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By J Loeb, D Thornton

Blast movement measurement is a key component of grade control, enabling mines to carry all of the precision involved in locating ore blocks, through a chaotic blast, to production. A monitoring system was developed about ten years ago so that mine operation personnel can measure three dimensional movement in every production blast. Research has shown that blast movement is always highly variable with a significant non-deterministic component. The consequence is that modelling will be inaccurate and therefore optimal ore recovery can only be achieved by direct measurement of blast movement.Three dimensional movement vectors are measured at discrete locations in the blast. If blast movement is only measured at one location in a blast pattern, data is severely limited and has all of the inherent inaccuracies of modelling a variable population. It is intuitive that the accuracy of defining the post-blast ore block mark-ups are proportional to the number of movement measurement locations, however increasing the number of monitoring locations causes increases to the direct operating costs of the mine.A cost-benefit analysis is used to explore the optimal number of monitoring locations. Using the method described in this paper, an automated selection of the number and location of blast movement monitors are analysed against the value of recovered ore compared to the control, for each trial.CITATION:Loeb, J and Thornton, D, 2014. A cost benefit analysis to explore the optimal number of blast movement monitoring locations, in Proceedings Ninth International Mining Geology Conference 2014 , pp 441–450 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By E J. Sellers, A Cocker

Movement of the fragmented rock mass is an inevitable consequence of open cut blasting. Uncontrolled, unaccounted movement from blasting commonly causes ore loss and dilution from waste mixing. Therefore, the prediction of the post-blast location of both ore and waste is vital in grade control and of direct interest to mining geologists. Direct measurement techniques have matured significantly over the past decade, but their use remains expensive and labour intensive. Access and safety issues are further disincentives to regular movement monitoring. What is needed is a combination of direct measurement to establish baselines and reliable predictive modelling.The W H Bryan Mining and Geology Centre of the University of Queensland has pioneered 3D blast movement modelling using ‘physics engines’ to handle in-flight collisions and predict the final resting place of blasted material. Open cut metalliferous mines are a demanding environment for this style of modelling as they can involve complex geometries and variable buffering, which leads to inconsistent confinement. A version of the model designed to deal with these complexities is under development. A well-controlled field trial was needed to validate this new version.A validation trial was completed at a gold mine in South-East Asia. The aim was to increase throughput by increasing the blast powder factor without losing grade through dilution and mixing with waste. Four blocks were blasted to identify the effect of bench height and face confinement on ore movement, fragmentation and process throughput. The powder factor and blast timing were kept constant. Movement of the broken rock was measured by placing blast movement monitors at known positions in the block and then locating them after the blast. The majority of sensors were recovered, providing a unique insight into blast movement dynamics and generating a substantial data set for model validation.The model (called ‘MetaMove ‘) was calibrated for one blast and applied to investigate the extent of grade loss and possible mitigation strategies. Conventional mining techniques that involved firing across the strike of the orebody, and no post-blast boundary adjustment of the ore/waste boundaries prior to digging, were found to cause up to 44 per cent loss of high-grade ore, depending on the grade distributions. Post-blast adjustment of the ore/waste boundaries can negate this loss. The model indicates that altering timing and ensuring that the block boundaries are well confined can further constrain the movement of ore/waste boundaries. Thus, the model can be successfully applied to minimise grade dilution and limit misclassification of ore as waste whilst using higher powder factors to increase mill throughput. Application of a calibrated model to move ore/waste boundaries prior to digging will enable the production geology team to add significant value to the mining operation.CITATION:Cocker, A and Sellers, E J, 2014. Modelling blast movement for grade control at an open cut gold mine, in Proceedings Ninth International Mining Geology Conference 2014 , pp 377–386 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J Paradis, K Dudgeon, M Topping

At Newmont’s Jundee Operation, exploration and resource geologists collaborated to produce an open pit resource model. Using a variety of modelling and estimation techniques but no new data, an uneconomic underground target was converted into a potentially economic open pit evaluation. During an industry downturn, it is more important than ever to efficiently share expertise, ideas and resources to problem solve and produce meaningful project outcomes. The two departments brought together different methods and ideas, and the process showed that certain methods worked better than others in different situations, thus the appropriate method was applied to each part of the evaluation. The results were used to create new procedures and improved lithology modelling and resource model estimations. Adaptability of the geology departments and collaboration such as this are key to ongoing improvements and future mine life at Jundee.CITATION:Dudgeon, K, Paradis, J and Topping, M, 2014. Cook open pit model – the hurdles: how we leapt, lunged, stumbled and overcame them, in Proceedings Ninth International Mining Geology Conference 2014 , pp 169–174 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By K Ehrig, C Lower, V Liebezeit, M Smith, E Macmillan

