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By G J. Lyman

Sampling of grain for mycotoxins is challenging in that some mycotoxins, such as Ochratoxin A (OTA), have very low permitted levels and the kernels carrying the mycotoxin may be highly localised within the bulk of the grain as ‘hot spots’. Sampling for genetically modified organisms (GMOs) can be fraught with similar problems, especially if the contamination is adventitious and random. Incremental sampling under these circumstances can be shown to lead to a high variance in the sampling result.A new design of sampler for grain and other free-flowing particulates has been developed that is effective in practically eliminating the sampling variance due to distributional heterogeneity (DH).This paper introduces the design and argues that the sampler should be free of sampling variance due to DH.CITATION:Lyman, G J, 2017. A new sampler for grain and other free-flowing particulates, in Proceedings Eighth World Conference on Sampling and Blending , pp 277–280 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By M D. Sussman

A large number of countries in the world now have some regulation for labelling the presence of genetically modified organisms (GMO) in food. For the last ten years, ISO/TC 34/SC 16 has been providing methods, guidelines and requirements concerning the evaluation of molecular biomarkers including GMOs. This activity makes sure that stakeholders on all sides of commercial transactions are satisfied and their marketing or regulatory needs are met. Developing and maintaining a transparent, science-based environment for users of horizontal methods for molecular biomarker analysis is a high priority. Sampling and analysis of molecular biomarkers has become critically important for food and agricultural organisations developing, producing, distributing and selling genetically engineered, non-genetically engineered, identity preserved and/or organic crops and their derived products and preventing their respective destructive diseases. To aid in international harmonisation, a new work item proposal to develop an ISO type A management system standard (MSS) for organisations including laboratories using molecular biomarker analysis and sampling has been submitted to ISO/TC 34/SC 16. The purpose of this MSS is ensuring that determination of the presence, absence or quantification of a particular biomarker with a relationship to a product quality determinant, a marketing claim, a regulation or a plant pathogen is carried out under a suitable quality assurance / quality control system. This MSS will provide an overarching system to apply and manage molecular biomarker analysis and sampling for any organisation large, medium or small in a private, government or academic setting.CITATION:Sussman, M D, 2017. ISO/TC 34/SC 16 horizontal methods for molecular biomarker analysis – molecular biomarker analysis and sampling management system, in Proceedings Eighth World Conference on Sampling and Blending , pp 295–302 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By P Minkkinen

"Pierre Gy showed in his early works that the results in estimating the variance of the mean value of continuous lots depends on sampling mode (random, stratified or systematic), except in the theoretical case that the measurand is randomly distributed in the lot. The experimental variance estimate calculated from samples taken from the lot is independent of sampling mode but depends on sample size and the type of the lot heterogeneity. Variography can be used to estimate the variance of the lot mean for different sampling modes.Gy also defined weighting error, which is made if a simple average is calculated from the assays of samples taken from a continuous object (eg from a process stream) where the flow rate varies with time and is correlated with the concentration of the analyte in the stream.The effect on sampling uncertainty of the three sampling modes and their interaction with the following factors in estimating the uncertainty of the mean concentration is studied using simulated lots, and lots having heterogeneity patterns similar to those of real data sets, including the effect of: the type of heterogeneity (random, grading and clustered heterogeneity patterns) increment size and number employing composite sampling weighting error. CITATION:Minkkinen, P, 2017. Dependence of the variance of lot average on the sampling mode and heterogeneity type of the lot, in Proceedings Eighth World Conference on Sampling and Blending, pp 319–330 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

