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By D François-Bongarçon

After a review of the progresses made on the liberation factor theory since its inception by Gy (1982), a new and surprising result of great practical importance is presented: the liberation factor. First introduced simply as a number between 0 and 1, then shown to be the ratio of two variances, is now shown to be well approximated by the proportion of liberated mineral.CITATION:François-Bongarçon, D, 2017. Evolution of the concept of the liberation factor and a surprising new result, in Proceedings Eighth World Conference on Sampling and Blending , pp 307–310 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By C Paoletti

About 15 years ago the debate on the reliability of sampling procedures for agricultural food and feed commodities was initiated by a few brave scientists who questioned the representativeness of what, at the time, were routine sampling procedures established exclusively on the basis of tradition and practical feasibility. Over time several national and international organisations contributed to the discussion, developing standards and publishing papers either to underline the fact that sampling is always a source of error, in itself, which cannot be overlooked, or to minimise the relevance of sampling on the basis of argumentations linked to time and money limitations. The latter dominated, but is nevertheless impossible to accept from both a scientific and a responsible management perspective. Here the author presents an historical overview of these past 15 years, illustrating the most controversial issues, reporting major achievements in food/feed sampling, highlighting milestones, as well as unresolved problems that still need the attention and contribution from the sampling community. The need to incorporate Theory of Sampling (TOS) into food/feed safety assessment (pre-market), as well as into food/feed safety monitoring (post-market) has recently been highlighted, and the practical applicability of TOS to base food/feed safety decisions on representative sampling, has been explored and documented via concrete examples of risk analysis in different areas of food/feed industrial production chains. Now it is time to move forward and ensure that TOS is fully integrated into the well-established Food and Agriculture Organization (FAO) / World Health Organization (WHO) risk assessment approach, in order to guarantee a transparent and correct universal frame for risk assessment and the subsequent management decision-making process. WCSB8 offers the ideal platform to explore the best way to do so, switching from a theoretical discussion of correct sampling principles for food and feed agricultural commodities to practical recommendations in the interest of consumers, worldwide. These 15 years have also been a personal journey of interesting dimensions, indeed a veritable roller-coaster ride in-and-out of the scientific, technological, industrial and (last but not least) regulatory worlds. The start was WCSB2 in 2004, when I flew to Australia to discover if in other areas sampling had been identified as an unavoidable issue and, if so, what the solution was. There, I found a good travel companion who today is still on my side, to assemble the puzzle and explore how to shape the future, to concretely answer to the 15 years’ quest for proper sampling in the assessment and monitoring of food/feed safety.CITATION:Paoletti, C, 2017. Assessing and monitoring food and feed safety – a 15 year quest for proper sampling, in Proceedings Eighth World Conference on Sampling and Blending , pp 39–44 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By E A. Amaral Jr, A C. Chieregati, J C. O Souza

Cross-belt samplers are designed to sample particulate material in processing plants, usually when there is no space to install a conventional linear falling stream sampler. Most of the available cross-belt samplers are mounted on the top of conveyor belts, and remove each increment from a loaded moving conveyor with a 360° rotation of an open faced cutter, in a plane perpendicular to the material flow. Despite the practicality of this equipment and the fact that it occupies very little space in the plant, cross-belt samplers are well known for collecting biased samples, especially due to the increment extraction error. Sampling consultants around the world tend to condemn this sampling equipment, claiming that it is incapable of collecting the fine material from the bottom part of the load, and, since the sampling probability is not uniform for all fragments and depends on its position in the stream, this kind of sampler generates biased samples and its use should be avoided. Furthermore, the greater the segregation effect between particles, the larger the bias. However, some plants, whose initial design did not plan for the installation of a falling stream sampler, must rely on cross-belt samples for process control and reconciliation. For the past years, sampling equipment manufacturers have been putting effort in modifying the cross-belt sampler design in order to comply with the principles of correct sampling. Changes to the cutter material, shape, position, speed and movement in relation to the material flow have been made, and are continually being tested for different types of ore with various chemical and physical characteristics. This paper presents the improvements made to a cross-belt sampler at a gold plant feed in Brazil and describes the tests performed until it was possible to validate the new sampling equipment for reconciliation purposes.CITATION:Chieregati, A C, Amaral Jr, E A and Souza, J C O, 2017. Validation of a modified cross-belt sampler for reconciliation purposes, in Proceedings Eighth World Conference on Sampling and Blending , pp 247–254 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By D François-Bongarçon