"Minerals, minerals, minerals. Elements occur in the earth as minerals. If local physical, chemical and structural conditions are conducive to concentrating these minerals to sufficiently high abundances in the earth’s crust, a mineral deposit will form. If technology is available to extract metals from the minerals economically, then you have a mineral resource that will be mined and processed. Determining which minerals are present and quantifying their abundances, textural characteristics (grain size and shape) and how they are intergrown with each other is the realm of the mineralogist. Geologists use this mineralogical data to understand how the mineral deposit formed, how to find high-grade zones within the deposit and where to find other mineral deposits. Metallurgists use this data to design, operate and optimise processing facilities to extract metals from the minerals. The types, quantity and precision/resolution of the mineralogical data required by geologists and metallurgists are different, but are not mutually exclusive of each other. Fortunately, measurement technology is available that is relatively rapid, high volume and low cost, thus enabling ore and gangue mineral characterisation at a historically unprecedented scale of a mineral resource.CITATION:Ehrig, K, Liebezeit, V, Smith, M, Macmillan, E and Lower, C, 2014. Geologists and the value chain – how material characterisation by modern mineralogy can optimise design and operation of processing facilities, in Proceedings Ninth International Mining Geology Conference 2014, pp 5–14 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By R Hargreaves, C Morley

The authors often see problems on mine sites that are due to insufficient feedback between technical discipline silos as the realities on the ground fail to inform the models and plans used to drive resource exploitation. Resource modelling, reserve definition, life-of-mine planning, short-term mine planning and scheduling, mine operations and beneficiation operations are all processes that inform each other, but in many instances feedback between these processes occurs in an ad hoc way and only after problems have come to light.Universal reconciliation uses a multidisciplinary approach across the entire mining value chain to identify both opportunity and loss of value and to maximise operational performance. This paper will look at the operational effectiveness of universal reconciliation and will outline the important elements that make it successful, including how to map out the detail underpinning modelling, planning and execution processes. We do this by documenting the physical processes, logical work practices, organisational roles and responsibilities, data origin and quality, working assumptions and information management practices at an operation. The results quickly show how misinformation and assumption causes suboptimal decisions to be taken, where inefficiencies exist and what the opportunity is to remedy these issues.A universal reconciliation study opens up an opportunity for stakeholders to reassess how the operation should be run and how operational effectiveness should be measured. Clear envelopes for reconciliation become obvious and questions about the practicality and data quality can be addressed.A reconciliation code of practice is a key element of a successful universal reconciliation project and the authors outline the important aspects that will provide an operating model, showing the effectiveness of the resource and reserve modelling, the practicality of the mine planning and scheduling practices, how well the mine operations team are executing these schedules and how effective the processing area is given what it is fed. Most importantly, a system that allows operations time to react before the losses become systemic and that is based on identifying early warnings from hard data when these processes start to wobble is outlined. Finally as a case study, the revenue and cost benefits resulting from universal reconciliation diagnostic projects for nine mine sites is documented.CITATION:Hargreaves, R and Morley, C, 2014. Universal reconciliation – a multidisciplinary approach across the entire mining value chain to identify loss of value and maximise operational performance, in Proceedings Ninth International Mining Geology Conference 2014 , pp 411–420 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By S Coward, S Jackson, S Moayer, J E. Vann