May 9, 2017

By A C. Chieregati, A Heberle, F L. S P Villanova

Since the publications of Gy’s initial work, many authors have discussed the approaches to estimate the variance of the fundamental sampling error (FSE). Experimental tests suggested by Pitard and François-Bongarçon determine the sampling parameters K and a to calibrate Gy’s formula. The heterogeneity test and the sample tree method are well known and broadly used for many commodities. However, prior to the analysis, the collection of a representative sample is an intriguingly difficult task. The composite for the heterogeneity tests often consists of run-?of-?mine material or processed ore on a conveyor belt. In most cases the final sample does not have enough mass, mixes different geological units, represents a rare blend and does not characterise the deposit. In order to obtain a reliable composite for trace elements and low-grade ores, sampling practitioners suggest at least half a ton of material.To prevent the common representative pitfalls in the FSE, this case study focuses on a single gold-?bearing geological unit collected in situ. With this unit being structured by the mine geologists, but with the interaction between engineers and chemists, it was possible to validate the reconciliation suggested by Pitard (2015). The heterogeneity test and the sample tree method were performed using 500 kg of a smoky quartz from a single geological domain and the results were compared to Gy’s formula. The logging practice by the geologists was modified, emphasising the definition of the size of the gold nugget or its cluster, number of grains and association. Finally, a mineralogical study was conducted on the geological unit to define the liberation factor. All the information is compiled in this paper, showing the need to fully understand the mineralisation to correctly define representative samples and proper analytical techniques.CITATION:Villanova, F L S P, Heberle, A and Chieregati, A C, 2017. Heterogeneity tests and core logging – a final reconciliation, in Proceedings Eighth World Conference on Sampling and Blending , pp 107–114 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By M Singh, R C. Steinhaus, J J. Rust

Metallurgical process control systems in mineral plants often employ state-of-the-art monitoring analysers in an attempt to optimise plant operations and enhance mineral recoveries. These systems are unfortunately invariably fed by simplistic ‘sampling’ designs consisting of various in-stream methods or pressurised probes. These are unfortunate compromises and provide a false picture of what a mineral flotation or other process can achieve. The situation is further aggravated by some manufacturers using misleading marketing to suggest discrete cross-stream methods for metallurgical accounting and unreliable continuous in-stream off-takes for control sampling and that they are of synonymous integrity.Reliable, absolute or representative samples are often absent in many modern day concentrator plants, due to compromises around sample taking, particularly in terms of delineation and extraction errors and thus leading to sample bias. For more reliable information from online analysers we need a continuous, but much more reliable sample taken, than is current practice.Online analysers require a fully proportional and continuous supply of sample for effective process control, otherwise maximised or benchmark recoveries will be nothing but a pipe dream. Large discrete cross-stream samples from mechanically less reliable equipment cannot be used as feed to online analysers, as it will negatively impact real-time feedback and efficient process control.It is possible to build correct sampling systems that could do both process controls online and metallurgical accounting at the same time. Multotec Process Equipment (Pty) Limited, in close association with experienced sampling consultant Francis Pitard, have jointly patented a concept to achieve this and which is embodied in the design of the unique Rotating Cone® Sampler (International Patent Application No. PCT/IB2016/057464). This versatile unit for dry and wet applications has high division ratios via two-step sampling and division.A prototype was built and tested to validate the design and levels of precision achievable when employing the unit to split dry mineral fines or even certain foodstuffs.CITATION:Steinhaus, R C, Rust, J J and Singh, M, 2017. Does process control sampling always have to be a compromise?, in Proceedings Eighth World Conference on Sampling and Blending , pp 197–202 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By S C. Dominy

This contribution examines the effect of feedstock sampling before the sorting stage of polyethylene terephtalate (PET) bottle recycling. Batches of waste PET bottles may contain non-PET bottles which need to be removed by sorting. Any residual presence of PVC is detrimental for the quality of products manufactured from recycled PET. The maximum tolerated concentration of PVC in cleaned PET is extremely low, which places high demands on the recovery of PVC achieved by sorting. To be confident of attaining the desired PET quality after sorting, acceptance sampling of truckloads of PET bottles may take place prior to sorting. It is shown that accounting for sampling uncertainty requires that the sorting process achieves a consistently high recovery of PVC bottles.CITATION:Glass, H J and Dominy, S C, 2017. Plastics recycling and sampling, in Proceedings Eighth World Conference on Sampling and Blending , pp 129–134 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By N H. Jansen, H L. Bridgwater

