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By H Asche

The Melbourne Metro project has evolved from the Victorian Transport Plan. MM1 is the second major phase of the proposed separation of Melbourne’s radial railway system, creating a line that will operate independently across the metropolitan region. The central section will run beneath the inner suburbs and the central city. The initial project comprises nearly 8 km of twin bore tunnels, three cavern stations and two cut and cover stations, as well as a dive structure and connections with the existing rail system. This paper describes the development of the geological model, a modification of the rock mass classification system derived during the EastLink project and the influence of the geology on the design of the tunnels and stations for the Department of Transport’s business case.The majority of the tunnelling will be in the siltstone and sandstone bedrock. This material has been extensively folded, sheared and intersected by igneous intrusions. A revised rock mass classification system has been developed for the Melbourne Formation to assist in identifying the important engineering properties of the rock and to rationalise the support types required.The Metro’s tunnel alignment crosses the Yarra Delta deposits in the lower reaches of the Moonee Ponds Creek and again at the Yarra itself near Princes Bridge. These deposits vary in extent and thickness over very short distances. The investigation of these materials has been carried out using conventional drilling techniques in conjunction with sonic drilling methods.Over the central section of the Metro, the positions of the new station are determined largely by transport planning requirements and urban development opportunities. However, the stations, and the tunnels, have been the subject of studies, optimising exercises, and selection processes to arrive at the concept design. This paper describes the influence of the varied geology on the development of the design, and the identification and management of the risks in tunnelling under the centre of Melbourne.

Mar 8, 2011

By M Sandy, A Vakili, J Albrecht

Although rock strength anisotropy is a well-known phenomenon in rock mechanics, its impact on geotechnical design is often ignored. No widely accepted guideline currently exists for its characterisation. Anisotropy can significantly control the failure mechanism and progression of damage into the rock mass, particularly in high-stress conditions. As such, it can play a key role in the stability of underground excavations and subsequent geotechnical design.This paper introduces the concept of anisotropy at both intact and rock mass scales. It then presents guidelines for measuring anisotropy and assigning rock mass strength properties. An improved unified constitutive model (IUCM), which can account for more complex failure mechanisms, is then briefly described. This IUCM is used to better understand the typical responses of anisotropic rocks to underground mining and to develop an improved damage classification scheme for these conditions.The application of conventional design methods in anisotropic conditions is shown to lead to significant errors. Two case histories are then presented, illustrating how the proposed methodology can improve the reliability and accuracy of the geotechnical analysis when compared with conventional design methods.CITATION:Vakili, A, Albrecht, J and Sandy, M, 2014. Rock strength anisotropy and its importance in underground geotechnical design, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 167–180 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By L Drowley

The Adelaide Desalination Plant (ADP) draws raw sea water into the facility and returns saline concentrate to the Gulf St Vincent via subsea conduits. This paper describes the detailed design and construction methodologies developed for the cross connection tunnel excavation. The paper concentrates on key design elements which include:· lateral breakout support of the segmental tunnel lining,· ground improvement grouting in the zone of the cross connection tunnels due to extremely variable and weak ground conditions, and· excavation methodologies and proposed support types of the riser to tunnel cross connections.The design process consisted of developing concepts, detailed risk assessment, three-dimensional (3D) finite element modelling and structural analysis for temporary support of tunnel lining; functional design of the ground improvement grouting and the temporary support; and permanent lining design of tunnel to ocean riser connections in a mixed soft ground/hard rock environment.The paper also presents conclusions of the design based on construction data available, and highlights the close collaboration between the design team and construction team.

