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By E. Moosavi, K. Tolouei

In mine production scheduling problems are well-known, where most are categorised into deterministic and non-deterministic NP-hard problems because of their complexity. Many researchers have attempted to solve the problem by applying various optimisation techniques. While using traditional methods they observed extreme difficulty in solving highly complex problems. In the 1990s, many researchers addressed long-term production scheduling (LTPS) by using simulated annealing, the genetic algorithm, the tabu search algorithm, and the ant colony algorithm. These algorithms are known as the meta-heuristic algorithms, and have proved to be the most efficient algorithms for solving LTPS thus far. The firefly algorithm is one of the best methods for visualising problems related to LTPS, and provides the best possible optimisation. It is one of the simplest methods, and easy to apply to any NP-hard problem. The experimental, and comparison with other recently published algorithms shows that the proposed algorithm is feasible, and is an effective approach for long-term production scheduling problems. The results indicated that a better solution is obtained by the proposed method, compared to other methods in terms of cumulative net present value, and average ore grade. Additionally, the CPU time via the proposed model is roughly 2.52% higher than the other method.

Sep 1, 2021

By F. M. Ramadhan, M. R. Pratama

Monitoring open-pit mine road conditions has become very critical nowadays. There are several benefits to in conducting research on this field such as opportunity to improve truck’s speed which directly influences truck’s productivity. This research aims to provide a semi real-time, and sensors-based automatic road damage detector that predicts the road quality through road damage exact location tracing, road damages auto-classification, and real-time instruction in the form of work order format to mining road maintenance, and repair authorities through mobile apps and maintenance unit’s in-cabin display. It will also provide the maintenance/repair activity performance evaluation via integrated dashboards. The artificial neural network algorithm is applied during the process of data training regarding classifying road damages and severities which resulted in a valid model. The road damage classification model has a precision level of 80.5% in predicting whether the road is damaged or not. Using this approach, we are expecting to visualise a road quality map of all active roads on mine site.

Sep 1, 2021

By R. Minnitt, C. Morgan, D. Fourie

The problems associated with outliers and their adverse effects on resource estimation in deep level South African gold mines are presented, and solutions suggested in available literature are reviewed. Traditional Witwatersrand type outlier capping uses the 99th percentile grade as the upper limit, a somewhat blunt approach. The occurrence of high and low grade areas in mining operations and the estimation of resources using geostatistical techniques require that the assumption of stationarity be upheld. Honouring the stationarity of data requires that mining areas be subdivided into appropriately sized and spaced domains. In order to overcome high-grade conditionally biased block estimates, the overly strong influence of extreme grades is mitigated by using naturally occurring grade sub-domains, by identifying outliers within the grade sub-domains, allocating relevant capping limits, and weighting them in a post-estimation process to. Rather than applying a capping value across a domain it applies a maximum cap based on the extreme value and its range of influence; the method also ensures that relevant capping occurs even in lower grade sub-domains. The proposed method for capping outliers recognises that metal contained in high grade chip samples should not be over-capped, and based on the grade of surrounding samples. The post-processing method of capping outliers does not interfere with the kriging equations. The method is simple, elegant, and can be easily applied. An advantage is that the output from the kriging process is not overwritten, allowing for comparison between original kriging results and post-processing results.

Sep 1, 2021

By A. Melkumyan, K. Silversides

Chemical assays collected from blast holes have the potential to greatly improve the local accuracy of grade models. Assays must be assigned to the correct domain or they will introduce errors. Boundary surfaces created from the widely spaced exploration holes (~50m) do not provide sufficient resolution to correctly delineate domain boundaries between closely spaced (3-5m) blast holes. This paper demonstrates a probabilistic method for classifying production blast holes near domain boundaries. Gaussian processes models are applied to identify the assays and assay ratios most suited to distinguishing particular domains. These models are combined with the exploration based surfaces to classify the blast holes that can be confidently assigned to a particular domain. A reiterative method is used, where information from the blast holes closest to the exploration holes is used to label blast holes further away. This is tested on two domain boundaries in a banded iron formation-hosted iron ore mine.