Field portable X-ray fluorescence (XRF) and near infrared (NIR) instruments are proven technologies in the minerals industry. The in-field results of these instruments can add value early in the project life, leading to cost-effective decision-making compared to their equivalent laboratory based techniques. However, in order to add value to a project, it is crucial that the instruments are employed correctly.Orientation studies should be carried out prior to initiating a sampling program to achieve the highest level of quality assurance and control for the results. Hence, an appropriate sampling workflow begins with considering what outcomes are required, including level of precision, accuracy, reliability for elements and minerals of interest, and sampling errors. The workflows proposed include soil sampling and reverse circulation and diamond drilling sampling techniques, and laboratory based techniques. They are practical and flexible workflows using available portable XRF and NIR technologies that can be applied to current sampling and drilling methods.The combined technologies have the ability to create large, integrated geochemical and mineralogical data sets that can provide cost savings for every stage of the mining chain from exploration to prefeasibility, mineral processing and environmental remediation.CITATION:Jansen, N H and Bridgwater, H L, 2017. Proposed workflows for portable X-ray fluorescence and near infrared instruments for soil and drill hole sampling, in Proceedings Eighth World Conference on Sampling and Blending , pp 219–228 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By A Hollweg, K H. Esbensen, M Lischka

Two new splitter designs for intercepting moving streams of matter are presented, the variable cross-stream splitter (vCSS) and the rotary stream splitter (RSS), which are intended for implementation in a fully automated modus. The vCSS facilitates obtaining up to three subsamples with different splitting ratios from automated laboratory flow paths, while the RSS divides the intercepted sample into 16 equal analytical aliquots. The splitters can process a wide range of dry, granular and free-flowing materials (<5 mm). The required weight for each subsample can be set without mechanical adjustments in the case of the vCSS. Typical applications are subsampling/splitting for X-ray fluorescence pelletisation (or fused beads) or splitting for average shift composite sampling or grain size analysis. The vCSS combines the advantages of riffle splitting (three user-defined subsample masses) with miniature bed blending and can accept up to 15 kg in total incoming sample mass. In practice, the automated vCSS can deal with unlimited ingoing mass fluxes, while the RSS is designed to operate at a user-defined fixed subsampling rate (1/16th in the tested version). Both splitters have the potential to be optimised and evaluated according to an application/user-defined total sampling error (TSE) + total analytical error (TAE) threshold. Both splitters were tested under adverse conditions and with compositions involving three components with properties representing typical mass fluxes and components concentrations in industrial and technological systems: phosphate concentrate 89.00 per cent (<500 µm), slag ten per cent (>2 mm) and glass spheres one per cent (750–1000 µm). The slag particles vary widely in particle shape, aspect ratio and surface roughness, while the glass spheres are extremely prone to bouncing and segregation (spillage). This test system is extremely difficult to split and thus constitutes a realistic worst-case scenario. While the vCSS does not comply strictly with Theory of Sampling demands for correctness, both splitters may well be able to deliver fit-for-purpose representative results if/when tested properly. Average relative mass deviations ranged from 1.89 per cent for phosphate concentrate (relative standard deviations of 20-fold repeated splitting) to 4.72 per cent for glass spheres and 13.04 per cent for slag. For the RSS, the average replication experiment splitting variation was 2.89 per cent for phosphate concentrate, 4.82 per cent for glass spheres and 11.1 per cent for slag. Both new automated online splitters would therefore appear to be able to be tuned to fit-for-purpose representivity (defined here as maximum relative reproducibility <5 per cent) for many non-extreme materials; however, it is always imperative to test every new type/class of material empirically. There is a wide commercial potential for important materials and commodities sectors, including food, feed, drugs (pharmaceutical), secondary raw materials, recyclates, agricultural products and seeds.CITATION:Lischka, M, Hollweg, A and Esbensen, K H, 2017. New online/atline splitter designs for laboratory automation – feasibility results, in Proceedings Eighth World Conference on Sampling and Blending , pp 159–166 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By B Chi, A Mahanta, R A. M Maddever, O Dominguez