The variability and uncertainty of mineralisation, coupled with subsequent uncertainty in mining and processing, is often paid scant regard or overlooked during the evaluation of mining projects. In many instances, when the project transitions to the operational phase, the reality of feed or product variability and the consequences of unquantified uncertainties throughout the value chain become obvious. The outcome is the familiar picture of frequent ramp-up underperformance and failure to deliver on planned targets and objectives.Both mine and exploration geologists are expected to generate mineral deposit models that are based on an integration of diverse sources of data. These multifaceted deposit models already play a pivotal role in the design, development and optimisation of mining project value, and the trend to a fully digitally engineered future means that this importance is increasing. It is therefore vitally important that tools be made available to the geologist (as well as mining engineers and metallurgists) that enable them to characterise and assess variability and uncertainty via appropriate deposit models and thus articulate their impact on potential project configurations and decisions. Scenario-based project evaluation (SBPE) provides a framework for full and proper analysis of the downstream impacts of inherent deposit variability and uncertainty on project performance.SBPE has been developed by the authors over several years and aims to propagate geological uncertainty and variability through the mining value chain. The outcomes of SBPE can be tested against future external scenarios capturing financial, economic and socio-political factors that also drive project performance. Stochastic representations of the orebody (via conditional simulation (see Chilès and Delfiner, 1999)) that explicitly incorporate variability and represent uncertainty are propagated through the value chain on a block-by-block basis (ie on a much more granular basis than traditional project evaluation approaches).Conventionally, metallurgical processes are modelled with deterministic equations (eg regression models) based on limited data. The SBPE approach allows for the modelling of process performance uncertainty using geometallurgical sampling fully. Multiple outcomes of SBPE are passed through financial modelling, which can also incorporate stochastic components, thus allowing full quantification of the risks and opportunities of a set of project alternatives. The value of the SBPE system is that once a base case has been established, multiple engineered alternatives coupled with external scenarios are easily evaluated and compared in terms of incremental value.A new case study of SBPE is presented that shows how, by analysis of the various aspects of variability and uncertainty, project managers are able to focus on the areas that have the greatest ability to reduce risk and/or add significant value. This can lead to sufficient flexibility being built into operations that allow operators to cope with the real orebody delivered to the plant.CITATION:Jackson, S, Vann, J E, Coward, S and Moayer, S, 2014. Scenario-based project evaluation – full mineral value chain stochastic simulation to evaluate development and operational alternatives, in Proceedings Ninth International Mining Geology Conference 2014 , pp 21–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By T Wellman, G Sternadt, R Hingston

The 335 000 oz Wilber Deposit is located within the Meekatharra-Wydgee Archaean greenstone belt in the Murchison District of Western Australia. The deposit comprises high-grade gold mineralisation hosted within a steeply west-dipping quartz lode, which lies within a broader (20–60?m) north-east striking shear zone envelope. Locally, the northerly-trending host rock geology includes greenschist facies high-Mg basalt (albite, actinolite, chlorite, biotite, calcite, zoisite, muscovite and titanate) intruded by at least two generations of felsic to intermediate porphyries (albite, actinolite, zoisite, chlorite, sericite, biotite, quartz and titanate). The Archaean rocks are cross-cut by a number of east–west striking Proterozoic dolerite dykes (biotite (50 per cent), albite, carbonate, epidote, titanate and actinolite) that are interpreted to have intruded pre-existing regional structures. The entire mine package is cross-cut by a system of shallow north-east-striking, north-west-dipping, barren quartz veins that commonly contain large (up to 30 cm), euhedral, smokey quartz megacrysts.The north-east-trending lode lies within a 3 m wide shear zone and varies from a single discrete 0.5 to 4 m wide laminated, massive or brecciated quartz-carbonate vein to multiple laminated veins up to 1 m wide within the shear. The veins exhibit strong boudinage, with cross-cutting quartz-carbonate seal veins in the boudin necks. The boudin necks often contain pink calcite. The shear zone fabric wraps closely around the boudin necks proximal to the vein, becoming more lode parallel distal to the vein. The lode is offset by a north to north-north-west trending fault.Mineralisation occurs as free gold within the quartz carbonate veins, with accessory sulfides including pyrite ± chalcopyrite, ± galena ± sphalerite. Fuchsite is observed in the veins, as laminar wall rock inclusions, with visible gold commonly associated with the wall rock laminations.Gold grades range from less than 1 g/t within the hosting shear zone, either at the margins or interstitial to the veins, to approximately 30 g/t in the single vein, and up to greater than 60 g/t in the multiple vein areas. Gold is commonly visible and disseminated throughout laminated, breccia and massive quartz veins, although laminations show the highest concentration of gold grains.CITATION:Hingston, R, Wellman, T and Sternadt, G, 2014. The geology of the Wilber Deposit, Andy Well Gold Project, Murchison District, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 55–64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By R O’Sullivan, D Taylor, J G. McLellan, B Miller

