methanol and 1-propanol relative to tests with no additives under similar conditions. Operating a continuous-flow mini-column reactor yields surprisingly good results, potentially related to the maintaining of a consistent leaching micro-environment on the mineral surface. Scanning electron microscopy studies showed that the alcohols result in the removal of surface deposits formed during the anodic dissolution, potentially thus facilitating improved cathodic reduction of the ferric ion to drive the anodic dissolution.

Jan 1, 2023

By S. M. H. Haddad, M. Saghaeian, R. Hejazi, V. Sheikhzadeha, A. H. Baladastian, A. Dehghani Ahmadabadi

Sulfide impurities in iron ore concentrates play an important role in designing pelletising and steel making plants. Therefore attempts are made to keep the sulfur content of the final concentrate produced by the plants as low as possible. Generally, in the beneficiation process of iron ore concentrate, the removal of sulfur is performed through magnetic separation systems, followed by reverse flotation. The sulfide content of the iron ore concentrates originated from two main sources, including pyrite and pyrrhotite. In this research, in order to compare the floating capability of these two types of sulfide minerals, two iron ore concentrates with different sulfide constituents, pyrite or pyrrhotite, were selected. Reverse flotation tests were done separately on these samples under similar conditions. Process parameters considered for the tests included pH (2, 4, 6, 8 and 10), collector consumption (150, 200, 250, 300 and 350 g/t) and frother consumption (40, 50, 60, 70 and 80 g/t). Potassium Amyl Xanthate (PAX) and Methyl Isobutyl Carbinol (MIBC) were the collector and frother used in the tests, respectively. For modelling and optimising process parameters, the Central Composite Design (CCD) method was applied to the test results. Empirical coded equations were obtained for responses involving weight recovery, Fe recovery, Fe grade and S grade. Finally, comparison of test results revealed that the elimination recovery of pyrite sulfides was far greater than pyrrhotite sulfides, and it was possible to remove 84% sulfur content of the pyrite sample compared to minus 30% for the pyrrhotite sample. Keywords: Reverse flotation, pyrite and pyrrhotite, sulfur removal, iron ore concentrate, beneficiation plant

Jan 1, 2020

By R. Asamoah, P. Forson, S. Xu, W. Skinner, M. Zanin

In most auriferous hydrothermal deposits, gold is preferentially associated with pyrite and arsenopyrite minerals, with higher economic gold values noted for the latter and arsenian pyrite minerals. In this paper, surface (Cryo-XPS) and solution (EDTA extraction) analysis were used to characterise pyrite and arsenopyrite minerals under different aqueous conditions involving electrokinetic study and collector interactions to better understand ways of improving the separation of pyrite and arsenopyrite. The evidence showed higher surface oxidation at solution pulp pH values in the range of 4-11 for arsenopyrite relative to pyrite. The observed highest ratio of pyrite to arsenopyrite selectivity was 1.7 at collector concentration of 50 g/t and decreased with an increase in collector concentration. Keywords: EDTA extractable iron, selectivity index, differential flotation, grade engineering

Jan 1, 2020

By C. R. Royal, B. E. Friedland

Energy & Densification Systems (EDS) has developed patented new technology crushing/milling equipment. The EDS Multishaft Mill is a compact vertical mill – utilising high-speed impacts to break down particles with large reduction ratios, low energy consumption and improved liberation. The milling action combines several processes to provide a multitude of output products to satisfy various specifications. Comminution often accounts for more than 60% of the total power consumption on a mine. Two of the key problems to be solved in comminution is to bring down the specific energy required to reduce particle sizes; and to improve liberation or improve the efficiency of the beneficiation and recovery of the required elements. The EDS Mill has shown extensive improvements in both these areas with energy efficiencies up to 75% better than conventional milling equipment and improving liberation beyond the standard beneficiation processes. Conventional comminution equipment requires massive, heavy parts to be moved or rotated, consuming a lot of energy in doing so and not inputting that energy into the breakage of particles. In the EDS Mill, ramping up the relatively small shafts to speed is all that is required. Once at speed, the momentum, together with the minimal amount of constant drive required, means that the energy can be transmitted directly and efficiently into breaking down the particles. The high-speed impacts allow for a shattering effect of the particles and this quickly generates a high ratio of fines. Furthermore, the single impact force breaks particles in a very different manner to conventional compressive force breakage. With compressive force breakage, the particle breaks from point to point. With high-speed impact force breakage, the force tends to migrate through the weakest areas of the particle, which tend to be the mineral boundaries. This, therefore, means that when the particles break, the various minerals are exposed and hence liberated. Keywords: Comminution, high-speed impact, liberation, energy efficiency, novel comminution