Mar 8, 2011

By R A. Pax, B Cornish

"Although it is well known and easily experienced that the feed size distribution influences the throughput and stability of operation of a semi-autogenous grinding (SAG) mill, the details are poorly understood since it is often only the input and output measurements that are used to identify unfavourable in-mill conditions. Load cells and power monitoring are sometimes used but are generally poor indicators of the mechanisms that lead to such unwanted conditions.At the MMG Century operation a 12-microphone array around the SAG mill using non-contact acoustic measurement methodology has been used to diagnose the in-mill conditions to facilitate improved throughput and stability of operation. Use of acoustic measurement and control has provided a demonstrated increased throughput of at least 20 per cent as well as improved stabilisation of the mill. Since the information derived from the acoustic noise from a mill allows discrimination of the behaviour of the steel balls and the rock, a number of in-mill conditions can be identified with signals that include toe and shoulder angles, water holdup and the ball to rock ratio.Feed size variations, measured online with an imaging system, have been used to determine their effect on the internal charge behaviour. It has been found that circumferential segregation of steel balls and rock occurs as well as poor mixing of large rocks. Both of these effects are not conducive to optimal breakage rates of different size fractions. Longitudinal segregation effects also occur. This paper presents and discusses these results and illustrates how the new acoustic knowledge can be used to manage and improve mill operation and stability.Citation:Pax, R and Cornish, B, 2016. Understanding Size Effects of Semi-autogenous Grinding (SAG) Mill Operation as a Pathway to Solving Feed Disturbances - Case Study using the MMG Century SAG Mill, in Proceedings 13th AusIMM Mill Operators’ Conference 2016, pp 321–330 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Oct 10, 2016

By O Arafat, K M. Bartholomew

A voracious consumer of energy and grinding media, the modern ball milling circuit has a huge direct cost impact on a mineral processing operation. Through optimisation, grinding also has the potential to unlock great improvements in recovery and throughput, but how can the complex interactions between mills, classifiers, tonnage, ore-type and downstream recovery be measured, understood and managed in a systematic manner?Functional performance analysis provides the tools and insights needed to measure, understand and improve the two key process efficiencies in ball milling circuits: classification system efficiency (CSE) and mill grinding efficiency.CSE measures the composite performance of the classification system as a whole. In short, the purpose of the classification system is to ensure that grinding mill energy is used to grind coarse particles while minimising overgrinding. CSE is simple to measure in the plant and it provides immediate feedback to the plant metallurgist, mill superintendent and management about the performance of the classification system and the amount of wasted energy in the grinding plant.Mill grinding efficiency measures the capacity of the grinding mill to convert feed-sized material into product-sized material on a tonnes per kilowatt hour basis. It is normalised based upon the ore resistance to breakage, so it provides feedback about the ‘health’ of the milling process under varying operating conditions and ore types. Mill grinding efficiency is measured at the same time as CSE through circuit sampling.Functional performance analysis combines CSE and mill grinding efficiency to provide a measureable, manageable optimisation objective. It also provides a link to tonnage, ore type and recovery. As a result, systematic optimisation of a grinding circuit is a measureable and manageable process to meet business objectives.CITATION:Bartholomew, K M, McIvor, R E and Arafat, O, 2014. Functional performance of ball milling circuits – a plant metallurgist’s tool for process characterisation and optimisation, in Proceedings 12th AusIMM Mill Operators’ Conference 2014 , pp 227–232 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 1, 2014

By D Maconochie, S Pradhan, M Reed

The Waterview Connection will provide a high-quality strategic alternative to State Highway One and complete Auckland’s Western Ring Route connecting State Highways 20 and 16. The project includes twin three-lane motorway tunnels 2.4 km long and 13.1 m internal diameter (ID). The tunnel construction started in November 2013 using the tenth largest earth pressure balance (EPB) tunnel boring machine (TBM) in the world. The tunnels will pass beneath urban and greenfield areas as well as a major local arterial road. The project is being delivered by an alliance of constructors, designers and the New Zealand Transport Agency. This paper describes some of the key innovative and cost saving design solutions that have been achieved through collaboration in the alliance environment with the construction team, owner’s verifier, the segmental lining precast suballiance and the M&E suballiance for the underground works. The key design elements of the tunnel comprise a three-lane roadway, invert culvert and backfill, precast segmental lining, sixteen mined cross passages including a low point sump cross passage and steel segments for opening to the cross passages. This paper reviews interdisciplinary design integration and the economies achieved in the permanent works tunnel lining design, including reduction in lining thickness and optimising reinforcement, cross passage separation of 150 m, efficient design of the invert culvert and backfill design, main drainage pipe and low point sump. The paper also describes the attributes of the TBM and the invert culvert construction methodology.CITATION:Pradhan, S, Maconochie, D and Reed, M, 2014. Tunnel design in an alliance for Waterview Connection, New Zealand, in Proceedings 15th Australasian Tunnelling Conference 2014 , pp 425–430 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 17, 2014