Sep 1, 2021

By I. Kaabachi, F. Meunier, N. Morales

In open pit mining, ore and waste are hauled outside of the excavation area by trucks that move along a system of ramps. The design of these ramps must be carefully addressed because they have to comply with geomechanical constraints to ensure the stability of the pit walls, provide access to the different levels and phases, but also maximise the value of the extracted ore and reduce the extraction of waste. Because an optimisation approach able to deal with the design of the full ramp system seems to be out of reach at the moment, this paper addresses the problem of designing one ramp providing access to a single pushback, which has been determined beforehand. The optimisation objective is therefore to find a ramp that gives access to one given potential volume, while minimising its impact on the economic value of the volume. Two versions of the problem are formalised. One version allows the extraction of ore and waste only if this extraction is necessary for the ramp system. This version somehow minimises the intrinsic value of the ramp system. In the second version, it is possible to extract more than is needed by the ramp system. For instance, this takes into account the possibility of attaining ore on the wall opposite to the ramp as soon as the ramp reaches its level. In the setting mentioned above, the contribution of this work is three-fold. First, the computational complexity of the two different versions of the problem is presented and discussed; in particular, they are shown to be NP-hard. Second, compact integer programs modelling these two versions are proposed. Third, an efficient GRASP algorithm able to cope with the large instances of the problem is proposed. To assess the proposed approaches, the models and algorithms are applied to real instances with an off-the-shelf solver, illustrating and discussing their potential and relevance for the two versions of the problem. They are also compared with other approaches from the literature in terms of value and resulting designs.

Sep 1, 2021

By M. M. Ali, C. Musingwini, R. A. Phillips

The long-term open-pit mine production scheduling problem (OPMPSP) is typically solved in two broad stages. The first stage entails optimisation of the ultimate pit limit, which delimits the economical final pit and maximises the undiscounted value of the deposit. The second stage entails optimisation of the long-term open-pit mine production scheduling, which maximises the discounted value of the deposit. The long-term OPMPSP is a type of an NP-hard problem, such as the travelling salesman problem (TSP), because it is intrinsically complex to solve since it incorporates both hard and soft constraints. Therefore, metaheuristic approaches have been used to find global optimum solutions to the long-term OPMPSP. This paper presents a metaheuristic approach utilising a dual interchange algorithm (DIA) to solve the long-term OPMPSP. The DIA is a parent algorithm which supervises two subservient algorithms, namely, simulated annealing (SA) and Tabu search (TS). The DIA selects the better solution generated in each run from the two algorithms, and simultaneously penalises the algorithm that produced an inferior solution, while rewarding the one that produced a better solution. The DIA was tested on the three-dimensional Arizona Copper Deposit (KD) dataset, which is publicly available for research purposes from the online MineLib repository. It was set to generate net present values (NPVs) in five-minute intervals and the solution improved until it plateaued at about 30 minutes of runtime. The NPVs compared favourably to those obtained on the same KD dataset but obtained over 24-hour runtimes, when solved using simulated annealing and Tabu search algorithms, and the NPV generated from the work of Muñoz (2012) using the modified TopoSort as found on the MineLib repository at the time of this study. Therefore, this paper demonstrates that DIAs can be developed and used to solve the three-dimensional long-term OPMPSP.

Sep 1, 2021

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 I. O. Flores, A. Anani, H. Li

Current technological advancement has increased the exploitation of deeper ore bodies using underground methods. In certain cases, the mineral deposit starts near the surface and continues deep within the earth's crust. Such deposits are best mined with both underground and surface methods. Two main techniques are used to determine the optimal transition depth from surface to underground - a disintegrated approach and an integrated approach. Both methods have limitations in their use to determine the optimal transition depth. The objective of this research is to investigate the conditions in which an integrated approach to the transition depth problem is superior to a disintegrated approach. Three binary integer linear programming models are developed for this purpose: a surface and underground model for the disintegrated instance and an integrated model. A case study is performed to validate the models, with a comparative sensitivity analysis to obtain operational insights.

Sep 1, 2021

By E. Emami, J. Valencia, J. Sattarvand

The knowledge of the final location of a drillhole is critical in obtaining the expected blasting results. This paper proposes a new methodology to control the drilling accuracy in open-pit mines using aerial images and machine learning. Specifically, it investigates how support vector machines (SVM) and convolutional neural networks (CNN) are useful for automatically detecting blastholes over drone images captured in blasting patterns. Several datasets were obtained from different mines in Nevada (USA) and were used to train and test models. We then processed those images to create orthomosaic and digital elevation representations of the patterns. Thousands of patches were then extracted and augmented to develop SVM and CNN models. The results demonstrate that machine learning is useful for drillhole detection and, in this way, to control the drilling accuracy and use the explosive energy more efficiently.