The Mount Isa copper deposit is located adjacent to the city of Mount Isa, Queensland, and lies within a series of Palaeoproterozoic to Mesoproterozoic Superbasins. The deposit is hosted almost entirely within the Urquhart Shale (US), a unit of the Mount Isa Group sediments and part of the Isa Superbasin. The copper mineralisation is separated into two distinct orebodies: the X41 mine (1100 and 1900 orebodies) and the Enterprise mine (3000 and 3500 orebodies). The orebodies are situated in the hanging wall of the major controlling structures, the Paroo Fault, which has juxtaposed older basement Eastern Creek Volcanics against the younger Mount Isa Group sediments cf 1655 ± 4 Ma. Conjecture remains over the exact timing of this thrust event. However, it is clear that inflections on the Paroo Fault have a close association with the orebodies and are an important structural feature in the mineralisation of the Mount Isa copper deposit.The life-of-mine is reducing steadily and new geomechanical modelling techniques were employed to target structurally controlled mineralised zones in three dimensions. Following a structural review of the mine using underground mapping, structural data and core shed observations, a conceptual 3D mine model was constructed utilising existing data modelled in MineSight®. This conceptual model included all the main lithological units and structures. The conceptual model aimed to test the effects of deformation on the main lithological and structural components of the system and attempted to highlight areas of anomalous stress and strain that may indicate a higher likelihood of fluid focusing and mineralisation potential. This project was focused on testing the latter stages of a D3 event (NE–SW compression) and D4 event (SE–NW compression), which are considered to be responsible for the current location of the mineralisation.The fully coupled 3D finite element analysis models resulted in highlighting anomalous patterns of stress and strain and subsequent fluid flow as a result of the two deformation events. The NE–SW D3 simulation provided the best correlation with the known distribution of mineralisation. This event also indicated several areas on the Paroo Fault and within the US that have potential to host further areas of mineralisation. The SE–NW D4 simulation provided less of a correlation with known mineralised zones. However, this event may have been responsible for post mineralisation re-mobilisation of copper on a relatively small scale. Areas of maximum shear strain, shear stress, volumetric strain and fluid flow correlated well with areas of minimum principal stress and provided the best overall match with known mineralised zones. Furthermore, several additional highlighted areas provide a high potential for further discovery of copper mineralisation. Recent exploration drilling north of the Enterprise mine 3000 orebody, utilising geomechanical modelling as part of the targeting criteria, intersected copper mineralisation, providing further validation of the modelling results.CITATION:McLellan, J G, O’Sullivan, R, Miller, B and Taylor, D, 2014. Geomechanical modelling of the Mount Isa copper deposit – predicting mineralisation, in Proceedings Ninth International Mining Geology Conference 2014 , pp 197–206 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By I Treloar, T Elenbaas, E Isaaks

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

Aug 18, 2014

By R Sterk, B Reid

The Konongo Gold Project is located on the western margin of the 125 Moz Ashanti Gold Belt in Ghana, West Africa. It is situated 60 km along strike of the world-class mineral system at Obuasi and is interpreted to lie on the same controlling regional shear system.The project is operated by Signature Metals, a subsidiary of the Liongold Corporation, and is managed and funded by the Liongold Corporation.Historic underground operations at Konongo produced 1.6 Moz Au at a head grade of 11.8 g/t Au, from eight operations spread along 16 km of the shear system. Mining focused almost exclusively on free-milling gold in quartz, ignoring the gold-bearing sulfide mineralisation associated with the quartz veins. Underground mining ceased in 1986.In 2013, Signature Metals re-focused the program at Konongo to assess the viability of mining the sulfide ore sustainably. This led to the first campaign review of the historic underground data and resource potential since mine closure. The Obenemase mine was the first of the eight operations to be assessed as part of this campaign.Large amounts of legacy data have survived for Obenemase and several historic resource estimations have been completed based on these data. The data typically consisted of hand-drawn sections and plans, and ledgers of commonly incomplete drilling and sampling data. Some drill core have been lost over time, but a large amount of quarter-core and half-core as well as pulps and rejects are still available. Previous resource estimates had a low confidence value because all the available assay and geological data were integrated effectively with the estimates, resulting in a lack of understanding of both grade and geological continuity.This project built a new geological model for Obenemase that greatly enhances the understanding of the controls on mineralisation using a thorough approach of re-surveying, re-cataloguing and re-logging. This model led to an increased degree of confidence and a subsequent upgrade of resource classification, and created several previously unrecognised strong exploration targets. The resulting resource estimates increased the value of the project by 100 per cent.This paper emphasises and highlights the importance of a well-understood geological model on the confidence of a resource estimate and how this may directly impact on the project’s ‘bottom line’.CITATION:Sterk, R and Reid, B, 2014. The Konongo Gold Project, Ghana – an example of how geology makes all the difference to a resource estimate, in Proceedings Ninth International Mining Geology Conference 2014 , pp 467–476 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J Ta’ala, M Handyside

