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By M. Narasimha

The flow in a hydrocyclone classifier is highly turbulent complex nature of multi-phase structure, which has led designers to rely on empirical mathematical models for predicting the performance. A number of classifying cyclone models have been developed and successfully used in mineral comminution circuit simulators over the past four decades (Plitt, 1976 and Nageswararao, 1978). However, most of the mathematical models currently available to describe hydrocyclone classifier performance are based on single average mineral density component behavior. In industrial comminution circuits, the feed to the cyclone composed of a mixture of particles of varying degrees of liberation and sizes. The behavior of multi-component particles in a hydrocyclone is poorly understood and unaccounted for in most of the mathematical model equations available in the literature. There is evidence from a number of experimental data sets indicating the significant influence of the multi-component particles on measured cyclone performance. A concept for modeling the performance of hydrocyclones based on multi-component behavior is proposed in this paper. A set of semi-empirical model equations for cut-size, sharpness of separation are presented and the corresponding model parameters evaluated from the measured data are given.

Sep 1, 2012

By G Wyartt

Systems such as Davey Bickford’s Daveytronic® SP blast initiation system and electronic detonators have been an integral part of drill and blast activities in Australia for over a decade, with the significant benefits of electronic blasting well documented. Since 2010 the Multiblast feature has been commercially available, which enables eight individual blast patterns (up to 1500 detonators each) to be blasted in the same firing window. Synchroblast has been in active operation since 2012, which allows a blast of up to 4500 detonators – either as a single blast pattern, or several smaller adjacent blast patterns – to be reliably initiated.Multiblast manages blasts separately but concurrently, allowing all blasts to conduct prefiring checks simultaneously from the firing point utilising only one remote blasting unit. Each blast can be selected and fired individually, in a sequence determined by the operator by scrolling through the colour display. Synchroblast automatically detects the blasting configuration, and manages all detonators as a single blast pattern. This simplifies the design and blasting processes for the mining operation.Multiblast and Synchroblast are routinely employed throughout Australia and globally in both open cut and underground operations, enabling optimal productivity due to increased blast volume and reduced operational downtime associated with blasting events.A number of case studies will be presented in this paper, detailing various mining operations that are consistently blasting in excess of 2500 detonators per blasting event as a part of standard drill and blast operations. Blasts over 3000 detonators are becoming more frequent as mine planning departments adapt to this operational capability and flexibility.CITATION:Wyartt, G, 2017. Multi and Synchroblasting – maximising operational productivity, in Proceedings Iron Ore 2017, pp 631–634 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 24, 2017

By T. Rasmussen, T. G. Jørgensen, T. Fischer, R. K. McLimans, C. Knudsen, D. Frei

Ilmenite-bearing paleo-beach deposits were discovered in Jylland, Denmark using a combination of Ground Penetrating Radar (GPR), portable X-ray fluorescence (XMET), bulk XRF analyses, Computer Controlled Scanning Electron Microscopy (CCSEM), and wire line logging. The Miocene-age paleo-beach deposits are located below a thin Quaternary cover in a region of very moderate relief and essentially no outcrop demanding unique approaches in exploration. Initially, an isopach map of the Quaternary is prepared from existing water well data. A geological model for likely occurrence of Miocene paleo-beach deposits is generated and the coincidence of thin Quaternary cover and potential paleo-beach deposits define targets for detailed exploration. The defined targets are traversed with GPR to identify paleo-beach structures which are then used to define a drilling program. This methodology located a paleo-barrier island at the Vorslunde location with more than 10% ilmenite in the sand. During the drilling process, the TiO2 and heavy mineral contents of the sand were logged every meter with a portable XRF unit (XMET) and subsequently calibrated more accurately by comparison to bulk XRF and CCSEM analyses for selected samples. The bulk XRF data also provided more complete compositional information. Insitu determination of geology, heavy mineral abundance, and corroboration of the XRF logging was done using wire line logs, a combination of spectral gamma and induction conductivity logs. Detailed characteristics (abundance, grain size, shape) and chemical composition of minerals was determined by the GEUS CCSEM methodology (Frei et al, this vol.). The average weight percent TiO2 for all Ti-minerals is 62%, 60% excluding rutile. That elevated TiO2 content (>> ilmenite stoichiometric value, ca. 50 %) indicates that ilmenite experienced an iron-leaching environment. The source of the sand deposit was investigated by dating contained zircon. The results show that the likely sources of zircon are in southern Norway and southwestern Sweden with common zircon ages of ca 1100 Ma. and 1500 Ma.