Sep 1, 2021

By J. Githiria, D. Wachira

The conventional truck and shovel haulage system has become expensive to operate in most mines due to current strict environmental conditions, increase in depth and size of open-pit mines, increase in labour costs, and fuel costs. These factors have motivated the search for alternative material haulage options in open-pit mines. In-pit crushing and conveying (IPCC) system has been regarded as a plausible alternative in material haulage systems. However, usage of IPCC has been limited to a few mines due to limited knowledge of IPCC performance, and other technical factors of the system. This paper investigates, and evaluates the productivity performance of four types of IPCC systems (fixed, semi-fixed, semi-mobile, and fully mobile IPCCs) using mine productivity index (MPi). Using a model developed by MATLAB, the MPi for the four systems is computed using input variables such as availability, utilisation, performance and number of trucks and shovels in a limestone quarry. The mine productivity index for fixed, semi-fixed, semi-mobile, and fully mobile IPCC is obtained as 67.13%, 69.02%, 70.52%, and 71.52% respectively. In conclusion, the fully mobile in-pit crushing and conveying system is the most appropriate IPCC in the quarry, due to its better productivity performance compared to the other three IPCC systems and the truck and shovel system currently in use.

Sep 1, 2021

By L. Pretorius, S. Uludağ

This paper explores how to apply system dynamics principles to surface mining problems towards understanding the consequences of mining efficiencies. Some simulation examples related to machine and people performance have been used to demonstrate systems engineering concepts to mining engineers. The simulation tool used is Vensim, which is widely used in industrial engineering applicable to systems thinking, and systems dynamics. The science and mathematics behind the system dynamics as well as benefits and typical challenges are discussed to explore the applicability to mining problems. The benefit of having one less drill is easily quantifiable with the developed model which is one of many other measurable benefits, using the developed model. Some of the benefits of the improved quality of drill holes are not fully quantified as this depends on the mine specific inputs. There are examples of quantifying this in the other industries using system dynamics tools.

Sep 1, 2021

By C. Musingwini, A. S. Nhleko, P. M. Muke

Open-pit mine planning includes the determination of a long-term open-pit mine production scheduling (OMPS) plan. The OMPS plan is generally a three-dimensional (3D) block extraction sequence that seeks to maximise the net present value (NPV) of future cash flows, while complying with technical and operational constraints. The OMPS problem is computationally complex because it involves the analysis of large datasets, while simultaneously incorporating both multiple hard and soft constraints. The OMPS problem has been solved using deterministic or exact approaches, heuristic, and metaheuristic models. When compared to heuristic and metaheuristic models, deterministic approaches tend to take much longer to solve the OMPS problem when the number of constraints increases. Therefore, this paper presents a metaheuristic model which utilises a genetic algorithm (GA) framework to solve the OMPS problem. The GA-based model was applied to the Newman1 and Zuck Small mining instances, which are publicly available from the online MineLib database. The NPVs for the OMPS plan generated using the GA-based model for the two case studies were compared to the best-known published MineLib solutions obtained using the TopoSort heuristic model at the time of this study. For the Newman1 instance the equivalent annual NPVs were approximately US$6.6 million for the GA-based solution and US$5.1 million for the TopoSort solution. For the Zuck Small mining instance, the equivalent annual NPVs were approximately US$99.8 million for the GA-based solution and US$102.5 mil for the TopoSort solution. These results show that the GA-based model produced comparable solutions to some of the best-known solutions, thus, indicating strong potential application of GA-based models to solve OMPS problems.

Sep 1, 2021

By Hongsheng He, Xiaofang Lv, Jianfeng Wang

This paper provided an overview of characteristics of limonite ores as well as their influence on sintering performance. Evaluation experiments focusing on basic characteristics, granulation characteristics, and high temperature sintering characteristics had been conducted by using two types of limonite ores, then the principles of high effective utilization technology of limonite ores were discussed, and the sintering pot tests were conducted. Limonite ores possessed low total iron content, high combined water content, high SiO2 content, large average particle size, low adhering particles proportion, high porosity, high water absorption rate, short water absorbing time, poor granulation ability, high melt formation ability, low melt fluidity ability, low melt penetration ability, high melt absorption ability, low bonding phase strength, and high forming ability of SFCA. By taking the technical measures of ore-proportioning optimization, increasing the proportion of burntlime and segmentation granulation, the usage of limonite ores could reach 50% in sintering.