The link between geostatistics and Theory of Sampling (TOS) is examined again in view of new findings made while trying to compare predicted sampling variances and estimated grades (using geostatistics) on the same material, and this provides an important consistency requirement whenever calculations are made that involve both theories in a comparative way. It also briefly explores the relationship to De Wijs fractal model of mineralisation and eventually provides new support for the use of consistency theory for calibrating TOS variance formulas.CITATION:François-Bongarçon, D, 2017. Theory of Sampling and geostatistics – the ultimate link, in Proceedings Eighth World Conference on Sampling and Blending , pp 391–394 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By A Parbhakar-Fox, S C. Dominy

The prediction of acid and metalliferous drainage (AMD) from mine waste materials is critically important during all stages of the mine value chain. However, to determine such geoenvironmental characteristics static and kinetic testing of individual waste units must be performed on representative samples. The importance of sample selection cannot be underestimated; it is the single most critical aspect of any geoenvironmental investigation. Poor sampling techniques and inadequate sample selection will contribute to excessive variance, difficulties in interpretation and incorrect assessment. By undertaking mesotextural characterisation based on hyperspectral mineralogical data (with sulfur assay data if available), opportunities to improve sampling strategies are presented. Such data will inform the selection of samples for low-cost total sulfur, paste pH and geoenvironmental logging, which collectively will allow for accurate AMD forecasting and improved sampling practices to be achieved. Once sampled, robust quality assurance/quality control (QA/QC) protocols must be developed where the use of international certified reference standards become obligatory. This is currently not practised, resulting in inter-laboratory discrepancies when undertaking waste classification. Further improvements in geoenvironmental characterisation testing lies in the adoption of blended static testing protocols, whereby blends of waste materials can be efficiently tested so as to give an early forecast as to whether they will produce acidic or metal-laden drainage. Such information is integral in developing a waste schedule that will allow for a non-acid forming waste landform to be constructed right from the start of the operational phase. Ultimately, improvements in this discipline lie in technological innovations with regards to mineralogical characterisation, and by offering geoscience and minerals engineering students a competent education in the discipline. Collectively, this will empower a step-change in AMD prediction and waste handling, and will make the realisation of the United Nations Sustainable Development Goals a reality, rather than a dream.CITATION:Parbhakar-Fox, A and Dominy, S C, 2017. Sampling and blending in geoenvironmental campaigns – current practice and future opportunities, in Proceedings Eighth World Conference on Sampling and Blending , pp 45–54 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By D W. Wall, J P. Vagenas

Questions of sampling precision and accuracy affect every process plant in differing ways and to differing extents. To address these perceived issues, chemists, metallurgists and engineers are often asked to check their results to confirm their reliability. However, it is not possible to achieve the level of detail required to check every sample, especially if the event has already occurred. No operation has the resources to frequently sample every point in the process for the purpose of verification.One way to address this scenario is by generating a sufficiently detailed comparative data set from a dynamic mass balance simulation of the processing plant. This mass balance uses both sample and plant instrument data to model every flow, while also taking inventory changes and process chemistry into account.The mass balance data can be used to identify any bias present in plant sampling and analysis. It can also be used to verify any unexpected assay results by taking a holistic view of the process. Improving the precision and accuracy of sampling data helps support operational decision-?making and understanding. It also improves the accuracy of the dynamic mass balance used in this process, facilitating further improvements.CITATION:Vagenas, J P and Wall, D W, 2017. The benefits of automated metallurgical accounting for plant sampling, in Proceedings Eighth World Conference on Sampling and Blending , pp 203–210 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By K H. Esbensen, A Arkenbout