By M Franklin, C Puglisi, S Fitch

Implementation of a well planned and executed Management Operating System (MOS) can result in widespread improvements to operational performance but its success relies heavily on the investment by and engagement of the larger workforce with the project. Over the seven month period of the Telfer MOS project, significant improvements were achieved; a 20% increase in monthly hoisted tonnes from the open stope and sublevel cave operations and a 45% increase in square metres of ore extracted from the narrow vein operation. The Telfer MOS was undertaken with the intention that the project wasn’t solely about producing new tools, it hinged on the investment and behaviours of the personnel affected by these tools and alterations. To ensure that the project ran smoothly, the Byrnecut senior leadership team and their operators were heavily involved in the project’s development. In the initial stage, Telfer’s MOS project determined that the quality and accuracy of the information received in the form of radio calls to mine control and completed operator plods was questionable. This required an overhaul of the data collection and verification process in the form of altered operator plods, which was then cross referenced with the operator’s radio calls to mine control. Once the data collection and verification process was implemented, the Telfer team was then able to produce several tools with the aim of providing visibility to the data being captured and its implications. These tools allowed the mine foremen to determine whether equipment was being under-utilised and where they should focus their production efforts to meet monthly targets. Whilst the initial underground project is now complete, the implementation of MOS across the entire site is ongoing with significant operating improvements occurring.

Mar 15, 2021

By R Marchant, D Willingham

"Predictive maintenance (also known as PHM or equipment ‘health monitoring’) refers to the intelligent monitoring of equipment to avoid future equipment failures. In contrast to conventional preventive maintenance, the maintenance schedule is not determined by a prescribed timeline; instead, it is determined by analytic algorithms, such as machine learning, using data collected from equipment sensors and/or via simulation.Predictive maintenance offers the following benefits for operators and equipment manufacturers:reduction of equipment downtime by identifying issues before failure, thereby enabling convenient scheduling of equipment service and extending equipment lifetimeautomatic determination of the root cause of the failure, enabling appropriate service to be performed without utilising resources to determine a diagnosis avoidance of costs of unnecessary maintenance and unexpected failures improved safety and product quality.Algorithms and data are critical to predictive maintenance success. Sensor data preprocessing is performed using advanced statistical and signal processing techniques. In the case that data isn’t available for the full range of operating modes, operating scenarios can be simulated. Machine learning techniques are then used to estimate equipment health. Once tested, predictive maintenance algorithms may be operationalised in an IT environment such as a server or cloud. Alternatively, algorithms may be implemented in an embedded system directly on the equipment, allowing for faster response times and significantly reducing the amount of data sent over the network.In this paper, we use both historical and simulated data of the plant under various modes of operation including run to failure, and we then leverage machine learning techniques in MATLAB to estimate degradation and remaining useful life. This technique, of combining both simulation models and machine learning, in the areas of predictive maintenance and equipment health monitoring has been adopted by Safran, makers of aircraft jet engines, since 2007. They now have over 160 modules developed (Lacaille and Aurelie, 2015).Citation:Willingham, D and Marchant, R, 2016. Predictive Maintenance Using Simulation and Machine Learning, in Proceedings 13th AusIMM Mill Operators’ Conference 2016, pp 279–284 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Oct 10, 2016

By R Moller

Reconciliation at large iron ore operations is a complex and time- consuming process. Often the volume of data and the large range of different stakeholders makes the process almost impossible. Up until recently geologists and engineers at these operations would spend hours cutting and pasting data in and out of monster spreadsheets, diligently comparing how resource/reserve models, grade control and survey pick-ups compare to what was actually produced. In 2003 the Sishen Iron Ore Mine in South Africa broke this cycle by implementing SnowdenÆs Reconcilor software. The implementation of a dedicated reconciliation system required a number of existing practices to be changed, with the involvement of stakeholders right across the mine. Data sources had to be clarified and validated, terminology had to be standardised, processes needed to be documented and some methodologies needed to be updated. This was a task that required significant effort by Kumba personnel so that the system could be successfully implemented. This paper provides a case study of the reconciliation system implementation at Sishen. It is a story of an operation that evolved from using a number of fragmented reconciliation processes to using a unified automated system. This paper outlines the key estimates and measurements that are used for reconciliation, details the characteristics of an automated web-based information management system to facilitate the process and provides some insights about the benefits that have been gained though the use of a rigorous reconciliation process.