Mechanical sampling from conveyors has historically been a staple in the iron ore industry when information related to chemistry, sizing and moisture is required. In order to comply with ISO 3082:2009, samples can be taken either on a mass or time basis provided no bias is introduced by periodical variation in quality or quantity. With the introduction of mechanical sample carousels, you also have the opportunity to collect samples on a mass or time basis. In order to optimise automatic sample stations in a changing production environment, BHP Billiton Iron Ore (BHPBIO) has developed a simulation model that enables the various combinations of mass–mass, mass–time, time–time and time–mass to be investigated.The sample station model can utilise actual (variable) feed rates to achieve high resolution and enables the simulation of sample size variation. Cutter speeds and other settings can then be adjusted to better optimise the performance of the sample station with regards to optimal sample size as well as ensuring the sample station is in compliance with ISO 3082. The model can also assist process engineers in adjusting settings to better optimise the sample station and reduce unwanted events such as blockages. The model can be easily modified to conform to various sample station designs. This paper demonstrates the use of the model and the benefits that can be achieved.CITATION:Handyside, M and Ta’ala, J, 2014. Simulating time versus mass basis?sampling, in Proceedings Sampling 2014 , pp 155–164 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By P J. Jacobs

FORACO is the third-largest global drilling services company, and recently celebrated its 50th anniversary. The company’s historical roots are in French-speaking West Africa, delivering hydrogeological drilling services to resource companies, villages and regional centres. Today, FORACO operates over 300 drill rigs in more than 20 countries.The Asia Pacific region of FORACO runs a fleet of 37 late model drilling rigs servicing the diamond drilling, reverse circulation, coal, coal seam gas and hydro drilling sectors.FORACO Australia has extensive experience delivering large diameter coring (LDC) samples to the resource community. In the past three years, the company has been involved in six 8? coring projects in a variety of geographies and geologies, including iron ore, coal and uranium. FORACO has developed proprietary equipment and techniques to deliver cost-effective LDC samples with outstanding core recovery.The FORACO LDC sampling system is hands free, with mechanised rod and corebarrel handing to minimise the risk of manual handling injuries. Sample volumes are six times PQ (the common industry standard for large core samples), with core recoveries consistently above 96 per cent in extremely difficult formations.Eight inch coring is a conventional coring system suited to hole depths up to 150 m. For deeper applications, FORACO has recently invested over $4 M in a 6? wireline coring system capable of achieving depths of 300 m.CITATION:Jacobs, P J, 2014. Large diameter core sampling, in Proceedings Sampling 2014 , pp 71–76 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By D François-Bongarçon

The theory of sampling (TOS), and therefore representative sampling, is based on three fundamental principles: sample correctness, which handles the search for non-bias; segregation, the effects of which must be eliminated or minimised; and variance control to help achieve the desired reproducibility. After briefly reviewing these very few, albeit essential first principles of Gy’s TOS, the state-of-the-art in TOS is examined through the prism of these principles and the prospects for the future are explored, with suggestions for further research where relevant. Regarding segregation, which is currently the focus of much research, new orientations are proposed. For correctness, which takes on a major importance when it comes to sampling devices, some new, important principles that have been put forth by recent research, are described in details.CITATION:François-Bongarçon, D, 2014. State of affairs and current research trends in theory of sampling fundamentals, including segregation and correctness, in Proceedings Sampling 2014 , pp 11–16 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By J Webb