Jan 1, 2020

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 U. Atici, R. Comakli

"Understanding rock properties is of vital importance in mining and civil engineering. Rock properties are generally determined through laboratory tests, which require a large number of uniformly shaped samples and technicians who use indirect methods to determine rock properties. The texture coefficient (TC), which represents various textural parameters including the size, shape, orientation, and relative proportions of grains and the matrix, is an efficient means for indirectly evaluating the mechanical behaviour of rocks. In this study, 12 different rocks (ten granites, one diorite, and one gabbro) were collected and their engineering properties. including specific gravity, porosity, P- and S-wave velocities, Schmidt rebound hardness, uniaxial compressive strength, and elasticity modulus, were investigated. Relationships between TC and these measured properties were assessed. Statistically significant (at the 95% confidence level) correlations were found between the TC and compressive strength, elasticity modulus, sound velocity (both compression and shear waves for dry and saturated samples), but no significant correlation was found with Schmidt rebound hardness. The results suggest that it is possible to use the relationships between TC and the mechanical properties of rocks in rock classification. IntroductionIn every aspect of rock engineering, knowing rock properties is essential for determining and predicting the behaviour of rocks and rock masses. Mechanical properties of rocks are important parameters in mining, geology, and engineering, and they are affected by textural characteristics such as grain size, grain shape, cement type, degree of cementation, mineral content, and the ratio of the grain area to the matrix area. The effects of textural properties on the physical and mechanical properties of rocks have been investigated for a long time, and previous studies revealed close relationships between single parameters related to rock texture and mechanical properties of rocks (Akesson et al. 2001; Gunsallus and Kulhawy 1984; Merriam, Rieke, and Kim, 1970: Onodera and Kumara 1980; Prikryl 2006; Ulusay, Tureli, and Bider, 1994; Tugrul and Zarif 1998). Rock properties are usually determined using mechanical tests, which require uniformly shaped and relatively large samples. However, it is not always possible to obtain such samples. Furthermore, rocks with similar textural and structural properties may exhibit different mechanical behaviour. Howarth and Rowlands (1987) developed a texture coefficient (TC) that expresses all the main textural parameters of a rock in a single dimensionless quantity based primarily on statistical assessment. The TC makes it possible to understand the effects of a rock’s textural properties on its mechanical properties using thin sections instead of large, uniform samples. Ersoy and Waller (1995) investigated the relationship between strength and TC for limestone, sandstone, and siltstone; they also examined the effect of rock properties and TC on drilling performance. Ozturk, Nasuf, and Bilgin (2004) explored the relationship between rock quality and TC by evaluating the uniaxial compressive strength (UCS) values of limestone, basaltic andesite, and tuff. Gupta and Sharma (2012) evaluated TCs as well as the petrophysical and mechanical properties of quartzite from the lower and higher Himalayas and found a strong relationship between TC and UCS. Similarly, Ozcelik, Bayram, and Yasitli (2013) investigated the relationship between TC and various parameters in marble by applying the statistical analyses developed by Ozturk, Nasuf, and Kahraman (2014)."

Jan 1, 2019

By Y. R. Murthy, S. Angadi, A. K. Bhatnagar, S. K. Tripathy, L. O. Filippov

Dolomite is an essential raw material for the refractory industry, a flux in the iron and steel industry and also for the extraction of magnesium metal. Generally, particle size reduction, screening and classification are used for the preparation of the high-grade sized material for different applications, whereas low-grade fine fractions are not utilised. These fines or low-grade overburdens are dumped at the mine site for future utilisation, which creates environmental issues along with inadequate space management. In the present investigation, a detailed study was carried out to decrease the silica content of the low-grade dolomite fines from Gomardih , India, containing 28.6% CaO and 20.1% MgO along with 8.3% silica. Different process flow sheet options were evaluated with a combination of dry classifier, wet classifier, gravity concentrators as well as flotation. Different process variables were assessed along with mineralogical characterisation to optimise the process for efficient rejection of siliceous gangue minerals. Results indicated that dolomite, calcite and quartz are the major mineral phases present in the ore along with other minor minerals. It was concluded that two-stage flotation was an effective process for the reduction of silica up to below 1% after grinding to a particle size below 212 μm. A process flow sheet with a combination of gravitation air classifier and flotation can produce a concentrate with silica content below 4.5%. Keywords: Dolomite, flux, dry classification, flotation, characterisation, beneficiation