BHP Billiton, in collaboration with Sodern and CSIRO, has developed a downhole logging tool for measuring geochemistry in situ. The FastGradeTM 100 (alternatively, FG100), exploits pulsed fast and thermal neutron analysis (PFTNA) to analyse the rock. This method is based on the detection and measurement of characteristic gamma rays emitted from isotopes in the material that become briefly radioactive when they are bombarded with neutrons. The tool outputs raw spectra arising from three types of neutron interaction, namely, inelastic scattering, neutron capture and neutron activation, which occur in successive time-windows (Smith et al, 2015). The spectra contain peaks at specific energies that are characteristic of the different elements interacting with the neutrons, the gamma count of which is related to elemental concentration. BHP Billiton uses in-house data processing software to convert the measured spectra to elemental concentrations.Much work has been done to understand the tool response under a wide variety of environmental and operating conditions, including logging speed, borehole rugosity, the presence of cavities, water etc. Effort has also been directed at understanding and quantifying the current sources of error in our conventional assays due to sample collection, preparation, and laboratory instrumentation in order to use this information as a baseline to compare against the FastGradeTM 100 results.To date, the FastGradeTM 100 primary use has been as a verification tool (JORC, 2012). However, beyond this, it has considerable potential to improve productivity in both exploration and production environments due to its ability to provide geologists with assay results soon after a hole is drilled.This paper presents initial test work and tool performance, including accuracy and precision under various conditions. Results are illustrated by comparing tool measurements to assays from laboratory samples collected from both reverse circulation and diamond-drilled holes.CITATION:Chi, B, Maddever, R A M, Mahanta, A and Dominguez, O, 2017. Near real-time assay with downhole assay tool (FastGrade™ 100), in Proceedings Eighth World Conference on Sampling and Blending , pp 137–144 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By S C. Dominy

Various styles of gold mineralisation pose problems during sampling because of their complex gold grade distribution and presence of coarse gold. Effective sampling and sample preparation forms the basis of resource estimates. The design of a sampling and assaying protocol must be based on a thorough understanding of the mineralisation in question, which should include consideration of gold particle size and mass distribution. The proportion of coarse gold within samples has a profound effect on the requirements for sample preparation and assaying. Choice of preparation procedure and assay type is of critical importance if sampling errors are to be minimised. Traditional fire assays, using small charge sizes, often understate assays gained from large charge sizes and techniques such as screen fire assay and LeachWELL. Proper application of the Theory of Sampling reduces errors during collection, preparation and assaying. A quality control/quality assurance program must be implemented and critically assessed. A case study from the Ballarat mine is presented, which is characterised by substantial quantities of coarse-gold hosted in quartz veins. Diamond core drilling is the key input into resource delineation. A number of different sampling and assay options have been trialled over the recent project history. The current sampling protocol utilises whole drill core, using LeachWELL assays after logging and photography.CITATION:Dominy, S C, 2017. Sampling coarse gold-bearing mineralisation – developing effective protocols and a case study from the Ballarat mine, Australia, in Proceedings Eighth World Conference on Sampling and Blending , pp 71–84 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By C Haughy, F F. Pitard

Blue Mountain Minerals is a large supplier of calcium carbonate products used by various manufacturers as a major raw material. Very small amounts of free carbon in the rock can have a huge impact in carbon-sensitive applications. The marble in the deposit at Blue Mountain Minerals contains variable amounts of free carbon in the form of trace amounts of the mineral graphite.To make quality improvements, variography was used to measure the impact of non-ideal sampling practices at the Blue Mountain Minerals operations in Columbia, California in the United States. A major investment in correct sampling systems and sampling protocols was implemented over a one-year period. Subsequent variography was used to measure the improvement on the predictability of the graphite content in marble produced by the quarry and as it is processed as an acceptable raw material for extremely carbon-sensitive applications. The improvements of the sampling protocols, control of long-range changes and better knowledge of process cycles are easily noticeable on variograms when they happen to exist. The economic impacts are discussed.CITATION:Haughy, C and Pitard, F F, 2017. Use of variography to measure improvement of sampling practices for the quality control of graphite consistency in marble used for carbon-sensitive applications, in Proceedings Eighth World Conference on Sampling and Blending , pp 255–260 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By D A. Vogel