Jan 1, 2005

The Cutoff grade optimization is very critical to the open pit production scheduling. In case of single mineral deposits, algorithms have been developed for determining cutoff grade policy that maximizes the net present value (NPV) of yearly cash flows. For deter-mining the cutoff grade policy for projects with two minerals including stockpiles the problem becomes much more complex. The purpose of this paper is to present fundamentals of a generalized cutoff grade optimization algorithm that will maximize the NPV of a project subject to mining, milling, and marketing constraints. Benefits of the methodology developed are demonstrated on three different case studies.

Jan 1, 1997

"HPGRs operate in a wide array of applications in mining and minerals. These range from relatively coarse crushing of copper and gold ores at one end of the spectrum to the processing of fine iron ore pellet feed and fine industrial mineral products at the other. Traditionally these circuits involve the treatment of relatively moist materials in pre-grinding circuits; using single stage HPGRs in open circuit or as a closed circuit operation with screening or partial product recycle. More recently, HPGR is increasingly deployed in dry grinding in combination with air classification. The high throughput demonstrated by larger HPGRs has stretched the application towards coarser size reduction duties for a number of new projects. At the same time, the basic principle of inter-particle crushing for generating a product with a high fines proportion gives ground to investigate applying the technology further towards finished product duties. The advantages that HPGR brings are clear. Multi Stage grinding enables energy efficient size reduction across more of the comminution circuit. Primary HPGR serves for a coarse grinding duty, whereas a secondary HPGR is geared towards generating a fine product for downstream processing or even a finished product. This publication summarizes some of the features of staged HPGR circuits and discusses some examples of operating and projected applications.INTRODUCTION In most HPGR applications, the grinding units are used as a single process stage, either in open circuit, such as for pebble crushing [Rose 2002, Westermeyer 2000, Van der Meer 2015] or in closed circuit with classification [Van der Meer 2009, 2012] or product recycling [Van der Meer 2010]. Where a higher plant capacity is required, the HPGRs are commonly installed in multiple lines in a parallel arrangement [Parker 2005, Koski 201, Vanderbeek 2006]. HPGRs can take a wide range of feed size distributions, and grind this down to a product with a high fines content. In general view, there is a limit on the size reduction range that even an HPGR can provide. Grinding down from a very coarse ore (e.g. 70-100 mm) to a very fine product (e.g. 100 microns range) is stretching the ability of a single stage HPGR circuit. Fine grinding generally requires a classification stage that returns the classifier oversize to the head of the HPGR circuit. From one point of view, it can be demonstrated that when recycling a large proportion of fines and middlings back to the HPGR feed results in an effective feed with an overrepresentation of middlings and fines, which will eventually reduce the grinding efficiency and consequently result in an increased recirculation mass flow [Van der Meer 2014]. From another point of view the large recycling mass puts a strain or even a limit on the capacity of present-day conveyor capacity."