In the north of the Netherlands, in the environment of Harlingen, an industrial waste incinerator was installed in 2011. The population in the region is concerned about adverse health effects related to possible emission of dioxins. This study compares the relative merit and reliability of four sampling approaches aimed at quantifying the possible pollution patterns surrounding the incinerator: short-term versus long-term isokinetic flue gas sampling, spatial sampling of grasses and a novel approach developed by the Toxicowatch Foundation, based on local composite sampling of ten eggs from backyard chickens (local area pollution load averaging by accumulating bio-entities). Based on the latter approach results of a new analytical bioassay, DR CALUX®, from 15 locations near Harlingen harbour show distinct above-threshold dioxin levels in the environs of the incinerator. Currently only short-term flue gas sampling is mandated by the authorities; based hereupon, under normal operating conditions, the incinerator appears to be compliant with emission standards. This short-term sampling scheme is seriously flawed, however, in that it only demands one continuous 12-hour sampling period per annum – an extreme grab sampling transgression in the time domain. In starkest possible contrast, significantly elevated dioxins emissions were measured in flue gas during events of unstable combustion conditions by continuous long-term measurements. The dioxin congener patterns from long-term flue gas sampling show similar patterns as the congeners found in backyard chicken eggs and grass, evidence that elevated dioxins in eggs is due to emissions from the incinerator. These results make it mandatory to perform long-term, continuous measurements for all sources where similar high-temperature combustion/emission processes take place. Backyard chicken eggs are a prevalent regional bio-accumulating sample type in rural and agricultural regions, which is relevant to air pollution emission monitoring. There are interesting relationships between this type of sampling bio-sensors and the special bioassay DR CALUX® features, which, although quite outside traditional contexts, never-the-less all can be well understood in the context of the Theory of Sampling. We venture to unravel the complex interactions between correct and incorrect sampling errors and the extraordinary complicated analytical issues involved in monitoring and source tracking using accumulating bio-sensors. The present contribution is but a first foray indicating the general total sample error scope and total analytical error framework needed for this approach.CITATION:Arkenbout, A and Esbensen, K H, 2017. Sampling, monitoring and source tracking of dioxins in the environment of an incinerator in the Netherlands, in Proceedings Eighth World Conference on Sampling and Blending , pp 117–124 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By O Bøckman, E Thisted, K H. Esbensen, U Thisted

Process industry measurement systems, once installed, are often interpreted as static black boxes delivering correct values as long as not proven otherwise. After first implementation and set-up with a distinct sampling frequency, they often run ‘forever’ without checking if this frequency is still appropriate with respect to changed raw materials characteristics, different process conditions or changed customer specifications. Failure detection is based on operator experience and skills (often close to an art form) and/or from control measurements of reference samples. This may well be too late for many industrial process contexts. An appropriate sampling frequency is a critical success factor for valid monitoring and control.Based on the methodology of variographic analysis we here illustrate how to design/re-design/optimise an industrial measurement system in terms of sampling frequency, discretisation and accuracy based on customer specifications. We also show how variographics can be used to monitor for deviations. We use experience from process industry to show how these methods can be used not only for product characterisation, but also for monitoring input factors, process indicators and measurement of these. The information hidden in the vast amounts of data that is continuously created in modern process industries can be utilised to cut costs in the measurement activities and at the same time contribute to early error detection. We illustrate by case examples from production processes at a nickel refinery, supporting the Lean and Six Sigma methodology. This will provide a standard operating procedure for monitoring the stability of measurement systems, and provide a basis with which to discuss how a variographic approach can be integrated with the Lean and Six Sigma approach as an online tool to map, characterise and validate measurement systems and thus avoid more cumbersome measurement system analysis in full detail.CITATION:Thisted, E, Thisted, U, Bøckman, O and Esbensen, K H, 2017. Variographic case study for designing, monitoring and optimising industrial measurement systems – the missing link in Lean and Six Sigma, in Proceedings Eighth World Conference on Sampling and Blending , pp 359–366 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By S C. Labram, A Stabile

"Modern train load out stations are becoming faster and have the ability to load a 100 wagon train in less than three hours. At 70 metric tonnes per wagon, that is an average fill rate of 2333 t/h and considering the train is continuously moving, the instantaneous feed rate into the wagon is in the region of 4200 t/h.The main feed conveyor that maintains the level in the surge hopper, above the final weigh hopper, operates in excess of 5000 t/h to ensure uninterrupted charging of the weigh hopper to not disrupt the train loading operation.To avoid demurrage costs (a charge by the Rail Operating Company for exceeding the contractually agreed loading time) the train has to be handled speedily and efficiently and spend the absolute minimum time at the loading facility. Everything else has a much lower priority, including sampling.Thermo Fisher Scientific’s brief was an engineering, procurement and construction management (EPCM) contract to provide a sampling scheme adjacent to the prepurchased and predesigned load-out facility, but which interfaced seamlessly with the loading system of the trains and provided the following: an instantaneous particle size distribution (PSD) result for each truck loaded, and a final PSD for the total train prior to the train leaving the loading facility a crushed (-3 mm) composite sample for chemical analysis for the whole train a composite physical analysis sample for the whole train.The design presented some interesting challenges to our team, but the end result is a system that not only ‘stands alone’ but interfaces seamlessly with the loading system. This paper discusses the design itself and potential improvements to future systems.CITATION:Labram, S C and Stabile, A, 2017. An automatic sampling methodology to determine contractual particle size distribution in rapid train load out stations, in Proceedings Eighth World Conference on Sampling and Blending, pp 229–234 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