Jan 1, 2005

By M Haest, O Dominguez, D Mittrup

With the current focus in the mining industry on reducing costs, while simultaneously improving ore quality, infrared spectroscopy is a tool that can potentially assist companies to meet both challenges. Changes in the nature of infrared spectra are strongly influenced by changes in mineralogy, which is a key input variable for exploration (geology and orebody modelling and ore characterisation) and mining (pit design, mine scheduling and processing plant design/management).Infrared spectroscopic logging of drill holes has been embedded as a standard tool in BHP Billiton Iron Ore exploration, with a process set up to automatically deliver mineralogy and associated imagery to the end users (typically exploration geologists). The availability of consistent and automated mineralogy drill hole logs across a project is improving the output quality and reducing re-work.BHP Billiton Iron Ore is now looking into using the same infrared spectroscopic data for other applications, including improving predictions of geometallurgical and geotechnical parameters. Trials show that addition of infrared spectroscopic data to conventional data sets (element analysis and depth information) is significantly improving the accuracy of regression models to predict the lump-fine ratio.Further initiatives around infrared spectroscopic data in BHP Billiton Iron Ore include the installation of infrared spectroscopic sensors over conveyor belts, infrared spectroscopic mine face scanning and infrared spectroscopic blasthole logging. The ultimate vision is to have consistent, seamless mineralogical data from infrared spectroscopic sensing available throughout the mineral value chain (exploration/mining/processing). This seamless infrared spectroscopic data ‘bridge’ will allow the transfer of knowledge between the different sections of the value chain (exploration, mining and processing). For example, ore handle-ability could be predicted on exploration samples using regression models built from processing plant observations. In the opposite direction, information gathered about the buried stratigraphy by infrared spectroscopy utilised during exploration, could be used to predict the stratigraphy encountered during mining. This collaboration across BHP Billiton Iron Ore is expected to deliver significant savings, while improving the quality of the final product, thus helping to drive efficiency over the next decade.CITATION:Haest, M, Mittrup, D and Dominguez, O, 2015. Reaping the first fruits – infrared spectroscopy: the new standard tool in BHP Billiton Iron Ore Exploration, in Proceedings Iron Ore 2015, pp 277–284 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By S F. Rogers, K Doumis, J H. Graaf, B J. Barsanti

Advances in technology now allow geotechnical practitioners to better describe the properties and variability of a rock mass through advances in surface and underground mapping, borehole technology and geophysical imaging. Yet the way in which practitioners use this data is not being realised to its full potential and the quality and quantity of data that is collected is often superior to the conventional design approaches that are typically adopted. A discrete fracture network (DFN) approach provides the ideal basis for using this data to generate geologically-realistic rock mass models based on parameters derived from field data, which more effectively capture the variability and rock mass behaviour. However, until recently, the DFN approach has mainly been applied to cave mining and small-scale models associated with synthetic rock mass modelling or groundwater flow modelling for the nuclear waste and oil and gas industries.Ground support design for blocky rock masses in Australia is often dealt with in a rather traditional manner, adopting either an observational empirical approach through rock mass classification systems or conventional wedge stability analysis techniques. Using these methods requires several generalised assumptions about the rock mass fabric and excavation geometry. As such, the support system is often designed for a worst-case scenario based on a predetermined risk tolerance that the mine is willing to accept and a design block size that is generally determined by the proposed excavation dimension.A study by Doumis (2014) used conventional wedge stability analysis and the probabilistic key block analysis software JBlock (Esterhuizen, 1996) to estimate potential block sizes and support requirements. A DFN approach has also been adopted at Callie underground mine using FracMan™ software (Golder Associates, 2014). The methodology of the DFN wedge analysis will be compared with the key block analysis work undertaken by Doumis.CITATION:Graaf, J H, Barsanti, B J, Doumis, K and Rogers, S F, 2014. Towards the implementation of discrete fracture network modelling as a geotechnical design tool – case study of callie underground mine, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 399–408 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By S Doudle

