MINING UNDERGROUND AND ABOVE GROUND OPERATIONS: PRINCIPLES, TECHNOLOGIES AND INDUSTRIAL PRACTICE

This paper describes a model that compares Autonomous Haulage Trucks (AHT) to a manual one by estimating benchmarked Key Performance Indicators (KPIs) such as productivity, safety, breakdown frequencies, maintenance and labour costs, fuel consumption, tire wear, and cycle times. The model uses a deterministic approach to model truck movement in an open pit and stochastic simulation to account for different events such as dumping, loading, queuing, breakdowns, downtime, and shift changes. The required data for vehicle motion include speed-rimpull characteristics of a mining truck together with the specifications of haul road profiles such as section length, maximum speed, maximum acceleration, and road resistance. Fuzzy logic has been used to model traction coefficients and rolling resistances in order to study the effect of these variables on the performance of an AHT compared to a manual one. The model extends conventional shovel/truck simulation into a variety of truck sub-systems such as controller systems, sensors, system communication and data collection, fuel consumption and tire wear to capture the mechanical complexities and physical interactions of these sub-systems with the mine environment on a 24/7 time basis. These sub-systems in the manual haulage case are constrained by driver performance which changes according to experience, personality, stress, and fatigue levels. Time in the shift and time during a work period also have major roles that affect performance. By studying different driver behaviours, the variances can be captured, studied, and used to validate the model. As a result, the “optimum driver” can be defined and set as input to model an AHT fleet. Running these two models in identical scenarios allow comparison of benchmarked KPIs, that can demonstrate the adaptability and utilization of an AHT.

This paper discusses a practical method, to measure 3-D rock movement due to blasting, using Blast Movement Measurement (BMM) transmitters which are activated, programmed and installed in drill holes prior to the blast and a detector locates the transmitters after the blast. The BMM software then calculates and summarizes the movement of each BMM ball. This information helps to redefine the ore and waste boundaries and enables improved ore and waste selection, resulting in a genuine step change in grade control.

Copper sulfides formed in micro electrical connections are very observed frequently in manufacturing areas of the electronics industry in arid and marine environments as whiskers or dendrites. This is generated by drastic variations of relative humidity (RH) and temperature levels in indoor of these industrial plants, which originates the corrosion phenomena and the deterioration and deformation of electrical ways where are conducted the electrical current of Micro Electromechanical Systems (MEMS). MEMS are fabricated in isolated and clean rooms of the electronics industry where are strict rules with specific for the control of microclimates to avoid the corrosion process. In these rooms there are filters with high control to detect diminutive and finite particles and gases which promote the electrochemical process. This added to the severe changes in some periods of the year, of humidity and temperature in outdoor of companies, affect the microclimates of the clean rooms, originating the condensation, which generates the visible or invisible thin films in the copper surfaces of micro electrical connections of MEMS and causing the corrosion. For this reason a study of characterization of sulfur compounds was made to identify the type of corrosion process generated with the climatic factors mentioned, and with the concentration levels of sulfurs that penetrate by holes and air condition systems principally to indoor of the electronics industry. This research shows results of the uniform corrosion in marine zones as in the cities of Tijuana and Ensenada and the pitting corrosion in arid environments as the Mexicali city. The technique used to analyze the copper sulfides as corrosion products was the Scanning Electron Microscopy (SEM) with information organized in graphs and tables and also a MatLab simulation was made to determine in a short future the corrosion rate of this electrochemical phenomenon to measure the grade of deterioration of the MEMS connections and have the precaution necessary to prevent the corrosion process.

There have been several attempts of coal mining automation during the last decades to improve safety and productivity. One important method in underground coal mining is the longwall mining, where the main equipment includes the shields for roof support, the armed face conveyer to remove the cut coal and the shearer or plow as exploitation machine. The horizon control, to keep the longwall workface in the seam, and the shearer positioning are still critical points in automation and also focus of the researches during the last years. Thus, coal interface detection and automation of the cutting process are two main topics. Almost all of the researches in longwall mining automation are focused on the shearer or the roof supports separately. The shield-data-based horizon control (SDHC) is a new control approach in longwall coal mining which includes the roof supports as well as the automation of the mining machine. Therefore the roof supports are used as a source to carry data about the seam. These data are used by the controller to calculate the new cutting adjustments for the exploitation machine The aim of the SDHC is to achieve an automatic cutting drum high adjustment for the shearer on the basis of the seam data delivered by the roof supports to provide an autonomous mode even if the seam direction changes. This article contains the basics and difficulties of the control concept including a short introduction to the simulation model as well as the scheme and the description of the shield-data-based horizon control. Some simulation results will be shown, as well as results of the experimental tests, in cooperation with the German mining company Ruhrkohle AG with whom the controller was developed.