Aug 27, 2021

By Julián M. Ortiz, Antoine Caté, Oy Leuangthong, Ilkay S. Cevik

Mineral resource classification relies on the expert assessment of a qualified person (QP) to determine which blocks of a 3D mineral resource model are classified as measured, indicated, or inferred. The decision is often based on a combination of quantitative parameters related to the estimation process and qualitative decisions based on previous experience or preconceptions not captured in the numerical model. As such, the procedure is subject to inconsistency, that is, blocks with similar qualities may end up in different categories, mainly due to the subjective nature of the approach. In this paper, we present a methodology to assist the qualified person in this task by clustering blocks with similar parameters and then classifying them into categories in a consistent and automatic manner that only requires the specification of a few hyper-parameters. The result is a consistent classification into resource categories comparable to the result of a classification done by a qualified person but fully consistent and generated in a short time frame. The procedure begins with repeatedly sub-sampling the block model to determine a distance matrix using an unsupervised random forest approach and then clustering the blocks using the associated distance matrix. Then, all the blocks in the model are classified using a supervised random forest approach, which gives a probability of belonging to each class. The initial class can be determined from the class probabilities. Support vector classification with a radial basis function kernel is utilized to smooth the boundaries between classes and define the final classification. An approach to tune the hyper-parameters of smoothing is provided. The methodology is demonstrated with two examples from two gold deposits. Results are comparable to the classification done by the project qualified person using conventional methods.

Aug 17, 2021

By Scott Rosenthal, David Gilkey, Michael McGivern, Lorri Birkenbuel, Daniel Autenrieth, Ty Murphy, Hadi Aldossari

A safety climate case study was carried out at a surface metal mine where investigators administered the Liberty Mutual Short Scale Safety Climate Survey to 365–368 miners to measure safety climate in consecutive years. Following the baseline safety climate survey in 2019, Foundations for Safety Leadership (FSL) training was conducted with 81 middle to upper management employees at the mine site. Investigators found statistically significant differences in the pre vs. posttraining FSL assessment scores of the middle to upper management employees who attended the training. The follow-up safety climate evaluation was compared to baseline scores and revealed no significant improvement. The overall baseline company safety climate score of 76.38 increased minimally to 76.50 (p-value = 0.616). Investigators also evaluated differences in safety climate between the company’s three major divisions (operations, maintenance, and administration). Both years administration had the highest mean score and operations had the lowest mean score. The authors attributed the statistically significant differences found among the three major divisions to various dissimilarities in their work environments.

Aug 13, 2021

By Greg J. Hasenfus, Allison M. Haines, Joshua M. Silvis

The floodable volume of longwall gob can be of great importance in developing accurate coal mine operation plans, particularly for mine water management and environmental control strategies. Given the inaccessibility and difficulty in direct measurement of gob characteristics following gob recompression, hydrologic, geomechanical, and spatial data and principles were used to solve for the porosity and height of the residual gob using a mathematical model framework and bulking-based techniques. Based on this approach, gob porosity of Appalachian longwalls appears to be tighter than previously reported, ranging between 4.99 and 14.31%. Residual gob height, as normalized with respect to mine extraction height, ranges between 1.90 and 2.45. A novel, bedding-based bulking approach is ampliative with respect to existing roof caving and bulking fundamentals, as it has greater explanatory value compared with the traditional, lithologic-based bulking application. The efficacy of using the residual gob characteristics determined by the mathematical model and bedding-based bulking is examined using a causal comparative method, whereby time series prediction of historical groundwater rebound is compared with observed mine pool elevation data. Prediction accuracy is significantly improved using a prototype model to calculate void volume of longwall gob, specifically, the dependence of porosity of the gob material upon the longwall width to overburden depth ratio for movement basins of subcritical and critical panel widths. The potential implication of these findings toward hydrologic, geomechanical, and ventilation studies of longwall gob could be significant.