The Iluka Resources Ltd Jacinth-Ambrosia heavy mineral sand mine (South Australia) is located in an undisturbed semi-arid landscape consisting of sparse trees, shrubs and grasses. The soil interspaces are covered with biocrusts, a living soil cover also found worldwide in arid regions. Biocrusts are composed of lichens, cyanobacteria, algae, mosses, liverworts, fungi and bacteria, and live on and within the first few millimetres of the soil surface. Biocrust organisms bind soil particles, sequester carbon and many fix atmospheric nitrogen making them important structural and functional components of ecosystems. Despite their important role in ecological processes, biocrusts are susceptible to disturbance; nevertheless they can recover provided sufficient inoculum is present. Cyanobacteria are the early colonisers and they capture atmospheric and landscape resources and establish conditions that subsequent successional seres can capitalise on. Research conducted in countries including China, Spain and South Africa has been focused on methods to either encourage rapid regeneration of cyanobacterial remnants or to introduce new material from cultured cyanobacteria. We have been investigating the extent and diversity of biocrusts across the 4500 ha mine lease and their potential to improve mining rehabilitation outcomes. Approximately 46 per cent of the soil surfaces are colonised with biocrusts and 33 taxa have been identified. Laboratory experiments were designed to mimic massive soil disturbance and treated with a range of water qualities. Within 22 days, treatments irrigated with fresh water were colonised by new cyanobacterial filaments with a mean surface coverage of 65 per cent. Secondary tests revealed that differences in the photosynthetic yield of the crust were dependent on the salinity levels of the irrigation water used. In 2011 this program is expanding from the laboratory into field scale trials designed to assess both the potential and practicalities of up scaling these techniques to provide crushed biocrusts and cyanobacterial bio-inoculum for use in mine rehabilitation.

Oct 5, 2011

By J Jackson, M F. Young

"Ore is the economic portion of a mineral deposit that can be extracted economically. Hence an ore type is a classification of the ore based on one or more dominant characteristics in order to enable communication between unit operations and/or technical disciplines.In project evaluation, ore types are often defined early based on geological observations by geologists and initial metallurgical testing is based around this classification even though a number of processing options can be under evaluation. However, the geological drivers of performance for each of these processes can be very different and the ore type classification for one process may not be relevant for another. In operations an ore type, as either defined in the project evaluation phase or those that evolve with additional knowledge, is unlikely to provide the knowledge required across all the unit operations. The ore type has a meaning to someone but does not necessarily for all unit operations across the value chain.Geometallurgical or orebody knowledge has evolved through the consideration of multiple processes within the value chain, the improved understanding of variability of process performance within ore types and the effect on the complexity of the mineral extraction processes. Furthermore orebody knowledge has been moving from personal based knowledge and understanding to a more process oriented approach where measurement and spatial and process performance modelling is playing a greater role. Advances in mine planning and scheduling allow for both detailed analysis of the block model and the expected extraction processing attributes across various time scales. This capability of analysing and describing the complexity still requires to be communicated to the various unit operations, which may be beyond the traditional classification of an ore type.The limitations of an ore type and potential alternatives to enable the relevant information to be communicated to the relevant groups are outlined through a number of case examples across the value chain.CITATION:Jackson, J and Young, M F, 2016. Ore Type – Everything to Someone but Nothing to Anyone, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 267–274 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By Alvarez A. R, Garcia H. l

A fuzzy expert system, DIME, has been developed, under Matlab v 5.1. to assess the coal and gas outburst risk in underground mining. Expert systems and fuzzy logic are powerful tools to manage information represented by linguistic statements,