Jan 1, 2020

By M. Kumral, Y. A. Sari

Underground mining operations tend to have higher operating costs than surface mines. When metal prices decrease, profitability is jeopardized due to the high costs. Therefore, mining management harnesses new practices that increase operational efficiency. One way to manage this challenge is to invest in new mine planning practices. Stope layout optimization as a part of underground mine planning aims to identify a portion of the orebody in the form of production volumes (stopes) to maximize profit under roadway and stope dimension constraints. In this paper we propose a novel approach based on identifying ore-rich areas of the deposit and prioritizing their extraction through an iterative heuristic clustering approach. The proposed approach is compared with and validated by an exact method through a small mining example. The heuristics produced nearly identical results in a very short time. Finally, a case study was carried out using a larger data-set. The cluster-based iterative approach generated nearoptimal stope layouts in a computationally effective manner.

Mar 1, 2021

By P. Ramsaywok, S Ndanduleni, G. Legodi

The objective of this paper is to share the optimisation journey of a pilot Reflux classifier (RC) circuit in the Exxaro GG1 plant, at Grootegeluk beneficiation complex in Lephalale, South Africa. The RC circuit was commissioned in 2016 to produce semi-soft coking coal at its fines circuit; however the stability of operation as well as the quality control of the coal product was not fully achieved. Various test campaigns and optimisation studies were conducted to understand and optimise the RC circuit at GG1. The studies revealed circuit design inefficiencies; provided an improved technical understanding of the current pilot circuit and the parameters required for the circuit to reach a stable operation. The operation was stabilised with its current inefficiencies to produce an average 12.5% ash semi-soft coking coal product for sustained periods, above the initial target of 10.3% ash. Keywords: Reflux classifier, coal

Jan 1, 2020

By E. P. Preis, R. C. W. Webber-Youngman

The real cost of any mining incident has, empirically, proven to be estimation-driven, rather than factdriven. One of the main reasons for this lies with the complexity of the cost composition of any given mining incident. Incident costs comprise both direct and indirect cost factors, and in many cases the costs associated with these factors are incurred during different time periods following the incident. In this paper we aim to identify the various cost factors arising from mining incidents, provide a thorough understanding of all the potential cost factors identified, and draw general conclusions on the knowledge obtained. Furthermore, recommendations are made on how mining companies could use the results, in order to assist them in calculating the costs of mining incidents. The paper also provides suggestions for further research, with the emphasis on the most significant immeasurable cost factors, namely the costs of implementing job accommodations following an incident, the harm to company reputation, and the decreased productivity due to low worker morale/psychological factors following an incident. If mining companies are aware of and understand which factors could contribute to the cost of any given incident, future planning and incident cost estimations could be easier. It should, however, be noted that although this study provides a comprehensive list of cost factors (and detailed explanations), other unknown cost factors relating to mine incidents could prevail in extreme cases.

Jan 1, 2021

By G. R. Lane

My opportunity to serve as President of the prestigious Southern African Institute of Mining and Metallurgy (SAIMM) was made possible by an Anglo American scholarship 39 years ago—a pivotal moment that set me on a career path spanning various roles and start-up ventures in the mining industry. Over the past decade, I have been privileged to broaden my experience by consulting across diverse industries globally. This exposure revealed something profound: what I had previously considered mining-specific challenges are, in fact, universal across many sectors. At its core, a mining operation is a complex system of interconnected activities—from exploration through mining operations like drill and blast, load and haul, to beneficiation, and outbound logistics. My cross-industry work has clearly shown that diverse sectors, such as chocolate manufacturing, tissue paper production, toilet paper converting facilities, labgrown diamonds, or high-tech equipment lifecycle management, all rely on value streams of interconnected activities to transform products. The objective is to maximise throughput while effectively managing performance variability. The primary difference lies solely in the specific technical expertise required for each industry, such as chemical, mining, processing, or metallurgical engineering. Across all these industries, I have observed a consistent pattern, that is, performance is primarily driven by individual efforts, where people react and work diligently as situations unfold in real-time. General managers and their teams often operate tactically, focusing on explaining yesterday’s poor performance rather than proactively setting up operations for success. This often resembles an ‘‘under-7s soccer match’’, with everyone chasing the ball. The common response to issues is to add more ad hoc meetings. This effort-driven organisational behaviour persists regardless of whether operations are greenfield digital manufacturing facilities, advanced digital mines with advanced process control, or operations run on paper and Excel spreadsheets for data acquisition. Paradoxically, more real-time data can lead to increased data noise, greater indecision, and sometimes, lower performance. Despite value streams often operating significantly below capacity, organisations continue to invest heavily in additional equipment or in ‘‘glossy brochure promises’’ of Industry 4.0 digital technology and real-time data solutions, which frequently fail to deliver value. This leads to a critical question: Have we underinvested in our most valuable resource— people? Even Tesla faced this challenge with their underperforming fully automated Model X facility. We must shift our focus to designing the ecosystem, or operating model, of our organisations. This extends beyond the traditional triad of people, process, and technology, and moves beyond simplistic views of change management. Artificial Intelligence (AI) has the potential to add significant value, but it also introduces another layer of complexity into designing the organisation of the future. My full presidential address below at the SAIMM AGM discussed the symptoms of an effort-driven organisation and covered the fundamental building blocks and requirements of an operating model, including recommendations on implementing a people-centric approach.