Jan 1, 2018

By D. Komljenovic, V. Kecojevic

Selection of the best possible truck type (model) is of crucial importance for the mine decision-makers. In this paper, authors contribute to the body of knowledge by developing a novel methodology for the selection of mining truck. Both the Coefficient of Technical Level (CTL) and Analytic Hierarchy Process (AHP) methods were used in this study. The CTL represents a mathematical function which takes into consideration the interrelations among the main technical parameters of mining trucks. The authors developed a hierarchical structure where both attribute categories and their importance, i.e. priority or weight in the selection process were determined. For each category, a number of sub-attributes and their priorities were assigned, and a pairwise comparison among them was performed using the AHP method. In the final part of the study, the CTL was integrated into the AHP and represents a holistic approach in the selection of mining trucks. A case study on 180 tonnes truck category offered by five manufacturers was carried out. A sensitivity study of obtained results was also performed indicating a very stable solution. The methodology presented in this paper may be used by mining operators to help in the selection of a specific type when acquiring a new truck. It may also be used by equipment manufacturers to help in analysis of potential benefits of envisaged modifications concerning an existing truck type and/or development of a new type.

Jan 1, 2007

By Tony Keller, Setsuo Maeda

Hand-Arm Vibration Syndrome (HAVS) was identified as early as 1918 in Bedford, Indiana in the U.S. Since then much research work has been done around the world in the areas of medical, epidemiological, engineering and legal aspects of HAVS. In Japan, much of the pioneering work in this field has been performed by Dr. Setsuo Maeda and his staff at the National Institute of Industrial Health (NIIH) in Kawasaki. Most recently, reports of work done by this group and by Dr. Ren Dong1 of NIOSH in the U.S., as well as many other suppliers and Japanese practitioners were presented at the 13th Japan Group Meeting on Human Response to Vibration held in Osaka2 during August 3-5, 2005. [ ]

Jan 6, 2006

By Dale Preece, Stephen Chung

Development of DMCBLAST-3D is continuing and now includes the capability to simulate the detonation of multiple blastholes in multiple rows that make up a conventional bench blast, either in a rock quarry or a surface coal mine. DMCBLAST-3D is a three-dimensional extension of the proven twodimensional rock blast modeling code, DMCBLAST. DMCBLAST has been under development since 1987 and has successfully predicted the physics, mechanisms and results of a number of different types of rock blasting including, coal mine bench blasting, mineral mine choke blasting and underground stope blasting. Substantial effort has gone into the qualification and verification of DMCBLAST by comparing computer code predictions with real blasts in the field. Comparison with field data has also provided significant guidance to the development of the code.

Jan 1, 2002

By P. Rambalee

A multiple coal fired boiler house provides steam for utility usage in various production plants. Maintaining stable header pressure and boiler availability is of critical importance for downstream consumers. Advanced Process Control comprising of a G2 based expert system and Model Predictive Control was implemented to improve the boiler house performance. The results yielded improvements in the main header pressure stability, reduction in boiler saturation and significant saving in coal consumption. All information used for this document is from a published whitepaper written and led by Prevlen Rambalee (Anglo Platinum) and Gustaf Gous (BluESP) titled, ?Control and Stabilization of a Multiple Boiler Plant: An APC Approach?.

Jan 1, 2012

A pilot scale AG milling campaign was conducted at the AngloAmerican Platinum pilot plant in South Africa. Different blends of hard:soft (silicate:chromite) and coarse:fine particles in the AG mill fresh feed were tested. The effects of multi-component feed on the pilot scale autogenous grinding are presented in this paper, and can be used as a guideline for multi-component feed blends for AG milling. Preliminary modelling and simulation for the multi-component AG mill model are also included.