Jan 1, 1998

By A Weeks, W J. Shaw, A Kuk

Grade control is a process that requires the interaction between many components of the mining operation and successful grade control is only realised through good data, robust systems, and a well-trained, motivated and disciplined workforce.The Mt Magnet Gold Project Pty Ltd (MMGP), a wholly owned subsidiary of Ramelius Resources Limited, started mining at Mt Magnet in February 2012 with high expectations for success. Positive cash flow would fund an aggressive exploration and mine development program in the area to increase mine life. Disappointment followed when after start-up the operation had issues achieving budget grade and realising the predicted grade of the mined ore. In January 2013, things started to improve. During the next six months, gold production steadily increased with successive months achieving record production. What had changed?Improvements started following the realisation that controlling grade was not the sole responsibility of the mining geologist and that everyone on-site has a role to play. This paper examines the factors that delivered success for MMGP.CITATION:Weeks, A, Shaw, W J and Kuk, A, 2014. Who is responsible for grade? – an evaluation of the value chain at Mt Magnet Gold Project, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 477–482 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By P Malkin, S Thomas, P M. Stone, D Kostyuk

In open pit mining, it is common that the bottleneck to productivity and profit lies in the truck-shovel mining operation, especially as strip ratios and mining intensity have increased with resource depletion and advances in mining equipment capabilities. This paper outlines a study of truck-shovel productivity using a new proprietary discrete event simulation platform for truck-shovel operations called MineDES. The study will specifically address the issue of whether truck queuing at shovels should be considered productive or not, and how mining engineers can determine the optimal truck fleet size for specific operational configurations.The MineDES simulation platform will be described and illustrated, highlighting the features that make it an appropriate tool for conducting the experiments at the heart of this study. The study encompasses a set of experiments, consisting of a number of simple truck-shovel operational scenarios for a benchmark open pit mining operation, which are simulated using MineDES. Each experiment is designed to highlight different factors, which are most important in calculating the ideal truck fleet size and for understanding the marginal productive impact of each additional truck added to the fleet. The scenarios will principally address the issues of how different types and levels of unscheduled equipment downtime and process variation, combined with the traffic delays/congestion arising in more intense mining operations, will affect productivity. The results of the experiments are interpreted using a simple fit-for-purpose cost and revenue model in order to highlight the indicative cost of over- or under-trucked configurations.The study has found that the optimal fleet size that maximises productivity and value will, in the presence of even small process variation, lead to non-zero trucks queuing at shovels on average. As process variations and unscheduled downtime events increase in the truck-shovel system, the required fleet size to optimise productivity and value increases. MineDES provides a convenient platform for quantifying this for real operations.CITATION:Kostyuk, D, Thomas, S, Malkin, P and Stone, P M, 2014. Is truck queuing productive?, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 267–274 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By I Ritchie, A Johnston, D Yataco

Marcobre SAC (Marcobre) is developing the Mina Justa copper mine project, located in the Ica region of Peru. The Mina Justa IOCG orebody comprises of a sulfide mass overlain by an oxide cap with a sharp transitional zone between the sulfide and oxide masses. The primary target metal is copper, but there are minor amounts of gold and silver. The oxide will be treated by HPGR, crushing and vat leaching, whereas the sulfide will be treated by HPGR, milling and froth flotation. The processing selections are due to some unusual ore characteristics which have required relatively unconventional solutions.Vat leaching was chosen over heap leaching and other processes after detailed trade-off studies found it to be the most attractive, primarily due to the high acid consumption of the ore. The sulfide flotation produces a wide range of concentrate grades due to the complex nature of the mineralogy. The selection of HPGR circuits for both the oxide and sulfide ore is due to the extremely hard and competent nature of the deposit. These factors and others have contributed to a unique process selection for this resource.The selection process for the oxide and sulfide ores, and an overview of the technology, equipment selection and geometallurgy, will be discussed.CITATION:Johnston, A, Ritchie, I and Yataco, D, 2017. Process development for the Mina Justa project, in Proceedings MetPlant 2017, pp 207–217 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 11, 2017

