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By S. J. Taylor

The siting, grading and fill usage for leach pads are important aspects of leach pad design. A method is presented that optimizes the cut and fill quantities (i.e. minimizes the cost) required to grade a leach pad with parallel cells; given the desired pad characteristics of maximum and minimum pad slopes, maximum cut and fill depths, etc. and the cut and fill costs. The method allows the variation of the cut and fill costs with depth, which allows the accurate modeling of the cost savings practice of using cheaper fill towards the bottom of a thick fill. This optimization could be incorporated into a CAD package, enabling a designer to simply draw a desired pad shape on a site plan, input the pad and heap characteristics (required heap volume, heap height, heap sideslopes, etc.) and then have the computer report both the adequacy of the pad area and the optimum grading for the particular pad shape. Using this, a designer could quickly and accurately assess the optimum, or cheapest, grading of many shapes and positions for a leach pad. This would be especially useful for large pads that need to be sited on rough terrain.

Jan 1, 1996

By Gustavo G. Pilger, Jair C. Koppe, João Felipe C. L. Costa

Information for mine planning requires to be close spaced, if compared to the grid used for exploration and resource assessment. The additional samples collected during quasi-mining are frequently located in the same pattern of the original diamond drill holes net but closer spaced. This procedure is not the best in mathematical sense for selecting a location. The impact of an additional information to reduce the uncertainty about the parameter been modelled is not the same everywhere within the deposit. Some locations are more sensitive in reducing the local and global uncertainty than others. This study introduces a methodology to select additional sample locations based on stochastic simulation. The procedure takes into account data variability and their spatial location. Multiple equally probable models representing a geological attribute are generated via geostatistical simulation. These models share basically the same histogram and the same variogram obtained from the original dataset. At each block belonging to the model a value is obtained from the n simulations and their combination allows one to access local variability. Variability is measured using an uncertainty index proposed. This index was used to map zones of high variability. A value extracted from a given simulation is added to the original dataset from a zone identified as erratic in the previous maps. The process of adding samples and simulation is repeated and the benefit of the additional sample is evaluated. The contribution of an extra sample was evaluated locally, globally and in terms of variation in total measured resources. The procedure showed to be robust and theoretically sound, mapping zones where the additional information is most beneficial. A case study using coal seam thickness illustrates the method.

Jan 1, 2002

By M. David Monroe

Getting the best match between truck and haul road requires examining the cost effects of many factors. Most mines use a bottom line measure based on cost per ton of material moved. This measure focuses on the two components of truck haulage cost per ton: productivity (or performance) and operating cost. For specific tasks, productivity can be measured or predicted using either field measurement or modeling. Individual tasks can be combined to provide a larger scale, longer term net figure for total mine output. True cost is more difficult to capture. Factors are time- and task-oriented and can be influenced by a summation of factors over a truck's lifetime. For example, "allocated" costs, such as owning (depreciation) and some repair costs, are spread over long periods. Items such as fuel and tires can be tied more directly to certain tasks. This article focuses on the more direct, task-oriented factors that affect truck productivity and cost. Major factors The relationship of haul roads and trucks means that each must be examined separately to isolate the most important factors affecting performance and cost. There are many factors but the most important are:

Jan 1, 1992

By M. D. Monroe

Getting the best match between truck and haul road requires examination of many factors and their effect on the bottom line. Most mines use a bottom line measure based in some way on cost per ton of material moved. This measure focuses on the two components of truck haulage cost per ton: productivity (or performance) and operating cost. Productivity can be measured or predicted for specific tasks using either field measurement or modelling. Individual tasks can be combined to provide a larger scale, longer term net figure for total mine output. True cost is more difficult to capture as they are time and task oriented and can be influenced by a summation of factors over a truck lifetime. For example, "allocated" costs, such as owning (depreciation) and some repair costs, are spread over long periods of time. Other cost, such as fuel and tires can be tied more directly to certain tasks such as fuel and tire cost. This paper focuses on the more direct, task-oriented factors that affect truck productivity and cost.

