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By Pierre-François Bareel

EU legislation imposes ambitious recycling targets for various consumer goods. End-of-Life Vehicles (ELVs), scrap iron and various proportions of Waste Electrical and Electronic Equipment (WEEE) are processed by shredding plants which recover most of the metals but produce Shredder Residues (SR) which are landfilled. They represent 20 to 25 wt.% of the shredder input. Energy issues for the coarse fraction of SR are now largely studied. However, below 2 mm, the calorific value falls off drastically. These Fine Shredder Residues (FSR) represent up to 55 wt.% of the total SR. To meet European objectives other alternatives to landfilling must be considered for the FSR. The present paper describes a study carried out to characterise the FSR and investigates ways to process them and produce marketable products. Applying Gy's theory, a sampling procedure was conducted over two years to statistically quantify the variability of the physical and chemical properties of FSR produced by a Belgian post-shredding treatment plant. Macroscopic characterisation has led to the identification of four material categories which could be separated according to their physical properties: ferrous metals (more or less oxidised), non-ferrous metals, an organic fraction (plastics, rubber, textiles, foams, wood) and a minerals fraction (glass, ceramic, concrete). The entrainment of small metallic particles within the pores of organic fragments will affect the quality of the separations.

Jan 1, 2006

By U. Meyer, A. Alonso, P. Banios

The sampling of cathodes has changed with the introduction of the ISA-process in copper refineries. A Jernkontoret joint working group of refineries and rod plants from both primary and recycled copper plants has been investigating whether the actual sampling of cathodes is representative for this type of cathodes. As a first stage, samples were sent to the members of the working group with the objective to find an easy basis for a comparison of the results of the next stages. All samples show the same tendency for nearly all elements. In some cases, there may exist differences in calibration and for some elements the detection limits are too high, especially when Optical Spectrometry is used. In the second stage, discs were compared with melted samples to answer the question whether the punching of discs is sufficient for the quality control of the cathode. The analyses of the discs represent fairly well the cathode quality. There are differences between cathodes from different crops. Three punches are sufficient to determine the cathode quality. Finally, samples from various lots of cathodes were compared with samples from the rod produced from these cathodes. The impurity content of the rod corresponds to the impurity content of the cathode.

Jan 1, 2000

Sampling is an integral part of gold bullion analysis. Gold mining industries sell millions of dollars worth of gold on the basis of analyses. Biased sampling can cause a serious loss in terms of monetary value to a mining company; hence accurate sampling is of great importance. The sampling procedures for gold bullion will be described. Emphasis is given to the most reliable method of obtaining a representative sample from a gold bar. The problems associated with sample preparation will also be discussed.The sampling procedure at the Kalgoorlie Metallurgical Laboratory will be evaluated in the light of comparative results from the Australian Gold Refineries (Perth, Kalgoorlie). The most common sampling practices adopted by different gold mining companies in the Goldfields and Australian Gold Refineries, Western Australia will also be presented.

Jan 1, 1976

While sampling techniques used by the mineral industry continue to improve, sampling is still an area which is often neglected. It is often left to personnel who do not fully appreciate the significance and importance of sampling. Yet sampling and sample processing are of vital importance. There is little point in making major capital investments in the latest analytical equipment and spending considerable time obtaining the best analytical precision, if the sample provided for analysis is seriously biased in the first place.

Jan 1, 1976

By C. H. J. Beaven, M. P. Jones

Since the various new techniques of automation and computing have enabled vast numbers of mineralogical observations of relatively small samples to be made cheaply and rapidly, the statistical assessment of these measurements has become of vital importance. Much of the theory and most of the procedures of sampling that are used in the mineral industry are based on Gaussian statistics, but modern measuring techniques show that many mineralogical parameters do not necessarily follow the Gaussian distribution function. Consequently, it has become necessary to examine the application of other, more suitable statistical methods in order to derive the maximum amount of useful information from the examination of mineralogical samples. Some of the errors that can be introduced by the use of incorrect distribution functions are discussed and the value of determining the function that is appropriate to the particular parameter that is being measured is shown. Examples are provided of non-Gaussian distribution functions in mineralogical materials that were encountered during prospecting and during mineral treatment operations: a Canadian uranium ore, a Thai tin ore, and gold ore tailings.