By J Coombes

The JORC Code lists the three core principles of Transparency, Materiality and Competency as fundamental to how mineral estimates are publicly reported. But where the principles of Transparency and Materiality can be considered conscious choices underlying decisions at the point of disclosure, Competency is a self-declared position statement based on one’s confidence to defend a technical position (as well as the functional pre-requisites of institute membership and a minimum of five years relevant experience).Developing competency in the mining industry is an ad hoc process, generally left to the individual to chart through a process of osmosis from personal work experiences that lead to a sufficient level of confidence. Companies that actually present professional development programs leading to reporting competency are rare. And even once a person has followed a program, there is no specific outline of what constitutes technical competence.No doubt, there are persons signing off on mineral statements who would benefit from developing and/or updating their technical skills (they may not even be aware of unmastered skills). Equally, there are technical practitioners who are sufficiently competent, but lack the confidence to step up and publicly report their estimates. Confidence in one’s own abilities plays a significant role in deciding when one is ready for the responsibility of submitting mineral estimates for public consumption. In addition, a person’s organisational support, such as the availability of suitable peers and professional development programs, and opportunities to learn from a variety of technical projects contribute to developing relevant experience. Increased exposure in both technical breadth and depth enhance confidence in one’s ability and competence.The mining industry provides numerous opportunities through direct and indirect means to develop the competency underpinning a stable reporting code. This paper examines a theoretical framework and associated processes that could be used to examine how the mining industry, companies and individuals collaborate to develop this vague principle of competency. This paper seeks to initiate research with the express purpose of enabling more effective and efficient development of reporting competency in our industry.

Aug 22, 2011

By M Haest, O Dominguez, D Mittrup

Technological innovations and emerging analytical capabilities are transforming the way drill samples are analysed, with real-time mineralogical analysis made possible. In addition, new business/technical requirements are challenging long standing processes to incorporate more sources of information during planning in order to improve compliance to plan during mining and processing. Unfortunately, the new sources of information that are added do not always have adequate protocols in place to ensure quality data is collected.Spectral data covering the visible – near – short wave – midwave – longwave range are routinely collected by the Geoscience and Exploration department at BHP Billiton Iron Ore for accurate mineralogical identification. These data are used for geological interpretations (logging and modelling) and prediction of physical variables (metallurgical and geotechnical properties).This paper introduces how sampling and quality assurance / quality control concepts have been applied in the spectral data process. The described routine for sampling, data collection/management and reconciliation has been developed to track system precision and accurately and consistently ensure the data is of high quality before it is used across the mining chain.CITATION:Mittrup, D, Dominguez, O and Haest, M, 2017. A new approach to implement quality assurance and quality control to technological innovations – quality of spectral data capture and processes in the minerals industry, in Proceedings Eighth World Conference on Sampling and Blending , pp 265–270 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By N Schofield

For the sampling of particulate materials in mineral exploration and mining, the fundamental sampling error (FSE) introduced by Gy is a measure of the constitutional heterogeneity of the sample lot and is expressed as the relative standard deviation of subsample grades of a particular mass. The FSE is presently regarded as an important indicator of quality for samples used in resource estimation. Constitutional heterogeneity describes an ideal state of heterogeneity with respect to all constituents of the lot such that the fundamental error among subsamples of a particular mass is minimised.In this paper, the term ‘sampling precision’ used in relation to mineral resource sampling usually refers to a statistic based on the assay results drawn from pairs of separate subsample splits of multiple sample lots. The pairs of splits are extracted after the lots have been prepared by crushing and pulverising to meet specified criteria of grain size and subsample mass. There is presently no generally accepted method of calculating the ‘sampling precision’ from such paired data but some form of the relative standard deviation that is consistent with definition of the FSE is preferred here. The work of Thompson and Howarth in the 1970s on geochemical analytical precision, which has been subjected to extensive examination and criticism by Stanley and Lawie (2007), and that of Francois-Bongarçon since the 1990s forms the background to the discussion in the paper.A significant aspect of the application of Gy’s sampling theory to sampling in gold deposits is the requirement that the fundamental error be maintained at less than ±20 per cent. The most important reason for this is to ensure that the effects of other sampling errors such as the grouping and segregation, and increment delimitation which can cause local and global biases in sampling are kept as small as possible. This paper is focused mainly on the quality of sampling in gold deposits and looks at an alternative to the use of a constant sampling precision applied to a collection of lots with varying average grade. A theoretical model for the FSE based on duplicate sampling is presented and the simulated results of the model are compared to practical outcomes of real duplicate pairs drawn from multiple sample lots. The goal of the work is to present a more informative analysis of duplicate sample data from multiple lots which may allow a more informed view of the potential for bias generating errors during sample preparation and processing.

Aug 22, 2011