Jan 1, 2012

By N. Plint, D. Philips, J. Sweet, B. Durant

A pilot scale AG milling campaign was conducted at the AngloAmerican Platinum pilot plant in South Africa. Different blends of hard: soft (silicate: chromite) and coarse: fine particles in the AG mill fresh feed were tested. The effects of multi-component feed on the pilot scale autogenous grinding are presented in this paper, and can be used as a guideline for multi-component feed blends for AG mil

Jan 1, 2012

By M. D. Dolan

In this study, the development of a new method for investigating the diffusion of metal cations in multi-component slag systems, using microprobe analysis is discussed. This method allows the analysis of the diffusion of multiple species within a single system. This project has focused on the diffusion characteristics of manganese, iron, calcium and silicon in silicate slags, in order to simulate industrial steel and ferromanganese production. The diffusion behaviour of transition metals is of particular interest because of the effects of their variable valence. This study identified the variation in diffusivity of slag components with changes in composition and temperature of multi-component slag systems. The molecular structure of the experimental calcium-aluminosilicate slags was investigated to determine the chemical and physical properties that influence diffusion behaviour. This experimental data was used to develop predictive models for diffusivity. These models enable the estimation of the diffusivity of many slag components in complex slags, over a range of compositions.

Jan 1, 2004

By Gordon A. Irons

"Powder injection for melt refining is widely practiced in the steel industry, and is gaining acceptance in the non-ferrous industries. In these commercially-important systems, the thermodynamics and kinetics may be very complicated. More than one element may be removed by refining, and often the refining agents are not just one compound. In this paper, the thermodynamic and kinetic aspects of these processes are reviewed. A number of examples are given, such as the desulphurization of iron with a variety of reagent mixtures, and selenium removal from copper with several different reagent combinations.IntroductionI am very pleased and honored to present a paper at this Symposium recognizing the many contributions of Professor Howard Womer. Even at the time I was an undergraduate student, the WORCRA process was part of the curriculum. I remember at the time that I was fascinated by the concept, and due to it and the many other rapid developments in Process Metallurgy, I chose it as my field of study. I think the Symposium is testimony that Professor Womer has touched the lives of many others as well.My original assignment was an overview of the basic aspects of gas and solids injection. However, I reviewed most of this material at the Savard/Lee Symposium [1]. In the present paper, I will present some of the basic issues related to refining with powder injection, using work that we have recently completed in both ferrous and non-ferrous systems."

Jan 1, 1996

By Wenbin Ma, Cees van Rhee, Dingena Schott

Since the concept of deep sea mining (DSM) was proposed by J. L. Mero with his book, The Mineral Resources of the Sea, in the 1960s, many research and significant developments have been implemented. However, its commercial mining process still has not yet commenced. One of the most important issues is that a sustainable DSM transport plan is difficult to determine, taking into consideration the DSM technological, economic, and environmental aspects simultaneously. The objective of this paper is to propose a method to determine the sustainable DSM transport plan utilizing a fuzzy analytic network process method, which is a typical multi-criteria decision making method (MCDM). The DSM transport plans evaluating major criteria consist of technological, economic, environmental, and social aspects with both qualitative and quantitative attributes. Different major criteria include several sub-criteria, respectively:  Technological aspect: energy consumption, proven technology, technology reliability, production rate, technology availability;  Economic aspect: gross income, capital cost, operation and maintenance cost, investment recovery period;  Environmental aspect: species disturbance variance, severity of ill effect, turbidity of ocean water, total organic carbon content, sedimentation thickness;  Social aspect: social acceptability, policy support; The weights for all evaluating criteria and sub-criteria are determined through a questionnaire survey interviewing experts at different research fields. All the transport plan candidates are ranked based on a comprehensive index. The conducted research in this paper is meaningful to promote the DSM commercialization process.