"Sampling may be mandatory for safety or environmental reasons. It may be because the value of a sale needs to be determined or to provide important data for investments. Whatever the reason, an incorrect sample will come at a risk. Only the person that relies on sampling data can imagine what the potential cost of such risk is.Sampling itself has a cost too; the direct cost of a quality control department and indirect cost for interrupting a process, such as stopping a conveyor belt during loading. If all material is the same then only one small sample is enough. But if all the material is different, then a very large sample must be tested; in the conveyor belt scenario it must be stopped very frequently and the associated cost will be high.A good sampling plan finds the proper balance between risk and cost. A good sample must be small enough to handle yet large enough to be representative for what information is required. All good samples have three things in common: there was proper access to the material the sampling tool allowed equal probability of particles being selected nothing was disregarded, everything was included.This too is the core of Gy’s ideal sampling scenario, where all particles have the same probability of being selected and included in the sample. There is risk of bias when part of a lot is excluded from the sample. Extra care is needed when sampling particularly heterogeneous, segregated or layered materials. The sampling tool should never systematically leave out a portion; it shall not push aside large or hard particles. Wet samples shall not stick to the sampling tool. This extends to sample preparation too when reducing particle size and dividing the sample in the process.CITATION:Vogel, D A, 2017. Access, select, include – a review of the commercial sampling of traded bulk commodities in the context of Gy’s Theory of Sampling, in Proceedings Eighth World Conference on Sampling and Blending, pp 367–378 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

May 9, 2017

By L Kempenaers, T van der Maten, U König, M G. C Zoontjes

Improving liquid blending operations in production plants is of paramount importance in many industries like mining, oils, petrochemicals and food. For accurate blending of different types of process streams, like homogeneous, heterogeneous, cold or hot streams, it is essential that the composition can be accurately monitored in real time. Advances in energy dispersive X-ray fluorescence (EDXRF) technology offers the possibility to apply XRF for online elemental analysis. In this paper we discuss an online EDXRF analyser for accurate blending control in many industries.EDXRF has the advantage that multiple elements can be measured simultaneously over a wide concentration range of wt per cent down to a few mg/kg, for elements between sodium (Na) and americium (Am) in the periodic table. To reach the desired accuracy and precision in an online XRF analyser, it is important to bring a representative and homogeneous sample of the process flow into the optical path of the analyser. The combination of a laminar flow cell design and advanced EDXRF technology leads to low detection limits and high performance. The obtained precision and accuracy allows for much tighter process control. In this paper we present two examples of industrial applications.CITATION:Zoontjes, M G C, van der Maten, T, Kempenaers, L and König, U, 2017. Online X-ray fluorescence spectrometer for accurate monitoring and improving blending sharpness in liquid production processes, in Proceedings Eighth World Conference on Sampling and Blending , pp 235–238 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By T M. El Hajj, A C. Chieregati, M T. G C Marques, J M. Braga Jr, H Delboni Jr