Jan 1, 1992

By W. Morgan, D. Gove

In truck and shovel operations, productivity and cost per ton are influenced by the system matching choice, Optimization involves a balance of the size and number of trucks, the size and type of loading tool and the projected material conditions and haul roads. Caterpillar has updated its Fleet Production and Cost program so miners can more easily look at matching choices and optimize on the variable they choose. This paper introduces the Fleet Production and Cost program. It then demonstrates its capabilities with examples of optimization. Mining operations that use trucks need to properly match the number and size of hauling units (trucks, wagons, scrapers, etc.) to a loading unit (wheel-loader, hydraulic shovel-excavator, cable shovel, push tractor, etc.) to provide the best possible fleet match. Optimizing fleet match minimizes the cost per unit of material moved by that fleet. As haul conditions change (haul length, grade or rolling resistance), there may be need to adjust the number of trucks to maintain the optimum fleet match. Fleet Production and Cost is a tool that can be used to optimize the truck-loader match.

Jan 1, 1995

By D. Gove

All mining operations using trucks have a common need to properly match the number and size of hauling units (trucks. wagons. scrapers. etc.) to a loading unit (wheel loader. hydraulic shovel/excavator, cable shovel. push tractor. etc.) to provide the best possible fleet match. Optimizing fleet match minimizes the cost per unit of material moved by that fleet. As haul conditions change (haul length. grade. or rolling resistance), there may be need to adjust the number of trucks to maintain the optimum fleet match. Fleet Production and Cost is a tool which, among other things, can be used to optimize the truck-loader match.

Jan 1, 1994

By Ajit Godbole, Ping Chang, Ramakrishna Morla, Purushotham Tukkaraja, Shivakumar Karekal

This paper presents the results of a study on the optimum auxiliary fan location to control air recirculation in dead-end workings where diesel-powered vehicles operate. Investigations were conducted with various secondary fan locations from the dead-end crosscut and with the intake air quantities varied using different auxiliary fans to control air recirculation and diesel particulate matter (DPM).

Jul 1, 2023

By Ajit Godbole, Ping Chang, Ramakrishna Morla, Purushotham Tukkaraja, Shivakumar Karekal

This paper presents the optimum auxiliary fan(s) location to control air recirculation in dead-end workings where dieselpowered vehicles operate. Investigations were conducted with various secondary fan locations from the dead-end crosscut with varying the intake air quantities using a 30 m3/ s capacity twin 75 kW auxiliary fan and 45 m3/ s capacity twin 110 kW auxiliary fan to control air recirculation and DPM. The results showed that if the drive intake airflow rate matches the fan capacity, air recirculation will occur even when the fan is located 10 m away from the crosscut entry. Results also showed that if the intake drive air quantity was greater than or equal to 150% of fan capacity, no recirculation was observed when the twin 75 kW fan location was at least 5 m and the twin 110 kW fan location was at least 10 m away from the dead-end crosscut access.

Oct 18, 2022

By Nilabjendu Ghosh, Satyendra Kumar Singh, Gautam Banerjee, Harshit Agrawal

High-production methods like longwall mining with hydraulic powered supports are necessary to increase underground coal production in India. Longwall mining had a mixed success record for Indian geo-mining conditions. In this paper, an analysis is presented to optimally design an array of chain pillars in multi-seam longwall mining panels in the deepest coal mine in India. The study found that a chain pillar of 80-m width and 195-m length is necessary for long-term stability without any reinforcement. It was also observed that an optimum chain pillar can be designed by providing suitable side reinforcement (side bolting) which will reduce the chain pillar dimensions to 55-m width and 160-m length. Optimum design of chain pillars will reduce the coal locked up in these chain pillars by ~ 77%. This will also reduce the gestation period of longwall mining panel development. This paper also evaluates the maximum tensile subsidence strain induced at the surface and finds that the values are within the safe working limit of 3 mm/m. Thus, this paper finds direct application in the design of future multi-seam retreating longwall mining panels in Indian geo-mining conditions.