Dec 1, 1971

By K. I. Afewu

A modified approach to the implementation of Gy?s sampling theory is discussed and used to design a procedure for sampling crushed gold ore feed to metallurgical process plants. The approach involves calibration of certain ore-specific parameters. These parameters were calibrated for two different crushed gold ores en route to grinding mills in process plants. The model predictions were compared with the predictions from Gy?s original model. Far smaller masses of samples are required by the modified model than by Gy?s model at the same relative variance. The representativeness of the sampling procedure if normally distributed errors are assumed was also calculated. These procedures and evaluations lead to significant savings on cost of handling and preparation of the samples and to a quantifiable degree of confidence in the analytical results for the process plant.

Jan 1, 1998

Prior to 1975, most geochemical drainage surveys for gold were based on analyses for pathfinder elements, such as As and Cu, rather than direct analysis for gold, for two reasons. Firstly, analytical methods lacked the required sensitivity and precision to determine gold abundance at background levels in stream sediments (usually in the range 1 - 10 ppb). Direct analysis was also inhibited by concern about the potential for gross sampling error, brought about by the dispersion of gold as rare discrete particles of the extremely dense native metal. This sampling error, commonly termed the 'nugget effect' has two components: erratic distribution of the element within the stream environment, related to hydraulic factors, and the difficulty in taking representative samples, both in the field and later in sub-sampling for analysis. In more recent years the collection of very large samples was commonly advocated to overcome the sampling problem (Hams, 1982; Nichol, 1986).Two methods have been widely used to evaluate the gold content of bulk samples (Elliott and Towsey, 1989). The preparation and analysis of heavy mineral concentrates has in recent years been largely superseded by the leaching of gold contained in bulk samples by cyanide, commonly termed the BLEG (Bulk Leach Extractable Gold) or BCL (Bulk Cyanide Leach) methods. The terms BLEG and BCL are essentially interchangeable and the latter will be adopted for the remainder of this paper. The strengths and weaknesses of these two techniques were compared with conventional total gold analysis on fine fraction (

Jan 1, 1976

By Allchurch P. D

At Perseverance a reserve of 45 million tonnes at 2% Ni was indicated by drilling. Holes were drilled in trellis pattern on section lines 61m apart to assess shallow mineralization. To explore at depth holes were spaced 122m apart, collared vertically, then allowed to deflect under controlled drilling conditions. The mineralization may be divided into the three homogeneous classes of soarsely disseminated, heavily dissem- inated and massive sulphides. In the standardised sampling and assaying procedures used to assess the deposit, attention was always paid to these fundamental ore types. All sampling and assaying processes were continuously monitored by checks. Sampling and sample preparation errors were small, to judge from the differences between results of original and check samples. Assaying errors, determined from analyses made by independent laboratories using different methods, slightly exceeded sampling errors. Comparison of underground core, c'iannel, and grab sampling, suggests that core sampling tends to undervalue.

Jan 1, 1976

The discovery of economic uranium miner alisation in unique geological conditions at Yeelirrie, 700 km NNE of Perth, presented Western Mining Corporation Limited with a num- ber of sampling and evaluation problems. Carn- otite mineralisation occurred in a porous cal- crete-clay lithology in close proximity to the water table; background information on such a deposit was non-existent and sampling in these conditions could be difficult. The deposit was sampled initially by aug- er drilling with X-ray fluorescence analysis of drill cuttings, followed by reverse circulation and diamond drilling with analyses by X-ray fluorescence and gamma logging of the holes. Two costeans provided lithological and grade distribution data and mining experience in the deposit. Spoil from the costeans was stockpiled according to location in the first costean and according to location and grade in the second costean. Samples from the various stockpiles were analysed by X-ray fluorescence. No. 1 costean was extensively sampled by channel sampling of the walls and by pit sampling of the floor of the benches of the costean by back hoe. No. 2 costean was sampled by Geiger counters mounted in T-probes and by the gamma logging of auger holes to establish the valid- ity of the T-probe results. Samples were taken