Truck dispatching is an important issue to be tackled in the Open-Pit Mining Area because of the costs of material transportation, which can represent up to 60% of operating expenditure in realistic settings. The problem usually involves a truck dispatching system in which decisions on truck assignments and destinations are taken in real-time. The dispatch is usually done in a mine with many trucks working together to achieve a common goal, which can be the maximization of transported material in the end of the shift. This task is held in a stochastic environment with a lot of uncertainties, such as, quantity of transported material, size of truck queues formed in shovels and crushers, and involved times in the system. The shift change, which involves time, is a critical issue to be addressed in truck dispatching. It is very hard to preview with certainty when a truck must stop to change the driver, because, in most of the cases, there is time to remain working, but queues and/or distances may imply in delays and overtime pay. Thus, it is very important to define when the shift change must occur, even when it implies in idleness. This work presents a decision making methodology based on Time-dependent Markov Decision Process (TiMDP) to minimize the shift change problem in a stochastic example mining with 15 trucks, 3 shovels, and 1 crusher. The system is modeled and simulated in SimEvents® showing its performance in the shift change problem.

Hybrid Electric Vehicles improve fuel economy by taking advantage of the Internal Combustion Engine (ICE) peak efficiency operating envelope and using an energy storage system to supply drive power when the ICE has lower efficiency. To achieve this, a hybrid design requires an ICE, a generator/motor, motor controllers, and an electric energy storage system (battery) which can be connected-up in a variety of ways such as series and parallel hybrid systems. Hybrid control has been typically implemented by creating a cost function for using fuel or the stored electricity based on battery state of charge, driver torque demand, vehicle speed, and transmission gear. For example, as the state of charge of the battery decreases, it becomes more costly to use the electricity and hence the control system tends to transition the power source from battery to fuel. There are examples of haulage trucks implemented with hybrid-electric systems although energy storage has not been featured. These systems are typically arranged in a series configuration where the engine is completely decoupled from the wheels and used to provide electric power through a generator which in turn powers the electric drive motors on the wheels. The absence of a battery presents missed opportunities for fuel economy improvements through regenerative breaking and engine off operation. This paper discusses the fuel economy question with respect to road geometry data and future speeds, a condition that can be determined for autonomous haulage system with relative ease. Real-time access to such data provides for representative and accurate cost functions. With a look-a-head system, even if the state of charge is low, the system can continue to use the electric system if a downhill stretch is known to be present up-ahead so the system knows it can charge-up using regenerative breaking.

Elemental analysis of ore samples is an essential part of many mining and minerals processing activities. In exploration and orebody delineation drill cores are typically studied. Normally the cores are first manually analyzed by the mine geologists, and then submitted to a laboratory for a more specific assaying. For the analysis process the cores need to be first halved, crushed and grinded, which requires relatively much manual labour and the whole process may take several months. This delay can hinder the exploration work and cause unnecessary drillings that could be avoided if the drill cores were analyzed faster. In this paper, laser-induced breakdown spectroscopy (LIBS) is studied as a potential rapid on-line method for automated elemental analysis of drill cores. The method is based on a pulsed laser beam that is directed on a small surface area of the drill core. The laser pulse causes a small volume of the sample surface to transform into plasma. Individual elements in the plasma have characteristic emission patterns detectable by a spectrometer. Based on the measured spectra the amount of different elements in the sample can be estimated. Drill core samples from a nickel-copper-PGE mine and from a gold mine in Finland are used as test cases in this study. The LIBS measurements are compared to laboratory analysis results as well as to fast on-line XRF scanning results. It is shown that the LIBS method can produce similar elemental concentrations as the other methods. However, the spot size of the lIBS measurement is very small (in micrometer scale), meaning that a large number of measurements must be taken to reach a representative sampling result for large drill core volumes. On the other hand, high spatial resolution is easily achieved.

Automatic control assistance to improve the digging and bucket-filling trajectory of loading excavators is moving from concept to industrial applications. Directly controlling the path of the bucket instead of controlling individual hydraulic joints by human operators is possible using robotics. The task may be achieved by re-defining the excavator kinematics and enhancing it with a software-controlled "virtual kinematics." It is necessary to determine what type of kinematics transformation of the excavator would be best from its “as-built” motion pattern to an “as-desired” machine for the loading tasks. If known, this loading kinematics then can be programmed into the machine motion control system. Since no loading movement and bite is exactly the same as the previous one, a man-machine interface is needed for easy access for adjustment. Such loading tasks are analyzed for cycle time, energy consumption, and machine wear. Static and dynamic forces, torques, energy, and power consumption is evaluated for any given digging bucket trajectory for an EX3500 Hitachi excavator. Typical digging trajectories from published data are used to evaluate the potential benefits of a new bucket loading kinematics by “bucket steering, ” a motion kinematics which requires two joysticks control actions only. One joystick serves for interactive adjustment to the trajectory shape, and the other is for loading velocity control. The paper describes the potential benefit to mining front shovel operations.