"The estimate and control of sampling errors is essential for all mining operations, especially when dealing with strategic materials, such as niobium. This paper is based on a traditional quality assurance and quality control technique used to confirm mineralised intersection zones, and proposes the validation of sampling data using diamond drill twin holes, in order to evaluate and improve the quality of the current data set. The geological model of the niobium mine – located in Araxá, Minas Gerais, Brazil – was built including 77 diamond drill holes of a sampling campaign carried out during the 1970s. There are few records about the collection and preparation procedures of these past samples, making it difficult to estimate the errors associated with their analytical results. Therefore, 11 twin drill holes were drilled to compare their samples against the samples from the 1970s drilling campaign. The new hole locations were chosen as near as possible to the old holes location. The JORC Code, 2012 edition, relates the use of twin holes as a good sampling technique to assess sampling and assay data. Three parameters were considered to validate the 1970s drill hole campaign by the twin drill hole campaign: the difference of the coordinates between the paired holes the difference among the positions of the geological contacts to validate the geologic description the difference between the paired samples grades was calculated to validate the analytical results.The analysis of the grade range variation between sample pairs was based on three techniques: geostatistical interpretation of vertical semivariogram to obtain the nugget effect calculation of the relative difference between duplicates calculation of the error associated with the sampling protocol established according to Pierre Gy’s Theory of Sampling.The results were satisfactory for hole coordinates; however, the ore content showed a high deviation, although this divergence can be explained by the nugget effect. For the lithological intervals, the new results contributed to an effective identification of variations among lithologies, ie brown weathered ore and saprolite. The twin drill holes campaign successfully validated the geological model data, allowing effective mine planning and higher reliability of the reconciliation results.CITATION:Marques, M T G C, El Hajj, T M, Braga Jr, J M, Chieregati, A C and Delboni Jr, H, 2017. Theory of Sampling and geostatistics for twin drill holes analysis in a niobium mine in Araxá, Brazil, Australia, in Proceedings Eighth World Conference on Sampling and Blending, pp 97–106 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

May 9, 2017

By J Loimi, P Minkkinen, T Korpela

The head loss caused by metallurgical sampling for slurry streams can be reduced by metallurgical sampler design. When the process volumetric flow rate is reduced by vertical static cutters before the sampling by an equal number of moving cutters to the static cutters, the installation requires less installation head space than other sampling arrangements and is easy to accommodate at suitable locations in the process. Low head loss reduces building costs for the processing plant and operational costs during the lifetime of the plant.The presence of a possible systematic bias in the particle size distribution, solids density and elemental composition between an Outotec MSA 2/50 metallurgical slurry sampler sample and MSA 2/50 manually sampled reject have been studied by a customer. The paired samples were taken as simultaneously as possible. The customer evaluated the possible bias using a paired t-test and provided the assay results to Outotec for further evaluation.The results of the paired t-test showed no systematic bias in particle size distribution, solid density or assayed analytes, except in one analyte with low content and a high relative error. The high relative error in one analyte may have been caused by the same calibration model used in a X-ray fluorescence analyser for both high elemental-content concentrate and very low elemental-content tailings samples. The sampled stream is the tailings of a previous process stage.The results of the t-test were studied further using analysis of variance to reveal the error sources in samples. The results showed no bias between the samples collected from the MSA 2/50 reject and composite samples collected of the MSA 2/50 sample stream. The courier online analyser data was also available for evaluation of representativeness to the process stream.The analysis results of the courier online analysis reveals no bias between the MSA 2/50 reject samples, MSA 2/50 sample stream composite samples and online analysis results during the comparative sample collection period.CITATION:Loimi, J, Minkkinen, P and Korpela, T, 2017. Comparative evaluation of manual sampling and Outotec MSA 2/50 metallurgical slurry sampler, in Proceedings Eighth World Conference on Sampling and Blending , pp 167–172 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By F F. Pitard

The comparison between J Visman and C O Ingamells’ works with P M Gy’s works has been the object of intense debates in the past. Such negative debates inevitably resulted in a loss of many good opportunities. The author’s long experience in applying works of these three authors led to the pragmatic conclusion that it is relatively easy to integrate everything Visman and Ingamells created into the Theory of Sampling; therefore, it is suggested that the compatibility has been vastly overlooked, and a correction for such anomaly is recommended. It is important to emphasise that Visman and Ingamells works may be beneficial and provide relevant, harmonious additions in some areas, and ultimately offer attractive possibilities to sampling practitioners. Such additions may enhance our capabilities to predict sampling difficulties by using a stronger strategy and to design better sampling experiments that would allow us to further understand the heterogeneity of minor constituents, and especially trace constituents. Basically, the suggested integration is essential for sampling trace constituents in the environment, in food, in chemicals and in the pharmaceutical industries.CITATION:Pitard, F F, 2017. Integration of Visman and Ingamells’ works into the Theory of Sampling – a necessity to expand possibilities in sampling practices, in Proceedings Eighth World Conference on Sampling and Blending , pp 55–62 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By M P. Cipold, J F. Bachmann, C C. Bachmann, J Ha, H B. Wurst