May 9, 2017

By R J. Romañach

The theory of sampling (TOS) is now followed in the development of near infrared (NIR) spectroscopic methods for the pharmaceutical industry. TOS has been the guiding light for a two-step approach for spectroscopic composite sampling available for the development of real-time analytical methods for particulate-based industrial processes. The two-step spectroscopic sample composite has been used in the development of process analytical technology (PAT), an important regulatory initiative to improve the quality of pharmaceutical products. The two-step sample composite approach overcomes the low sample volume analysed by PAT methods; one of the key limitations to PAT implementation in the industrial production of particulate-based materials.PAT methods need to be validated demonstrating their accuracy, precision, specificity and robustness. TOS provides a deeper understanding of these validation studies which involve discrete particulate material. The validation of PAT methods is now being performed considering both sampling and analytical errors, while practically all previous method validations only addressed the total analytical error (TAE) of these methods. This has been a crucial impediment for the field of chemometrics as well.PAT is a key element of continuous manufacturing (CM) processes, which are considered an emerging technology capable of increasing the flexibility, agility and robustness of pharmaceutical processes while reducing their costs. The outflow of the continuous process is a 1D lot, and variographic analysis has been shown to discern process variation from sampling and analytical errors in pharmaceutical CM processes. Thus, variographic analysis is a process improvement tool with significant potential for improving CM processes. The possibilities for improving pharmaceutical manufacturing are enormous.CITATION:Romañach, R J, 2017. Theory of Sampling – from missing link to key enabler for process analytical technology, in Proceedings Eighth World Conference on Sampling and Blending , pp 63–68 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By F F. Pitard, K J. Ehrig

The Olympic Dam iron-oxide copper-gold (IOCG) uranium-silver deposit is second in size only to Norilsk, the gigantic metalliferous deposit. Olympic Dam is the largest publicly declared uranium, fifth largest copper and third largest gold resource. The deposit is typified by texturally destructive brecciation and intense iron metasomatism of the Roxby Downs Granite, bedded clastic facies rocks and mafic-ultramafic dykes. The deposit contains over 100 minerals. Copper mineralisation consists of chalcopyrite, bornite and chalcocite. Uraninite, coffinite and brannerite are the dominant uranium-bearing minerals. Gold mineralisation consists of electrum, tellurides and Au-Cu alloys. Hessite is the major silver-bearing mineral. The economic minerals are disseminated throughout the breccia matrix where the average grain sizes of the Cu-sulfide, uranium, gold and silver minerals are ~50, 20, <5, <5 microns, respectively.A significant number of sampling theory-based test programs have been completed since the mid-1990s to establish sampling nomographs, select appropriate sampling (ie split versus chip and interval lengths) and sample preparation protocols, quantify the errors associated with each subsampling stage, determine the practical uncertainty limits of Olympic Dam matrix-matched standards, and identify improvement opportunities related to the ongoing assaying quality assurance / quality control (QA/QC) program. Invaluable knowledge and unexpected insights gained from sampling studies at Olympic Dam have helped to improve our understanding of the distribution of economic and deleterious elements within the Olympic Dam deposit.CITATION:Ehrig, K J and Pitard, F F, 2017. Underground bulk sampling, uniform conditioning and conditional simulation – unrealistic expectations?, in Proceedings Eighth World Conference on Sampling and Blending , pp 21–28 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By G J. Lyman