Jan 1, 2018

By J. Ga?parík

The optimal selection of machine or machine group for building processes is very important role of building planner during the process of building planning. During this process building planner have to analyze several factors influencing the final effective decision concerning this problem. There are several factors and criteria for effective selection of building machines. In our contribution there are analyzed: ability of machines to realize designed building process (quality aspect), duration of mechanized process (time aspect) and minimizing of energy consumption (cost and environmental aspect). Selected scientific methods and theories of problem solution can be divided into these groups: theory of system (creation of building machine selection method), multi-criteria optimizing method (analysis of mechanized building process from the point of more optimal criteria), queuing theory (application during the mathematical modeling of mechanized soil processes), method of scientific analysis (analysis of factors influencing final decisions), method of scientific synthesis (creation of optimizing method implemented into building processes and possible application in construction sector). Multi-criteria optimizing method were during our research work implemented into soil processes and selected building group machines (excavators and trucks), which are very often used in construction and mining processes. This method can be considered as a multi-level decision making process based on multiple parameters. In our contribution is presented key mathematical models for model example solution and software built in Java, which has been created as a support for method described in this contribution. Application of this method and software will increase the effectiveness of building machine selection from the point of key criteria of optimizing: quality, time and energy consumption.

Aug 1, 2013

By S Van Duin, I Porter

This paper discusses how advanced manufacturing technology (AMT), which is fundamentally reliant on and developed via multi-disciplinary skills, has benefitted non-mining industries, and what lessons can be derived from this experience to benefit the mining industry, particularly underground coal mining. Examples of AMT use in æconventionalÆ industry, some drawn from the more than 25 years experience in many different industries of the Automation and Robotics team at the University of Wollongong, are described to show typical benefits, risks and opportunities expected in using AMT. Applying AMT to mining brings many unique challenges and this paper expands on these and then provides practical examples of how a multi-disciplinary team can develop new processes and systems leading to productivity, safety and other benefits for underground coal mining.

Sep 26, 2011

By Brian E. Davies, Bobby G. Wixson

INTRODUCTION The impact of modern mining and ore processing on the environment is readily minimised. Our improving knowledge of how pollutants are released to and move through the environment has been accompanied by better expertise in controlling these emissions. For example, when the new mines and smelters were developed in the Viburnum Trend of Missouri a sulfur dioxide pollution problem was quickly recognized and soon controlled. (Wixson 1974) But older operations were not efficiently organized and, despite their smaller scale, they often caused major pollution problems. The British mining fields are among the world's oldest and during the heyday of their operation (approximately 1750-1900) they were worked with- out regard to their environmental impact. The Rivers Pollution Commissioners in the mid-nineteenth century were led to remark that ore dressing was carried on in a slovenly and wasteful manner and the complaints by farmers, that river borne mine wastes were poisoning both their crops and stock, were justified. (Frankland and Mortan, 1984). The Comissioners report led to the 1876 River Pollution Act of Parliament, the first modern environment protection legislation. The development of mining since the last century is characterized by improved regulation of the pollution potential of ore dressing, smelting and refining. The collective memory is unfortunately long and pessimistic. A serious problem arises when old mines are reopened especially if the mine has not been worked for several years since local action groups may soon blame the new owners for causing problems which, in reality, are longstanding and were caused by the use of earlier state of the art technology. It is therefore essential that during the early development stages prior to reopening that comprehensive studies be carried out to identify and quantify local contamination problems. These baseline studies should include surveys on the nature and composition of old tailings disposal areas and other wastes on the mine properties. The composition of air and water should be monitored. Soils are long term sinks for all heavy metals and particular attention should be paid to soils within any city areas near the mine since there are sources of heavy metals in urban areas which are not connected with mining and ore processing. This paper describes some of the results of such a study around a prospective cobalt mine in Southeastern Missouri. It is restricted to the soil survey of forest and agricultural land which took place in and around Fredericktown, Missouri. The city is located at approximately 37° 30' North and 90° 20' West and lies 143 kilometers south of St. Louis. There are several metal mines near Fredericktown, including Mine La Motte, which is the oldest and was first opened in 1720. [Figure 1] is a location map of the area. The survey described here was in connection to the reopening of the Madison Cobalt Mine which was first worked in 1947.