Mining activity carries inherent risks in its work. These risks have produced many accidents in Chilean and all mining history, some of them with fatal consequences. Does the state and the environment of the mine affect workers performance and security? Do long periods without accidents generate overconfidence in workers? Do recent accidents generate insecurity in workers? These type of questions sought to be answered by the Chilean consultancy SolMat using mathematical modeling to generate a computational tool that will allow to anticipate the occurrence of accidents in order to improve the safety of workers in Minera Los Pelambres. This paper generates and validates predictive models for daily and weekly prediction of accidents in all productive sectors as one large sector, and on a segmentation of the whole productive place into three specific sectors. Solmat used Machine Learning techniques with supervised training, obtaining with independent testing bases results of 70% of total accuracy for the job, and 75%, 85% and 75% of accuracy for the 3 previous segmentations, being able to detect more than the half of accidents in each case. For the daily case, accuracy is similar, but with less accident detection.

The Lion Cave in Swaziland, with over 100,000 tonnes of hematite mined from pre-historic times (40,000 – 100,000 years ago) seems to award mining the title of the oldest industry on earth. Yet, methods of mining changed slowly until the beginning of the 20th century, with accelerated change in the last 30 years. This has resulted in a transformation of the industry. Productivity, efficiency and safety are driving the industry to become more productive and cost effective. Within the next 10-15 years it will achieve increased productivity by 100 to 500%, depending on the commodity. With the advance of computerized applications to geo-modeling, planning, execution and results reporting, the rapid introduction of automated, (smart) equipment, and remote control of operations, mining is becoming increasingly capital intensive. As such, it will experience a tendency to erode the promised cost effectiveness, and cost savings, unless effective management tools are utilized. This presentation will address the introduction of automated and remotely controlled equipment in both underground and surface mining. It will examine the successful implementation of new technology in ore sorting, in pit crushing, and metallurgical extraction methods, all designed to focus costs of operation to the most productive and profitable activity. It will examine the advances of inter and intra mine communication of production and financial data exchange and analysis with the home office, vendors and customers. The paper will present enhancements to supply chain management that reduce costs in energy utilization, equipment utilization, and transportation, which enhance sustainability and profitability. Lawrence LienUnited Finance and Management Services

The simulation of haulage systems can be used for carrying out their optimization by analyzing the anticipated performance of the system under wide range of operational conditions. It can also be used for designing new haulage systems or retrofitting old ones. There are a number of commercial simulators that have been used to simulate this type of systems; Such as Arena, AutoMod, Witness, SimCad, SimMine, Flexsim, and SLAM. Even though these simulation environments are powerful and have demonstrated their usefulness in many mining applications, they are not flexible enough to integrate other tools; Such as optimization techniques, advanced data analysis and /or continuous processes. This work describes the main modules for simulating a haulage system using a general-purpose event simulator such as SimEvent. The models of the main equipments involved in a haulage system are described in terms of their parameters and internal structure. These models consider both operation and maintenance parameters, and they are collected in a library called MinToolbox. In order to validate the simulations of these models, the simulation of a prototypical operation using both MinToolbox and Arena is carried out. The results demonstrate that the MinToolbox model obtain consistent results compared with Arena, but it has potential to be seamlessly integrated with continuous operations; Such as crushing and grinding and other toolboxes for optimization and analysis. MinToolbox will be used to test real-time strategies for real-time control of haulage systems, integrating different processes at operational level, interfacing through OPC servers to different systems such as real-time databases.

A development and field testing program was undertaken for an improved aqueous coalescer for produced water; Oily water; And electrolyte and raffinate streams. The achievement of such a program would provide low cost and effective coalescence of entrained organic that would improve the performance of subsequent dual-media filters and on raffinate provide for a stand-alone solution. The desired goals as a pre-treatment to dual-media filters are 1) improve final effluent quality, 2) reduce backwash frequency of the filters, and 3) provide a more easily recovered organic then the reprocessing of backwash electrolyte or water. The system was shown capable of operating at pressures under 140 kPa and obtained entrained organic removal of up to 95%. The low operating pressures allow for lower capital costs and the ability to treat entire raffinate streams previously not feasible due to extremely high capital and operating costs. This paper will discuss the design and basic operational considerations of this improved coalescer and how it can be applied to new construction as well as operating plants. A unique feature will be discussed as how the coalescer can be incorporated into existing dual-media filters to significantly improve organic removal, extend service runs, and reduce backwashing frequency.