By V. E. Cogho

Optimum Coal Mine comprises numerous defunct, active, and future mining sections. The mine is primarily a large opencast coal mine; however, underground mining activities will be increasing steadily over the next five years. Opencast and underground mining activities have a significant impact on surface and groundwater resources. To ensure that the mine will be able to continue with its mining operations in the catchment, the extent of this impact requires that substantial intervention and mitigation measures need to be implemented to ensure the environmental integrity and economic use of the catchment's water resources. In developing a sustainable long-term mine water management strategy, numerous scenarios had to be analysed. The various scenarios are a combination of water and land management activities. The main components of the mine's integrated water management strategy include: ? Management of water recharge by continual and appropriate rehabilitation of disturbed land ? Beneficial re-use of impacted mine water for coal plant process water and mining operations ? Reclamation and desalination of remaining excess impacted mine water to potable standard. From the mine's long-term water balance, it is evident that the continued implementation of numerous water management actions is required to mitigate the water resources impact in a sustainable manner. In addition, the installation of a water reclamation plant at Optimum Coal Mine (15Ml/day) is a key step for the mine to achieve a zero impact target.

Jan 1, 2012

By D. A. Phillips

A procedure for designing an optimum pit to yield maximum profit is described. The volume in which a possible pit is considered is divided into discrete blocks, each of which is assigned an economic value equivalent to its worth as a block of mineable material. The profitability of a pit can then be generated by summing the blocks within the pit. The optimizing procedure starts at the surface level and proceeds downwards level by level, to obtain the optimum pit at each level. The method makes use of the fact that an optimum pit at a particular level must be completely contained in any optimum pit at a lower level. Procedures for generating block costs, and pits with various slope angles under the restriction of complete block removal are considered briefly. The main description is of the theory of the method and the computer program based on this. The method is applicable to any type of mineral deposit, the only requirement being that the orebody should be represented accurately by a block model.

Jan 1, 2014

By S. J. Jung

The stability of underground openings for deep mines is critical, since incorrect orientation or geometry of shaft, stope, and accessways often results in the failure of openings due to high stress concentrations. Current state-of-the-art procedures for the design of underground openings are largely based on rules of thumb, experience, and trial and error. Rules of thumb are invariably based on the past experience of the designer and may not remain optimal as the depth and complexity of mine workings increase. Often, as conditions change, and as the interaction between geology, in-situ stress conditions, and mine openings grows more complex, the cost of maintaining structural integrity becomes prohibitive. Existing design procedures for deep mines are rapidly becoming inadequate as mines are worked at greater depths. For example, in the Coeur d' Alene Mining District, several million dollars are spent for inspection, repair, and maintenance on a regular schedule, largely as a result of inadequate design. In these types of situations, it is of critical importance that a new design methodology be developed for the layout and design of underground openings.

Jan 1, 1994

By Helmut Lerchs

An open-pit mining operation can be viewed as a process by which the open surface of a mine is continuously deformed. The planning of a mining program involves the design of the final shape of this open surface. The approach developed in this paper is based on the following assumptions: 1. the type of material its mine value and its extraction cost is given for each point; 2. restrictions on the geometry of the pit are specified (surface boundaries and maximum allowable wall slopes); 3. The objective is to maximize total profit-total mine value of material extracted minus total extraction cost. Two numeric methods are proposed: A simple dynamic programming algorithm for the two-dimensional pit (or a single vertical section of a mine), and. a more elaborate graph algorithm for the general three-dimensional pit. ASURFACE mining program is a complex operation that may extend over many years, and Involve huge capital expenditures and risk. Before undertaking such an operation, it must be known what ore there is to be mined