"It is vitally important in projects where the cut-off grade is low that there is no contamination during the sampling and sample preparation process, both in the ore and the waste zones. Failure to identify contamination could have devastating financial consequences for a project. The use of a variety of blank types is essential for ensuring that contamination is identified and eliminated at every stage of the sampling and sample preparation process. This paper examines an instance where an effective assay quality assurance and quality control (QA/QC) program was able to identify and eliminate a source of significant multi-element contamination in the prefeasibility stages of an open pit project. This examination includes the: evidence for contamination findings of the investigation process of resolving the problem and correcting the data evidence for both addition of metal and dilution through contamination potential impact on the project had this issue not been dealt with. It was through the use of a combination of blank types that the QA/QC process at Mount Isa Mines (MIM) identified a contamination issue at the first crushing phase of sample preparation. Identification of the contamination allowed MIM to stop assaying activities and work with the laboratory to correct the problem. The sampling program could then be continued with no further doubts about the sample preparation process. Contaminated samples were resampled from retained core. With the continuous monitoring provided by the blanks program, it was possible to ensure that only clean results went into the resource modelling data set. CITATION:Webb, J, 2014. When nothing is what you need – the importance of using blanks at all stages of sample preparation, in Proceedings Sampling 2014 , pp 49–54 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 29, 2014

By J E. Powalisz

"The application of automated sampling techniques can help to provide a representative sample of process fluids and slurries that provide data for controlling process, custody transfer and quality assurance and quality control purposes.The automation of sampling provides a more consistent and reliable sampling process and eliminates many of the human-induced errors. Automated sampling can also provide a higher degree of safety in the plant/processing environment as well as better bottom-line results.Automated, fixed volume samplers can provide a very representative sample by integrating many small ‘grabs’ of sample from a process. Automated samplers can be controlled in a variety of ways to optimise the sampling process, including:cycle ratedwell timetotal volume.Properly selected and applied, an automated sampler can effectively isolate the operator from the process fluid during sampling and, to a great degree, during sample container collection.A variety of materials of construction, including seals, are available to handle demanding mining applications. Alloy 625, alloy 2205, AL6XN® and even certain plastics are used successfully in mining slurry applications.This paper explores the application of automated, fixed volume, batch style samplers in copper/nickel and gold processing, specifically pregnant leach solution and extraction fluids.Several specific field applications are discussed, including process installation details, hardware and operation.CITATION:Powalisz, J E, 2014. The application of automated samplers in copper/nickel processing, in Proceedings Sampling 2014, pp 35–42 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 29, 2014

By L Lachance, F Flament, D Leroux, S Gariépy

The pervasiveness of poor sampling practices in and around mineral processing plants could seem intriguing in view of the various documented evidences both for causes and consequences. To this extent, this paper revisits the well-documented but lesser-known fact that failure to care sufficiently about how samples are selected and managed is the mother source of almost all sampling biases. The authors believe that the potentially huge leverage between causes and consequences as well as the diversity of people involved in sampling call for a globally integrated solution rather than for a point solution. Such a globally integrated solution has already been put forward by the AMIRA P754 Metal accounting – code of practice and guidelines (AMIRA, 2007) that inherently requires accuracy to be targeted, measured, reported and managed. Furthermore, always in order to avoid a point solution, several layers of protection against biases must be put in place with each one involving a different ownership whenever possible. This is exactly the role intended by the supervisory bias detection method described in this publication. It is based on the continuous monitoring of the expected value of reduced residuals obtained from statistical data reconciliation conducted in a metal accounting context. This supervisory bias detection method is developed in full details after which Monte Carlo simulations are done on a mineral processing plant example for showing how it can be successfully applied for detecting hidden biases.CITATION:Lachance, L, Leroux, D, Gariépy, S and Flament, F, 2014. Detecting sampling biases in metal accounting, in Proceedings Sampling 2014 , pp 109–120 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By F F. Pitard

The optimisation of a metallurgical plant requires two kinds of sampling systems. The first provides samples to follow process changes, so in due time actions to maintain key parameters within pre-established specifications can be applied. The second provides composite samples at the end of a working shift to demonstrate that valuable constituents sent to the plant went to either a final concentrate or to the tailings in a logical, expected proportion. Contrary to what many experts may claim, these two kinds of sampling requirements are incompatible and cannot be fulfilled using the same sampling systems; this is because the required samples have completely different objectives. A process control sample is an instantaneous sample with increments taken at short intervals, and the objective is to know where the process is at any given time. Excellent accuracy is not a must, however good precision is recommended since a possible process correction may need to be made. Online analysers fed with in-stream stationary cutters or other kinds of in-stream or by-stream probes can do well for such a mission. A composite sample for metallurgical accounting with increments collected over a long period of time, for which excellent accuracy and good precision are both required, must be generated by sophisticated and extremely well-maintained cross-stream sampling stations. The use of process control sampling systems to achieve good metallurgical accounting has been promoted by several manufacturers of sampling equipment around the world; it is a grave mistake that is misleading top management and a practice that should be scrutinised and preferably eliminated. Furthermore, bias tests used to prove otherwise are often based on insufficient data to draw valid conclusions; a guideline is provided.CITATION:Pitard, F F, 2014. Sampling systems for process control and metallurgical accounting, in Proceedings Sampling 2014 , pp 25–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By R Minnitt