Aug 13, 2021

By Shahab Alizadeh, Ahmad Khodadadi Darban, Mehdi Mohseni, Mahmoud Abdollahy

This study probed the selective separation of lanthanum and yttrium in a nitrate medium in the presence of aluminum and calcium impurities using di-(2-ethylhexyl) phosphoric acid (D2EHPA). The factors studied in a central composite design (CCD) included extractant concentration, pH, concentration ratio of total impurities to rare earth elements, and interaction of these three factors. The extraction mechanism and types of extracted metal-containing species were delineated by the slope analysis method. The obtained thermodynamic data showed that lanthanum and yttrium extraction by the D2EHPA extractant was exothermic. The extraction of both rare earth elements was accompanied by an entropy reduction. The negative magnitude of ΔS in yttrium extraction reaction suggests stronger D2EHPA-Y(III) complexation relative to La(III). As entropy decreased and enthalpy increased, the extraction process became unspontaneous. Using the proposed flowsheet, lanthanum and yttrium products with > 90% purity were obtained.

Aug 10, 2021

By B. P. Watson, D. P. Roberts, R. A. Lamos

The Upper Group 2 (UG2) chromitite reef is a shallow-dipping stratiform tabular orebody in the South African Bushveld Complex, which strikes for hundreds of kilometres. Mining is extensive, with depths ranging from close-to-surface to 2 500 m. Pillars are widely used to support the open stopes and bords. Little work has been done in the past to determine the strength of pillars on the UG2 Reef and design was done using formulae developed for other hard-rock mines. This has led to oversized pillars with consequent sterilization of ore. In this paper we describe a back-analysis of stable and failed UG2 pillars on the Bushveld platinum mines, and provides a strength formula for UG2 pillars. The formula may be used cautiously on all Bushveld platinum mines with similar geotechnical, geometrical, and geomechanical conditions to the pillars in the database.

Aug 1, 2021

By T. E. Oates, W. Spiteri

In 2015, after amendments to the explosives regulations, stemming became a mandatory activity for all South African mining operations. There are, however, circumstances in which it is thought stemming has an adverse impact on the blasting outcome. Some of these circumstances include blasting in hot holes, in reactive ground, or when blasting a pre-split. In order to determine when stemming is necessary, its role in the control of adverse blasting phenomena and impact on explosive performance were reviewed. Stemming was found to play a significant role in the fragmentation process and burden movement. Additionally, stemming significantly influences the control of flyrock, air-blast, and toxic fume generation. The review of the literature indicates some motivation for not using stemming for presplit, trim, hot hole, and reactive ground blasting, provided the benefits associated with not stemming the holes outweigh the risks of stemming them. Best practice for stemming from the literature indicates a stemming length of 0.7 × burden is best for larger hole diameters, and 20 to 30 × Ø for smaller hole diameters. Crushed aggregate appears to be the most effective stemming material. The South African explosives regulations pertaining to stemming were found to be consistent with those of Australia and the USA.

Aug 1, 2021

By B. P. Watson, A. Carpede, W. O. Kekana, N. Fernandes, W. Theron, M. P. Mahlangu, G. Betz

The research described in this paper was done to confirm the Upper Group 2 (UG2) PlatMine peak pillar strength formula (Watson et al., 2007), which was determined from a back-analysis of failed and unfailed pillars. Underground measurements were made on a stable pillar that was loaded by firstly reducing it’s length and then by mining the surrounding pillars until pillar failure took place. The pillar was instrumented with suitably positioned strain cells and closure meters, which allowed both the average pillar stress and strain to be determined. The paper describes the methodology applied to identify a suitable position for the instrumentation, as well as the results. A stress/strain curve is presented for a UG2 pillar with a w/h ratio of 2.0, at Booysendal Platinum Mine. The measured pillar strength was similar to the predicted strength using the PlatMine pillar strength formula for UG2 pillars. The PlatMine formula has been successfully implemented on Booysendal Platinum Mine, and about 3 670 pillars have been cut without a single failure. An additional revenue of US$1.3 billion was calculated for the 25-year life of the mine as a direct result of the improved pillar design, given the January 2020 platinum group metals basket price. An extended life of mine and better mining efficiencies will also be realized.

Aug 1, 2021