Jan 1, 1965

By I Treloar, T Elenbaas, E Isaaks

Critical reviews of grade control generally focus on blasthole sampling and the estimation of ore control block model (OCM) grades, with little or no attention given to dig-line design. For example, the estimation of block grades is deemed important as estimation errors lead to the misclassification of ore types and subsequent dollar loss. Recognition of the problem that the underestimation of block grades may be more or less costly than overestimation led to the application of loss functions to the classification of individual OCM blocks by ore type. The method is known as maximum profit selection (MPS). However, each OCM block may be misclassified a second time by dig-line design. Although each block may initially be assigned an optimum ore type by MPS, OCM blocks are seldom individually mineable by ore type. As a result, a common solution to this problem is the design of mineable polygons or dig lines loosely constrained by a minimum mining width. All material within a properly designed dig-line polygon can be mined and sent to a single destination such as the mill, stockpile or waste dump. These dig lines are often designed manually or by simple variations of computer-generated contour lines. They are generally suboptimal and result in additional misclassifications of ore types. This paper provides an algorithm for constrained optimum dig-line design where dig-line misclassifications are also evaluated through loss functions or MPS. Constrained optimum dig-line designs minimise the dollars lost by dig line misclassifications for a given minimum mining width constraint. A case study is provided illustrating constrained optimum dig-line design and subsequent benefits.CITATION:Isaaks, E, Treloar, I and Elenbaas, T, 2014. Optimum dig lines for open pit grade control, in Proceedings Ninth International Mining Geology Conference 2014 , pp 425–432 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

In some 35 years in the explosive and construction industries, we have probably seen the extremes in drilling and blasting practices. All of you know that it is difficult if not impossible, to separate those two operations, particularly when we are searching for an optimum. Early in my career while doing engineering survey work for a major cross country pipeline construction company, we witnessed some of the wildest blasts imaginable, and they were wild for two reasons. Both the drill hole diameter and the drill pattern were such that when loaded with explosives, the factor in terms of pounds/cu. yd. was extremely high. On the other hand, in 1982 we were in an underground coal mine where just one hole was used to prepare a 20-ft. (6m) wide face. In this coal mine, they brought down 7 yd3 (5.35m3) of coal with just 1 lb. (.454 kg) of explosive. On a pipeline job, the factor may only be .1 yd3 per lb. of explosives. Open pit operations in the same geographical area may have almost the same type of rock, but similarities could end there. The several operators over the years will have installed different size-crushing equipment or variances will exist in other facets such as drilling, excavating, and haulage units. That tells us that if we have 6 operations in that common area, we are faced with a fact that there is an optimum drilling and blasting pattern for each of those six. We start at that point. We will note from Figure No. 2 the simple equations for determining either cu. yds. or tons. For a rock heavier than limestone, it may require only 10 to 11 cu. ft. (.31m3) for 1 ton (.91 metric ton) of rock in place.

Jan 1, 1986

By A Fyans, B Ghahreman-Nejad

This paper discusses the method and results of an options study into selection of the optimal form for a 130 m high tailings/water retaining dam, located in a region of high seismicity in central Iran. The proposed dam is part of a planned expansion project for Sarcheshmeh Copper Mine (SCM), which after construction will provide 550 million tonnes of additional tailings storage over the next 27 years. Geotechnical investigation at the proposed site indicated that adequate suitable low permeability materials (i.e. clay) were not available in the immediate vicinity of the dam site and would need to be imported from a distance of well over 10 km (direct). Given the magnitude of the estimated quantity of material and construction cost it was considered prudent to compare the cost of alternative dam design options for the proposed storage. A total of five dam design options are considered including a conventional rockfill embankment dam with an upstream sloping earth core (ECRD), a geomembrane face rockfill embankment dam (GFRD), a sloping asphalt core rockfill embankment dam (ACRD), a roller compacted concrete dam (RCCD), and a filter rockfill embankment dam for tailings storage together with a separate smaller earthfill core rockfill dam (ECRD) located downstream for storage of decant water. The risks, costing and design of all options are discussed in detail and the outcome of the study is presented.CITATION:Ghahreman-Nejad, B and Fyans, A, 2018. Optimum embankment design for a tailings dam, in Proceedings Mine Waste and Tailings Stewardship Conference 2018, pp 427–438 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 23, 2018