In sampling a process stream, conventional sampling theory deals only with the variation of the analyte content and neglects the impact of the variation in the mass flow on the sampling variance, whether the sampling regime is time-based or mass-based. This is an obvious simplification of the real state of affairs and it is worthwhile to study this impact via simulation.With a facility to simulate large (long) random functions having some thousands of points in the function and the ability to impose covariance functions on the mass flow and analyte variations, such a study is possible. It is also possible to evaluate the impact of correlation between analyte content and mass flows.This paper describes a limited study of the variance increase due to mass flow fluctuations over the usual sampling variance due to analyte variation during the sampling period. The bias in the sampling result is determined for specific modes of correlation. Simulation methods are used as they are the only means by which a sampling result can be compared to the true assay for the lot; in the physical circumstances of mineral process analysis, it is never possible to determine the true process stream assay.CITATION:Lyman, G J, 2017. The impact of the weighting error, in Proceedings Eighth World Conference on Sampling and Blending , pp 311–318 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

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 C J. Kruger, E le Roux

Anglo American Platinum has adopted a strategy of Best Practice Principles (BPP) for sampling, mass measurement, analysis and metal accounting for more than a decade now. When new plants are designed, the most suitable sampling equipment and sampling protocols are implemented and material flows and plant layouts are designed around sampling strategies. A few years ago, a crushing plant for a high-grade matte stream was commissioned.The design called for the high-grade material to be crushed to 95 per cent passing 2 mm and the design allowed for a single cutter primary Vezin sampler, increments taken from a gravity flowing stream at regular intervals, whilst filling a tanker for the pneumatic offload at our base metal refinery. This was a single point of sampling and analysis that would measure the wanted output from our smelting complex and the input to our refineries. In addition, the design incorporated the functionality to collect increments in an ‘interleaved’ fashion from the Vezin sampler for internal precision checks.The metal accounting strategy for Anglo Platinum is the ongoing measurement of all inputs, outputs and stock levels for all our operations for platinum group metal (PGM) and base metal (BM) content. Included are yearly stocktakes, usually done on 1 February every year, across the smelters and refineries (at least the base metal refinery). A trend was developing in the accounting period immediately following the introduction of the new crushing and sampling facility, whereby the absolute difference between the physical stock and theoretical stock (PGMs predominantly) increased for the two respective sites on an ongoing basis. The smelter (sender) showed an increase in physical stock compared to the theoretical stock and the base metal refinery (receiver) showed that their theoretical stock increased against their physical stock. Because of this anomaly, an additional stocktake was held in September for the period in question and it was confirmed through the physical stock measurement results, that the PGM accounting problem was indeed pointing towards the evaluation of the high-grade matte stream.This paper showcases parts of the process that took place to explain the poor accountabilities for the respective sites. Previous results from the sampler ratification process (of the interleaved sampling design) were analysed again, a physical inspection was carried out on the sampling system again and the sampler performance was monitored (quality control parameters) for the period.From these investigations, it was found that airflows present inside the Vezin introduced the sampling bias and a change in sampling protocol was introduced as well as physical changes to the sampling equipment were made to eliminate the airflow and thus the bias conditions significantly. The accounting period which followed, after a phased upgrading process, showed that the accounting between our smelter and base metal refinery had been restored to within statistical limits (difference between physical and theoretical stock below five per cent relative to theoretical stock).CITATION:Kruger, C J and le Roux, E, 2017. Pitfalls in Vezin sampling for finely crushed materials, in Proceedings Eighth World Conference on Sampling and Blending , pp 151–158 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By P Goblet, S A. Séguret, E Cordier, A Galli