In washability, the objective is to establish the set of maximum possible separation performance criteria for a given mineral feed. The method of choice for this has been the conventional sink–?float analysis. Using traditional sink–float method it is not possible to sample and automatically measure. This fact, as well as time, cost and safety aspects, as well as required and manageable sample size of the sink–float method have prompted the search for a new approach for establishing separation performance criteria. This is especially important as performance levels of separator plants can be maximised if reliable information based on an analysis of washability in conjunction with particle size distribution, elemental constituency becomes available in time. The new method to establish washability and associated performance information utilises at least two measurement technologies concurrently: single energy X-ray transmission and image processing. For porous or very inhomogeneous materials the results can be refined further by using dual energy X-ray transmission and image processing.If used as a standard laboratory device the continuous build-up of the washability curve allows to evaluate the statistical significance of the sample size during measurement.The measuring method can even be improved if it is combined with an automatic sampling system that feeds a continuous and representative particle stream to the analyser. Then the value of the collected data increases considerably since the washability data are additionally available in time to be considered in the control of the process plant. The washability curve can be derived and is continuously updated based on the particles measured during the past time interval. Older curves and results are stored in a database and can be retrieved for later reference. This technology now enables automated sampling and integrated automated measurement, which was previously not possible.This incorporation of an automated washability monitor at a representative sample gives near real-time data that would impinge positively on the profitability of the plant operation. The method was extensively tested using a range of samples with different densities, varying from 1 g/cm3 (coal) to 5 g/cm3 (iron ore).CITATION:Bachmann, C C, Bachmann, J F, Cipold, M P, Wurst, H B and Ha, J, 2017. Inline analysis of washability parameters for process control, in Proceedings Eighth World Conference on Sampling and Blending , pp 213–218 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By L O. Filippov, Q Dehaine

Variographic analysis, a classical tool from the Theory of Sampling (TOS), can address practical situations with multiple variables; however, its application has very often been limited to one variable at a time. Recent developments have shown the benefits of using multivariate approaches for variographic characterisation of a set of variables instead of considering individual variables sequentially. Among these approaches, the multivariogram has been revealed itself to be a powerful tool when the overall time-variability of a process must be summarised in terms of a large set of properties (variables) to assess its true global variability. However, even when choosing the properties of interest carefully, the resulting global variance obtained with this approach may be very high. In particular, some variables that contribute to a major proportion of the global (multivariate) variability could be less important for the process performance than others having a lower variability. To address this issue, a new approach is proposed, combining the multivariogram with process modelling and multivariate data analysis methods such as partial least squares (PLS) regression from chemometrics. An example from the mineral processing industry is presented, for which the process performance could be linked to key process variables (sensor data) using the PLS regression. Once introduced in the multivariogram equation, PLS model parameters (loading-weights or regression coefficients) can be used to weigh the variables according to their relevance for the process. In addition, this also permits characterisation of process performance variability with time using only the process input variables and a weighted metric according to the PLS regression model. Ultimately, this method helps to find an optimised sampling procedure in terms of frequency, sampling mode and number of increments according to the actual overall process performance. This approach has potentially many applications in the mining, feed and food, pharmaceutical or any other industry for which it can be used to reduce risks and ensure a better use and management of resources.CITATION:Dehaine, Q, Filippov, L O and Glass, H J, 2017. Optimising multivariate variographic analysis with information from multivariate process data modelling (partial least squares regression), in Proceedings Eighth World Conference on Sampling and Blending , pp 381–390 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By G Gilchrist, S C. Dominy, T Jashashvili, R C. A Minnitt