Two methods of calibrating the parameters K and Alpha for use in Gy’s formula for the fundamental sampling error were investigated. Approximately 480 kg of broken ore from Harmony’s Target gold mine in South Africa was used to compile the replicate samples for two experiments. The duplicate series analysis (DSA) and segregation free analysis (SFA) methods differ in terms of their approach to recovering the sized materials required for the calibration procedure. In this experiment the DSA method split off six more-or-less equal masses of material from a 75 kg lot that was successively crushed to finer and finer fragment sizes. The sublots so formed were split into 32 samples and fire assayed for gold. The SFA method used approximately 250 kg of broken ore crushed to 95 per cent passing 2.50 cm, which was then passed through successively finer screens until a sublot of less than 0.0075 cm was obtained. Each of the 15 sublots obtained in this way were split using a riffle splitter into 32 samples that were fire assayed. A total of 672 fire assays were used in these experiments. The sampling parameters K and Alpha were used for the compilation of a nomogram and to calculate the gold liberation size of the ores. While there are no definitive results in terms of the actual gold grain sizes against which the calculated sizes can be compared, it appears that the DSA method produces more acceptable results.CITATION:Minnitt, R, 2014. A comparison of two methods for calculating the constants K and alpha in a broken ore, in Proceedings Sampling 2014 , pp 165–178 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By J E. Powalisz

Obtaining a representative sample of bulk materials in process industries is critical to providing valid data for process control and custody transfer (valuation). The accuracy of a sample, that is to say how well the sample represents the material in the process, is directly related to how well the process can be controlled and to how much a product may be worth. Sampling accuracy then is in fact related to bottom line profitability.Sampling theory offers information and equations on how to take a representative sample from a process, however, the actual practice of extracting a sample from the process can be more of an art.Key sampling variables include product specifications such as bulk density, particle distribution, material conveyance, practical sampler location, sampler type and sample frequency and volume/mass.This paper discusses basic sampling theory, sampling methods, types of samplers, how to develop a ‘real world’ sampling system and current manual and automated samplers.Key points include ‘practical precision and variance’, material properties, flow properties, direct sampling versus indirect sampling, sampler types and applications.CITATION:Powalisz, J E, 2014. Bulk solids sampling, in Proceedings Sampling 2014 , pp 179–188 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By W P. Breytenbach

"The phased application of statistical process control (SPC) infers that processes are classifiable as pre-SPC (or phase zero), phase I and phase II processes, with different objectives being pursued in the different phases. Phase zero processes, defined as processes affected by assignable causes of variation, are characterised as follows: out-of-control with unknown autocorrelation structure having an unknown statistical distribution not performing consistently on target with minimum variability potentially incapable of conforming to the product specifications. The objectives of phase I SPC is to obtain estimates of the mean (µ), variance (s2), probability density function (f(X)) and the autocorrelation structure, as well as transforming the process into a phase II process (defined as a process conforming to specifications and performing on target with minimum variability). As in any other type of research or pragmatic improvement intervention, sampling is required is to achieve these objectives. The challenge of deciding a phase I sampling plan is multifarious since it has to cope with the aforementioned effects of assignable causes and provide for rigour estimates of the unknown parameters. Furthermore, deciding sampling plans in phase I invariably presents a classical catch-22 situation: appropriate sampling is required to determine the autocorrelation structure of a variable, but knowledge of the autocorrelation structure is required to formulate an appropriate sampling plan. This paper suggests, for random variables, guidelines to formulate sampling plans, and presents a methodology to estimate the inherent process parameters of process variables and an approach to identify assignable causes in phase I. CITATION:Breytenbach, W P, 2014. Rational sampling and standard deviations for random variables in phase i application of statistical process control, in Proceedings Sampling 2014, pp 141–154 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 29, 2014