By Jyri Talja, Shaolong Chen, Hannu Mansikkaviita

"For optimum smelting results, proper treatment of the feed is needed to ensure favourable conditions for ignition characteristics, heat balance, mass balance with tolerable impurity levels, and overall process economics. Feed preparation consists of physical treatments before drying (blending), chemical treatments before drying, (roasting, if required), drying itself and physical treatments after drying (fractioning, if required).Effects of fluctuation on mineralogy and moisture should be minimized by blending the concentrates in a bedding plant prior to drying. As an alternative to drying, additional treatments such as roasting for impurity removal may be needed for part of the concentrate.Sustainability, energy efficiency, utilization of waste energy, low gas and dust emissions, product quality, availability and occupational exposure reduction are decisive criteria in drying today. These criteria are best met by the Kumera steam dryer, which has the best energy efficiency, zero CO2 emission, lowest operational and maintenance expenses, and superior availability and product quality.IntroductionFeed preparation plays a crucial role in having a smooth smelting operation and also the overall smelting economics in metal production. Therefore, it is of significant importance for all copper, nickel and lead smelter operations in which sulphide concentrates are fed to the primary smelting furnace. Generally speaking, the higher the metal content in the matte after primary smelting, the more important the feed preparation. This is of particular importance in the direct blister (DB) process for copper production and direct oxygen nickel (DON) for nickel production.Bedding is the first stage in feed preparation. This is very important for the sake of smoothing the mineralogical fluctuation in the feed for better smelting control. Its importance increases as the number of concentrates available for the feed mix decreases."

Jan 1, 2012

By Sebastian Avalos, Julian M. Ortiz

The long-term mine scheduling is the optimal decision on how to extract and process the mining reserves. The resulting plan is mainly driven by economic, metallurgical, and geological factors. Accounting for their uncertainties leads to a robust solution and the feasibility for economic-risk quantification. In this work, we model the spatial uncertainty of grade distributions of multiple correlated elements, by using a multivariate morphing transformation. The result is a set of multivariate geostatistical realizations of the grades, which honor the conditioning data, the direct and cross variograms, and the multivariate statistical distribution, inferred from a set of samples. These models are the input in a reinforcement learning framework, adopted to train a deep neural network that considers the grade uncertainty and leads to an optimum mine plan after training using deep Q-Learning. Mining and processing capacities, as well as economic parameters and metallurgical constraints, are incorporated as the reinforcement learning environment rules. The method is validated on a real deposit, providing insights for future applications.

Jun 25, 2023

By M. A. Usman, E. I. Akpan, S. O. Adeosun

Preliminary studies on the extraction and characterisation of biodegradable lignin from palm oil fruitbunch (POFB) for carbon fibre production has been conducted. Centra lComposite Design was used to determine the optimum operating conditions for maximum yield and properties of the extracted lignin. Soda concentration (1–3 wt/vol%), temperature (50–90 °C) and reaction time (20–30 min) were analysed using Rcore software. Experimental results show that using reaction temperature of 90 °C, time of 30 min and 3 wt/vol% soda concentration yields 3.3 g of lignin from 30 g of the POFB. The path of steepest ascent from ridge analysis shows that with temperature of 130 °C, time of 40 min. and soda concentration of 3. wt/vol%, 8.7 g of lignin can be extracted from 30 g of POFB. Analysis of FTIR and SEM show that the lignin has the same structure in all cases with minimal impurities.

Mar 1, 2017

By S. Abu-Samra

By virtue of its complex nature, the construction industry comprises a wide spectrum of interrelated variables and factors. This multifaceted character of the construction industry puts the use of engineering modeling tools and techniques on top of project management necessities. This research introduces a macro-level earthmoving management system using Genetic Algorithms (GAs) to reach the optimum allocation of earthmoving equipment. The Earthmoving Equipment Management System (EEMS) functions through four integrated modules: (1) A Central Database containing information about projects and available equipment; (2) An Equipment per Segment Selection module that calculates the cut and fill quantities, plots the Mass Haul Diagrams, and selects the equipment types to be used for each segment; (3) An Equipment Pool module which determines the production and cost for each available equipment, based upon the project site conditions; and (4) An Optimization Engine equipped with a GA optimization solver. This engine formulates the optimum earthmoving cost for all projects, by changing the number of allocated equipment. The Optimization Engine takes into account the number of available equipment and calculates the weekly equipment allocation. The EEMS model was implemented on an earthmoving company conducting five different projects on hand. The model proved to be an effective tool in providing decision makers with optimum equipment utilization on a multi-project scale to minimize the earthmoving cost. The results were then compared with the company?s existing micro-level management system, demonstrating better performance on the level of savings, amounting to 13% of total earthmoving cost.

Aug 1, 2013