In salar-type deposits, lithium grades can be measured by bailers introduced at different elevations in the drill holes at locations where, later, the brine will be pumped out to recover the metal. When they are duplicated, these a priori rudimentary measurements may show large differences without indicating whether this is due to the procedure itself or to some physical causes linked to the dynamic behaviour of the salar (seasonality, rainfall, underground flow etc). In the reservoir presented in the paper, the problem is complicated by the double lack of stationarity of the lithium grades: the grades not only increase importantly with the depth but at the same time their fluctuations decrease, making it necessary to use non-stationary geostatistical techniques to simulate them. Reservoir simulation is developed in two steps: first, geostatistical simulations of the lithium grade create possible realisations of the reservoir; then, each geostatistical simulation is followed by a pumping simulation that calculates, at each drill hole of a given extraction scenario, the lithium produced each year over 40 years. For the set of 100 simulations produced in this way, a scenario reduction is made to choose the five most representative simulations where more complex calculations will be carried out (for example, changing hydrogeological parameters such as porosity and permeability, or the elevation of the filters, the number and the location of the pumping and the reinjection drill holes etc). The paper first presents an analysis of the geostatistical model sensitivity to the grade uncertainty when measured by bailer. Among the 100 measurements at our disposal covering the future production domain, 50 per cent are duplicates measured at the same place but at different times. They are randomly sampled to produce five subsets of 75 values, which will constitute the future 3D conditioning points for the geostatistical analysis and the simulations. For each subset, trend, standard deviation and variogram models are fitted, leading to five sets of 20 geostatistical simulations of grades. In this way, the reliability of the different parameters involved in the procedure is evaluated, as well as its impact on the pumping results. Then, a reconciliation study is conducted between the non-stationary nugget effects encountered in the 3D variograms of the lithium grade and a pure statistical analysis of 25 duplicates measured at different locations and/or different times. The result is that if the nugget effect reaches 20 per cent, which is the case of three conditioning subsets out of five, the reconciliation is good and the nugget effect of the variogram model represents the bailer uncertainty, ie the measurement error. Since the geostatistical simulation incorporates a nugget effect, it handles the bailer uncertainty and the impact on the produced metal is included in the evaluation. The final conclusion is that, after the hydrogeological pumping simulations, the initial differences between the five geostatistical models do not influence the final results: lithium grades measured by bailers can lead to a robust evaluation of the extractable resources, a conclusion that conflicts with conventional wisdom.CITATION:Séguret, S A, Goblet, P, Cordier, E and Galli, A, 2017. Bailer uncertainty evaluation in a lithium salar deposit, in Proceedings Eighth World Conference on Sampling and Blending , pp 395–402 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By G J. Lyman, S A. Tittlemier

International regulations exist to manage the concentrations of mycotoxins such as Ochratoxin A (OTA) and deoxynivalenol (DON) in grains and prevent health risks from excessive exposure to OTA and DON. Since the permitted levels of these mycotoxins are very low (existing maximum levels are in the range of 5 ppb for OTA and 1–2 ppm for DON), sampling for these mycotoxins is potentially challenging. Given that the distribution of infected kernels in a consignment of wheat can be highly heterogeneous, detection by current sampling methods is subject to a high variance. Furthermore, the concentrations of mycotoxins in individual kernels vary over orders of magnitude, intensifying the heterogeneity of the bulk grain.In these circumstances, there is much interest in developing sampling plans that inform regulatory agencies, and mitigate the risk of misclassifying grain shipments as compliant or non-compliant within the global grain trade, when correctly implemented.Experimental data from laboratory and field studies describing individual wheat kernel concentrations of OTA and DON were combined with experimental data describing the variance due to the analytical methods used for OTA and DON to calculate the sampling distribution for wheat having various levels of contamination. This work has focused on quantifying the heterogeneity of samples at the point of submission for analysis and within subsequent sample preparation to arrive at total sampling distributions that include uncertainties due to the intrinsic heterogeneity and the analytical uncertainties. The sampling uncertainty that relates to the difference between the primary sample analysis and the true lot analysis is not included as it has been dealt with elsewhere.CITATION:Lyman, G J and Tittlemier, S A, 2017. The sampling characteristics of grains contaminated by mycotoxins, in Proceedings Eighth World Conference on Sampling and Blending , pp 281–294 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By B W. Atkinson, J Docherty

An Australian Working Group has been compiling a guide for operators to use in order to improve the efficacy of their routine and non-routine sampling tasks within their coal preparation process. The guide focuses on unit operations within the process, and not conveyor belts or transfer stations that are adequately covered by the existing Standard ISO 13909.Representative sampling of unit operations is generally an after-thought following plant construction, whether that be a result of oversight, or more commonly, capital cost minimisation during initial construction. Minimising capital cost by avoiding adequate sampling systems is generally a poor decision, since the result is a process that cannot be adequately measured, meaning that it cannot be adequately managed and optimised.The use of the term ‘guide’ rather than ‘standard’ is intentional. Practical means of sampling unit operations within existing plants generally relies on a compromise between sample representativity (minimisation of bias) and sampling feasibility. The guide does not endorse poor sampling practice, but instead offers practical guidance to overcome, to the extent reasonably possible, real-life limitations.When it comes to sampling any particular process, it is almost always necessary to make a professional judgement as to whether or not the proposed samples are likely to be sufficiently representative such that the sampling will be worthwhile. Such judgement needs to be exercised by personnel who understand the principles of sampling, as they apply to the stream being sampled. There are many circumstances where available methods for sampling of a particular stream will be meaningless, and in such circumstances analytical data from that sampling will only serve to propagate poor decision-making.This paper outlines the approach for the guide, the areas it covers and the approaches adopted for different types of unit operations and associated equipment configurations.CITATION:Atkinson, B W and Docherty, J, 2017. A practical guide to sampling in coal preparation plants, in Proceedings Eighth World Conference on Sampling and Blending , pp 241–246 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By K H. Esbensen, K Engström