Oct 2, 2025

By S. Saeed, N. Coulson, P. F. Stewart

"The Mine, Health and Safety Act No. 29 of 1996, as amended, embodies worker self-regulation to advance health and safety in the workplace. An important provision for this is the Right to Refuse Dangerous Work (RRDW). This paper explores worker perspectives about the implementation of RRDW on South African mines against a backdrop of revised guidance in the sector: ‘Guideline for a Mandatory Code of Practice on the Right to Refuse Dangerous Work And Leave Dangerous Working Places’, gazetted in February 2016 by the Department of Mineral Resources (DMR). A mixed methods study conducted at mines (n = 14) included a survey of workers (n = 293), focus groups (n = 6) and in-depth interviews (n = 16). Workers reported a high level of awareness, a positive attitude, and experience of the formal RRDW. However constraints to the formal RRDW meant that informal worker resistance to dangerous work was commonplace. Evidence of informal non-confrontational consultation, cooperation, and collaboration in the event of a dangerous workplace also emerged between workers, and supervisors. The research underscores the importance of the RRDW and worker health and safety representatives to mine health and safety. The revised guidance addresses RRDW implementation gaps, but of concern is the potential partiality towards management interests. IntroductionEnsuring that mineworkers act on their duties and responsibilities for health and safety remains a concern across the globe. Article 13 of the International Labour Organization (ILO) Convention Safety and Health in Mines (176 of 1995) entrenched the Right to Refuse Dangerous Work (RRDW) as an important mechanism through which workers act in the best interests of their own occupational health and safety (OHS) and is considered a cornerstone of worker self-regulation (ILO, 1995). Countries ratifying Convention 176 are under obligation to make this right available to workers through OHS legislation that frames the circumstances, procedure, and protection of workers from discrimination in the event of a formal work refusal. The Convention has been ratified by 31 countries, with South Africa becoming a signatory in June 2000 (ILO, 2000). Worldwide studies show that workers use this right with caution (Hilgert, 2013) and cases associated with work refusal are rarely presented in court (Gunningham, 2007; Cooper, 2013). Rather, in cases of formal notification of a work refusal, issues arising out of this are addressed either in the immediate workplace or through the site OHS system and/or at industrial tribunals or similar mechanisms (Harcourt and Harcourt, 2000)."

Jan 1, 2018

By D. V. J. W. Groenewald, T. M. Louw, L. Auret, S. M. Bradshaw, A. V. Cherkaev

Unexpected equipment failures lead to financial losses due to production disruption. Time-based maintenance, based on checks over regular time periods, has been employed to minimise disruption. However, the improvements it can offer are limited as it may lead to unnecessary service of healthy equipment or missed failures occurring between service intervals. Condition-based maintenance (CBM) provides a further improvement to equipment reliability by detecting faults and predicting remaining useful life (RUL) based on equipment health monitoring. Its application in the mineral processing industry is hindered due to the high cost of health monitoring equipment. In this study, two stochastic process models, the adaptive auto-regressive model and the gamma process, are compared in their ability to forecast the degradation state and to provide RUL prediction. The gamma process model was found to be effective in both tasks. Due to its simplicity and minimum hyperparameters requirements, it is proposed to use the gamma process as a baseline for comparison with other models. Keywords: Condition-based maintenance, remaining useful life, slurry pump, adaptive autoregressive mode, gamma process

Jan 1, 2020