Jan 1, 1985

By Pamela Castillo, Marcia Muñoz, Rodrigo Luca, Brian Townley, Fernando López

In the present study we discuss the value of multi-element geochemistry as a tool for semi-quantitative to quantitative bulk mineral characterization in geological and geo-metallurgical modeling of porphyry copper type deposits, with an emphasis on hydrothermal alteration associations, types and intensities. In mine production of porphyry copper deposits much effort is placed on ore grade and geological modeling, applied for predictive mineral processing behavior, from blasting, grinding, leaching or flotation, down to waste disposal and environmental management. High confidence geological models are commonly based on geological mapping of drill core and surface/ underground exposures, combined with discrete mineral characterization (e.g., petrography, QEMSCAN®, spectroscopy, etc.). Unfortunately these are expensive and applied to limited numbers of samples, thus lacking sufficient representation and not suitable for geo-statistical modeling. In addition, geological mapping always presents uncertainty, based mostly on qualitative estimates. The combination of information usually provides geological models that are hard to combine with geo-metallurgical data, much less with mineral processing predictive behavior models. The advent of multi-element geochemistry, at low cost, has allowed employment of such tools massively, yet little use is given to the data, usually focused on elements of economic interest (main ore and credits) and elements of negative impact to concentrates and/or process. Geochemistry reflects the mineral composition of rocks, thus allowing characterization of lithology, alteration types and intensities, and mineralization. As examples of such applications we present generic classification techniques which were developed on various porphyry copper deposits of northern Chile, these based on multi-element geochemistry, allowing for semi-quantitative to quantitative high resolution modeling of key aspects of lithology, hydrothermal alteration and mineralization, and which may be cross-referenced to metallurgical test samples and by that, to geo-metallurgical properties of rocks and modeling. In addition, as data is quantitative and continuous, modelling of gangue can benefit from geo-statistical modeling.

Jan 1, 2018

By R Carstens, L Munsamy, L Prinsloo, C Huang, C Zhang, R Liang, I Canbulat

With recent advances in machine learning, data-based automated decision-making has been proven successful with promising outcomes in many industries. Its application in the mining sector can be ground-breaking; particularly the data-driven analytics that can support decision-making in the mine and consequently enhance mine safety, efficiency and sustainability. However, the current data science applications in the mining industry are mostly noncomprehensive, especially inadequate in evaluations, thus often requiring further study to be potentially beneficial to operations. Furthermore, it was found that existing literature paid limited attention to understanding the role of such techniques. Hence, in this paper we aim to build an end-to-end machine learning powered data-driven framework for intelligent geo-hazard analytics to support decision-making for underground mining data management, where multiple types of data are managed in an integrated database to support the unified machine-learning model. Here we present the framework as data-driven workflow processes, including data gathering, data preparation, data processing and data presentation. In addition, we present an application scenario of the proposed framework, where falls of ground (FoG) is managed with the historical FoG investigation reports, related panel hazard ratings, compliance data and rock mass characteristics. A demonstration can be dynamic forecasting of high-risk areas for FoG based on both spatial and temporal factors, including a 3D data visualisation. Such a scenario shows the potential of the proposed framework to establish connections among various data fields across a diverse category of data. Furthermore, the results offer important insights for ground instability management and can potentially optimise the underground operation flow.

Nov 29, 2022

By A. K. Majumder

The multi-gravity separator (MGS) is a novel piece of equipment for the separation of fine and ultra-fine minerals. However, the published literature does not demonstrate its use in the separation of coal fines. Therefore, an attempt was made to study the effects of different process variables on the performance of an MGS for the beneficiation of coal fines. The results obtained from this study revealed that among the parameters studied, drum rotation and feed solids concentration play dominating roles in controlling the yield and ash content of the clean coal. Mathematical modeling equations that correlate the variables studied and the yield and ash contents of the clean coal were developed to predict the performance of an MGS under different operating and design conditions. The entire exercise revealed that the MGS could produce a clean coal with an ash content of 14.67% and a yield of 71.23% from a feed coal having an ash content of 24.61%.

Jan 1, 2007