Jan 1, 1976

By Francis F. Pitard

The presence of elements, minerals, or chemical compounds in materials at very low concentrations is becoming a constantly increasing concern for several segments of the Industry. Some trace elements or chemical compounds may be considered as hazardous, some are simply considered as undesirable In complex processes where they could be constantly recycled and end up as the major factor of decreasing quality for some valuable products. In some other cases, the presence of a trace element or mineral may be highly desirable because of its economical value: precious metals are falling into this category, they probably were the first trace elements to draw our attention. Tremendous quantity of money is spent for analysis at the trace level, also the analytical "tool" has been considerably improved during recent years, but still the sampling aspect of the problem remains obscur for many, and because of it, large quantity of analytical efforts become meaningless. Not only the absence of sampling strategies is badly affecting the representativeness of a large majority of samples, but furthermore for the same reasons, many laboratories are failing In their endeavor to prepare reliable standard reference materials. The reason of this failure has its roots in the unability to estimate effectively the sampling characteristics of the element, mineral, or compound of interest, not to mention the unability to perform precise and accurate complete analysis, so essential for the instrumental analyst (1). In this paper a strategy to perform a better sampling operation is recommended. SELECTION OF A PROBABILISTIC APPROACH AS SOON AS PRACTICALLY POSSIBLE It Is essential to differentiate probabilistic sampling from non-probabilistic sampling. As Illustrated in Figure 1, the sampling operation Is a selection process which could be performed In two different ways: I. A probabilistic selection process according to which all elements of a lot of material to be sampled are submitted to the selection with a same probability of being selected. 2. A non-probabilistic selection process according to which all elements of a lot of material to be sampled are submitted to the selection with different probabilities of being selected.

Jan 1, 1986

By Baafi EY, Appiah HK

The Prestea Goldfields Ltd of Ghana, West Africa has produced over 170 t of gold with average grade of 11 g/t since 1912. The deposits occur in a wide shear zone which closely follow the Birimian-Tarkwaian contact. Both the Birimian and Tarkwaian systems are of Precambrian age. Underground exploration is carried out to delineate ore bodies by means of AX size diamond drilling at 50 m sampling intervals. After the orebody has been delineated, development work is carried out by exposing the gold reef. Channel sampling is then carried out at about 3 m intervals in both the stope and stope drives. A channel sample length is commonly 0.6 in, but may vary depending on physical characteristics of the reef. The values of channel samples are linearly combined to obtain the average reef or slope values and/or widths of the exposed sections. The sampling practice and methods of improving the efficacy of sampling at the mine are described.

Jan 1, 1976

The efficient and profit-maximising daily and long-term management of the Vera Nancy resource depends on decisions based upon assay data. This paper examines the range of sample sources, the methods of sample collection, assay techniques and Quality Assurance used by the mine. The orebody has a relatively low nugget effect for a gold mine (around 25 per cent) and this greatly assists in reducing sampling error and producing reliable assay data for production decision-making. Reconciliation between mine and back-calculated mill grades generally sees the mine under-calling mill grades by around four per cent.

Jan 1, 2000

By Mark W. Springett

The sampling of precious metal deposits entails inherent problems due to the low mineral abundances, high mineral specific gravities, skewed grade distributions and wide ranges of mineral particle sizes. Sampling practices and precautions are discussed with particular attention to each of the tripartite stages of sampling - sample acquisition, sample preparation and sample assaying. Practical examples of approaches to the sampling problem are given and some examples of significant sources of error are provided from gold and silver deposits in North America.

Jan 1, 1984

By Mark W. Springett

The sampling of precious metal deposits entails inherent problems due to the low mineral abundances, high mineral specific gravities, skewed grade distributions and wide ranges of mineral particle sizes. Sampling practices and precautions are discussed with particular attention to each of the tripartite stages of sampling - sample acquisition, sample preparation and sample assaying. Practical examples of approaches to the sampling problem are given and some examples of significant sources of error are provided from gold and silver deposits in North America.

Jan 1, 1992

By Mark Springett

The problems inherent in sampling low- grade deposits have long been recognized. As economic grades become lower with increasing metals prices and improvements in recovery technology then the previously difficult sampling problem has consequently become even more demanding. The breakdown of the sample process and error is illustrated by describing in the remainder of the paper some sampling practices that have been utilized on mining and exploration properties and by describing some problems that have been encountered, providing a series of cautionary tales to those involved in any aspect of mine or exploration sampling.

Jan 1, 1983

By Francis F. Pitard

North America had an Important role in the early development of sampling theories. Unfortunately many progressive ideas were soon frozen into a series of guidelines based on the philosophy that "honest sampling only requires good judgment and practical experience". Such a philosophy appeared to be good enough In the early age of the mining Industry; however, it became quickly necessary to find new approaches. During the last thirty years, Pierre Gy's sampling theory provided tremendous breakthrough in the comprehension of this new science, nevertheless went unnoticed in North America. Sampling always generates complex problems and as the philosopher and mathematician Descartes suggested: "A complex problem can often be dissociated Into a series of several simpler problems, only then you try to solve those one by one". The only way to solve sampling problems is to consider each component of the overall sampling error: components of a continuous model such as long-range quality fluctuations, periodic quality fluctuations, weighting fluctuations; components of a discrete model such as materialization errors, delimitations errors, extraction errors, fundamental errors, grouping errors, and segregation errors. PAST AND CURRENT PRACTICES Many sampling methodologies have been developed, improved, and standardized during the first half of this century. Accordingly, sampling equipment has been proposed, selected, and used by standards committees. Today, there is a tremendous variety of sampling methodologies and corresponding tools offered to anyone with limited experience in sampling and it is very easy for a chemist, metallurgist, geologist or miner to spend considerable money in equipment transgressing the most basic rules of sampling correctness. Sampling stations that never worked properly in modern plants often cause engineers to abandon them and return to a primitive form of grab sampling.