Raman analysis is a well-established method for analysis of different mineral compositions in ores. Raman spectroscopy is based on Raman scattering of light by a material. This scattering causes shifts in wavelength, which can then be used to deduce information about the material. Raman analysis has been used in ore analysis in many parts of the world. In this study, Raman spectroscopy is tested as a method for rapid and contactless on-line mineral analysis. Especially the fast detection of minerals from drill cores could be used as on-site method of analysis, enabling more cost-efficient solutions to mineral exploration. This paper deals with optimisation algorithms for mineral detection using Raman analysis. Paper establishes different optimisation schemes and discusses optimization algorithms used. The objective of the optimisation schemes is to find the combination of reference Raman spectra that best matches the measured spectrum of a given sample. Raman analysis was conducted on rock drill cores gathered from two mines: Agnico-Eagle Mines, Kittilä Finland; and First Quantum Minerals Ltd, Kevitsa Finland. A Laser operating at 532 nm and with power of 100 mW was used for Raman measurements. Analysis of Raman spectra was done by using ready-made libraries of RRUFF-project (http://rruff.info). Library data was compared to measured data on wave numbers 180-1288 (1/cm). Nonlinear optimisation was used to combine linearly the reference spectra to produce spectra of samples with many different minerals. Nonlinear optimisation was used because the sample spectra displayed a property of having multiple reference spectra merged together. In order to compose a linear combination of reference spectra which better matched the given sample spectrum, readymade Matlab optimisation algorithms were used. Optimisation minimised the distance of either real points or scores formed by Principal Component Analysis (PCA), when the reference spectra and the sample spectrum were compared. As a result, it was found that nonlinear optimisation is able to discern useful information for the user. Nonlinear algorithm is able to discern two or more minerals from a given sample. Using Nonnegative least squares was found to be the most simple and efficient way to solve for combination of reference spectra to form the sample spectrum studied. Using absolute values and not squares in the cost function was found to produce small but significant difference in the results.

Automation and quality control within all stages of the extraction processes have been of increasing significance in mining and the mineral processing industry. Especially the ever growing importance of sustainability has led the field of research and development to new innovations, especially in sensor technologies. One of the latest major innovations of the Institute for Mining and Metallurgy Machinery (IMR) is the adaption of a laser-induced breakdown spectrometer (LIBS) into the harsh conditions of surface mines. Usually working in the clean environment of laboratories, a compact analyzer consisting of a laser system and a spectrometer was developed to work in harsh environments which are affected by dust, mist, vibration and shock. A comprehensive set of test series verifies the feasibility of applying LIBS for enabling a real-time modeling and exploration of quarry stone deposits, as well as improving the quality control of recovered materials by applying a LIBS analyzer on a drill rig. This project was conducted by IMR and Fraunhofer Institute for Laser Technology at RWTH Aachen University as a cooperation project. LIBS is a contact-free method for determining the elements contained in a sample. By generating plasma with a laser beam on the sample’s surface, the surface in the focus of the laser vaporizes and emits light in characteristic wavelengths which are unique for every element. Now, IMR is working on adjusting this laser system to underground conditions which are aggravated by the possibilities of methane explosions such as in hard coal mines. By applying LIBS as a method for real-time identification of coal roof and coalbed, the extraction of coal can be automatized by utilizing the obtained information from the analysis. The key objective for this application is an increased productivity and hence the overall profitability by decreasing the overall throughput of waste material which is harder than coal itself and thereby reducing the operating costs through reducing the wear of the equipment and the increased operation safety by avoiding operators in the hazardous zones. By optimizing the utilization of the deposits and the resources, the sustainability of a mine can be increased. This project focusses on the conception of the enclosure and it is sampling for LIBS analysis and it is funded by the German Research Foundation (DFG).

One of the main concerns of the actual mining industry is the reduction of energy consumption. The mine ventilation and temperature regulation systems are accredited as much as 50% of the energy consumption of the underground mining process. The ventilation systems provide a healthy and safe environment for the operations inside the mine. The most common ventilation control systems for underground mine operations are decentralized with simple control actions, making the optimization of the whole ventilation system energy consumption more complex. Consequently, we propose a Model Predictive Control (MPC) strategy to handle the energy consumption of the mine ventilation systems, maintaining the oxygen, toxic, and the flammable gases on an acceptable range for a safe operation inside the mine. The MPC approach shows a centralized solution and it is compared through simulation with a developed non centralized Expert System, showing that the actual control systems for mine ventilation can be substituted by more complex control (as MPC) to manage the energy consumption and preserve a safe operation inside the mine.

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