The grouping and segregation error is one of Gy’s seven errors that cannot be measured in any qualitative manner because of its transient and changing characteristics each time the sample is handled mechanically. Attempts to calculate the mean and variance of the segregation error is considered by some as ‘an exercise in futility’ that would not help us achieve representative sampling. This research is aimed at understanding the process of segregation of dense, finely divided and dilute particulate materials supported in a clean quartz substrate during intense agitation. Several mixtures of fine-grained materials including steel, tungsten carbide and gold grains were used in these experiments. Four hundred grains of each of the minerals and metals at a top size of 2 mm were mixed with approximately 600 g of finely ground quartz material (95 per cent passing 2000 microns) in a 500 ml plastic jar with a sealable lid. The mineral–?metal mixtures were analysed in three steps using microfocus X-ray computed tomography. Step one consisted of rolling the containers on a flat surface in an attempt to concentrate the mineral and metal grains in the core of the supporting substrate; this is a base case that can be reconstructed after each session of analysis. The second step involved gentle and vigorous shaking of the mixtures in order to segregate the denser minerals and metals from the supporting quartz substrate. In some cases, a third step involved splitting the sample through a riffle splitter. Three-?dimensional images of the surface of each grain, its volume and its X-, Y- and Z-coordinates, before and after intense agitation of the container, were interpreted from the reconstruction of the tomographic X-ray data. The spatial analysis of grains using cell declustering and 3D variography provided a useful means of characterising the distribution of the grains in space and the extent to which they had become segregated during the process of agitation. Spatial analysis indicates that in general, grouping and continuity of grains is weakly developed. The modelled nugget effect remains high for most tests, indicating that grains of similar size did not group together strongly. Agitation through rolling provided the best continuity, although not consistently in the long axis of the plastic jar. The nugget effect was consistently highest, and the range of continuity shortest in samples that had been split, indicating that the grouping and continuity were reduced through splitting the sample. Initial results indicate that very little segregation of the minerals and metals occurs in the quartz substrate. This is somewhat counter-intuitive, but suggests that the effects of agitation on mixtures of dense minerals and metals in substrates of lower density do not lead to excessive segregation. Differences in behaviour between dense materials in response to agitation are evident. Grains of different composition and shape did not group and segregate in a predictable manner in response to the agitation methods. Initial results indicate that the degree to which a material groups and segregates relates more to the characteristics of the denser material itself, rather than the agitation method employed.CITATION:Minnitt, R C A, Jashashvili, T, Gilchrist, G and Dominy, S C, 2017. Quantifying segregation of minerals and metals in particulate materials using computed X-ray tomography and variography, in Proceedings Eighth World Conference on Sampling and Blending , pp 173–182 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

By I Clark, S C. Dominy

Bulk sampling programs are typically applied in coarse gold mineralised systems to verify resource/reserve grades. In recent years, there have been controversies surrounding some results of underground bulk sampling exercises compared to the predictions using diamond drill data. Just how realistic is it to predict 100 t lots from drilling that was designed to model blocks of several thousand tonnes? This study looks at the variation of relatively small units within larger planned mining units and compares some of the geostatistical techniques which purport to provide tools for such studies. Relative difficulty of application, computer timings and summaries of results will be used to illustrate the likely variation in bulk sampling units as opposed to mining units and large-scale planning units. A case study based on publicly available data from a gold project in North America is presented. A simplistic and unconditional geostatistical simulation model demonstrated that up to 50 per cent of a relatively high-grade mining block could show as uneconomic low-grade subblocks. A subsequent study will consider a similar demonstration using uniform conditioning. Erroneous impressions of early sampling results can lead to unsupported prejudgements of the final results. Bulk sampling programs require detailed planning based on ore characteristics, where protocols must fit the mineralisation type. Any program requires definition of aims and data quality objectives across grade, geological, geotechnical and geometallurgical parameters.CITATION:Clark, I and Dominy, S C, 2017. Underground bulk sampling, uniform conditioning and conditional simulation – unrealistic expectations?, in Proceedings Eighth World Conference on Sampling and Blending , pp 3–20 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017