Jan 1, 1986

By J. L. Fuller

Thousands of mine air samples are taken underground each year by MSHA inspection personnel in order to further assure that miners have a safe and healthy environment in which to work. While most air samples are taken with stain tubes, many samples are obtained in evacuated containers and returned to a laboratory for more accurate analysis on a gas chromatograph. In order to enhance the accuracy, reliability and repeatability of the samples taken with evacuated containers, improved procedures have been developed, which are described in this report, for filling two different types of evacuated sample containers using either mechanical or electrical pumps. In those instances, such as when sampling strata gases in drill holes, where mathematical calculations may be required for proper sampling, example calculations are provided. The use of a third type of evacuated container, which is generally restricted to non-specific sampling of the ambient mine atmosphere, is also described.

Jan 1, 1986

By L. Capponi

At Tapira Mine (Tapira/MG/ Brazil), the largest phosphate concentrate producer in Brazil, the mining is fully mechanized and carried out using open pit mining. This work presents a review of the sampling protocol used for short term mine planning at different stages. Sampling is carried out in two steps. Firstly, diamond drill cores are sampled at 50 x50 x5 metre pattern. Fosfertil analyses grades of P2O5, Fe2O3, CaO, MgO, SiO2 and TiO2 plus geological logging. This information feeds the long term block model. Secondly, drill cuttings are collected at the mining faces released for blasting. The drilling pattern is staggered and when blasting is not necessary, a drill hole is made centered in the block area (25 x 25 x 5 m). The primary samples have mass approximately 60 kg and the same chemical parameters are analysed. Metallurgical and mass recovery tests are performed as well. These samples are used to build the short term block model. At the final stage, the short term mine planning model is used to build a stockpile blending model which is simulated using a spreadsheet to match the goals established by the process plant.

Jan 1, 2009

The creation of an accurate and precise enough database requires the collection of many representative samples, subsampling and assaying them without destroying their integrity. The selection and implementation of sampling protocols often lead to severe difficulties, making the unaware practitioner vulnerable to massive exploration, feasibility and operating failures. Therefore, there is no substitute for a good understanding of the Theory of Sampling (TOS). Either because of ignorance, or because of short-term economic reasons, failure to comply with many stringent conditions can be devastating for the validity of a feasibility study, leading to false evaluations, to the abandonment of a viable property, or to the exploitation of one that is not profitable. All these failures have something in common: insufficient duplicate sampling, subsampling and assaying were performed; very important, preliminary heterogeneity tests were never performed; for short-term economic reasons, poor sampling and subsampling protocols were selected, second-class sampling systems and weightometers were installed and poor preventive maintenance and cleaning were implemented;and sampling experts were called only when the project was obviously in trouble. The conclusion is clear: in due time, iterative auditing of sampling practices is an insurance policy against massive financial losses for the company involved. A complete, comprehensive 100 point checklist of sampling Quality Assurance and Quality Control is provided, so critically important details to ensure success are not forgotten.

Mar 1, 2010

By Marcel Vallée

Abstract -Traditionally, samples collected for mineral deposit evaluation have been viewed without explicit reference to reliability, with the illusion that a true value is attainable from a few samples and verifications. For exploration, mineral deposit estimation and production quality control the following definition is proposed: "a sample is a small quantity of material relative to the geological mass it represents, collected according to a systematic procedure, of measurable reliability, from which the grade/quality of the mass which it represents may be estimated, based upon appropriate protocols. This paper will concentrate on the actual rock sampling process. Too often, sample size has been, and is still viewed as a matter of convenience, leaving out representivity considerations, despite the importance of samples on project estimation. Linear samples (chips, channels, drill), panel samples, broken rock or mining samples and very large samples are considered. Collection procedures and quality control protocols to improve the representivity of non-mechanical samples are proposed.

Jan 1, 1998