The conclusion from the debate over the last decade in the mining sector is that, for grade control, reverse circulation (RC) drill sampling gives more reliable results due to less sampling problems than blasthole samples. However, by conducting the latter with well-controlled procedures there still exist fair possibilities to counteract the major blasthole sampling problems and achieve fit-for-purpose representativeness, especially if based on minimal loss of fines. In the present PhD study, extensive replicate experiments and variographic characterisations are conducted to evaluate the performance of manual blasthole (BH) sampling and sectorial segment sampling. The experiments were performed in Luossavaara-Kiirunavaara AB (LKAB)’s Leveäniemi open pit mine in the north of Sweden. The experimental area is an apatite-magnetite iron ore deposit of the Kiruna type, with the demand to exhibit a maximum of local heterogeneity to allow the experiment the largest possible conclusion powers. Gathering and splitting the complete BH drill cutting cones (fines cone, coarse cone) served as an authoritative reference on which to assess the representativity of the two BH sampling methods.Results show that manual BH drill sampling is able to produce samples with an acceptable accuracy and precision if performed properly and with insight. Based on variographic comparison, segment sampling shows similar precision for chemical grades as the manual sampling, while the particle size distributions were more deviating for segment sampling than for manual sampling at the high and low size ranges. Possible reasons for these partly surprising results are discussed.For further investigation of the performance of BH versus RC drill sampling, a second experiment has been planned on a parallel profile. This will result in an unprecedented opportunity for a full variographic comparison between RC and BH sampling, aimed at designing specific, fit-for-purpose sampling procedures as a function of ore quality, cut-off grades and important contaminant levels.CITATION:Engström, K and Esbensen, K H, 2017. Blasthole sampling (replicate and variographic experiments) in LKAB open pit iron ore mines – fit-for-purpose representativity?, Australia, in Proceedings Eighth World Conference on Sampling and Blending , pp 85–96 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By R Shaw, M Hidding

The design of primary sample cutters for high-capacity conveyors is critical to achieving a correct sample, both in collecting the sample and ensuring smooth sample discharge flow. Modelling usually occurs at the design stage and requires extensive experience to achieve the correct result. However, it is difficult to confirm the effectiveness of the cutter design until after installation. Even with high-speed video, confirmation of complete sample capture is difficult, especially if the material characteristics change over time. Recent investigation using discrete element method (DEM) simulation to model the flow of the ore into the cutter and observe how it interacts with the cutter has revealed some interesting design requirements not observed in the past. By including DEM modelling, the correct design and optimisation of the cutter can be more accurately determined prior to commissioning.CITATION:Hidding, M and Shaw, R, 2017. Modelling ore flow in the design of high-capacity sample cutters, in Proceedings Eighth World Conference on Sampling and Blending , pp 145–150 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By R J. Holmes

The procedures and equipment used for sampling iron ore process streams have generally improved in recent years. However, there are a number of areas where significant issues still commonly occur, including sampling high capacity streams, sample cutter design and operation, division of primary increments at the secondary sampling stage, the performance of crushers installed to reduce the particle size prior to sample division, and the sample mass that is retained at each sampling stage. These issues of non-conformance with correct sampling principles are caused by factors such as increasing the speed and loading of conveyor belts to increase throughput, which changes the trajectory of the ore stream and may result in an inability of the sample cutter to handle the increased flow rate without sample loss. Failure to sample the entire primary increment stream at the secondary sampling stage is also a common issue as well as failure of crushers to provide crushed products of the required particle size due to ongoing maintenance and/or adjustment issues. These common pitfalls can all be addressed through careful attention to detail.CITATION:Holmes, R J, 2017. Common pitfalls in sampling iron ore, in Proceedings Eighth World Conference on Sampling and Blending , pp 261–264 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017