Laboratory and ore analysis

Quality samples equal quality results

Taking better ore samples will produce better-quality results. This sounds easier said than done, especially in mining applications where often consignments of many thousands of tons of ore product needs to be represented by final composite ore sample sizes that wouldn’t fill a teaspoon. Mientjie Kleinhans investigates the science behind ore sampling for better analysis 

Different analytical apparatus and techniques require different ore sample preparation, leaving it up to the informed manufacturer and supplier to specify the relevant procedures. Seeing that there are various ore sampling systems for different applications with differing final sample sizes, mining companies need to keep certain factors in mind.

Rolf Steinhaus, sampling specialist and director, Multotec Process Equipment, explains the influence the quality of ore samples has on analysis. “Mineral ores that are being crushed, milled, then either separated or leached, concentrated or beneficiated in process plants daily are very heterogeneous in nature, in terms of the levels and types of naturally occurring elements and chemical constituents. It is of paramount importance that these ores are sampled sufficiently regularly (on a timed or mass basis) by cross-stream methods to achieve accurate final samples,” says Steinhaus.

He adds that sample integrity, in addition, also hinges heavily around the sampling of one-dimensional streams, such as from conveyor belts and vertical chutes or pipe columns, for dry or wet slurry applications respectively. Access to all parts of the ore material body needs to be guaranteed and then random samples can be obtained using recommended, industry-stipulated guidelines and equipment designs.

“Each particle passing a specific point in the process plant must be given an equal opportunity of reporting to a composite sample collected over a period of time. This minimum requirement should never be neglected. Some 80% to 90% of sampling errors occur well before analytical processes and need be a point of focus for any design or process engineer serious about introducing ‘correct’ sampling solutions into a plant,” says Steinhaus.

Improving ore sample quality

End-users of sampling systems need to ensure that the mechanical samplers they purchase are not only cost-effective, but that the inherent designs emphasise the required integrity, according to Steinhaus. “Lowest-cost procurement is not a route to quality! Aspects of the cutter arrangement that traverses the full material stream need to define and extract the full portion of that sample increment without misplacing particles as it does so. Belt-end, cross-stream sample cutters, for instance, need to traverse the entire material stream at right angles and at less than 0.6 m/s speed with parallel cutter blades and associated widths of greater than 30 mm for fine solids,” says Steinhaus.

“Furthermore, the equipment, once correctly designed, needs to be installed and integrated into new (greenfield) or existing (brownfield) plants. Sample cutters must intersect the material streams fully and ensure no blockages,” explains Steinhaus.

He adds that correctly installed equipment then needs to be maintained properly with regular, planned maintenance interventions to prevent longer-term mechanical breakdowns. “This should be done as per the guidelines in the equipment operating and maintenance manuals. We cannot expect good sample collection from neglected or worn sampling equipment,” says Steinhaus.

He further explains that daily operator inspections are also routinely recommended to ensure there is no build-up of foreign material on sample cutter apertures and to ensure consequent occluded cutter blades do not become a source of bias. Sample bias generation mechanisms can be controlled but sample variability cannot, and is associated with mineral ore heterogeneity.  It can only be minimised by sample protocols or techniques, such as crushing, blending and or sample increment frequency increases prior to further sample subdivision.

Products and technology

To improve the quality of ore samples, there are recommended cross-stream sampling techniques and mechanical sampler equipment to ensure final sample integrity. Steinhaus explains that these systems can be either a single-stage, cross-cut sampler for smaller plant throughput for fine material ores, or multistage systems for high ore flow rates, which will have additional equipment such as crushers, sample dividers, sample dosing feeders and sample collection carousels arranged sequentially to provide manageable final sample sizes for each ore consignment or batch.

“These final samples need to be representative of the consigned material, whether it represents a shift period, 24 hours of production, or train/shiploads. When sampling bulk commodities like coal or iron ore, adherence to long-established ISO sampling standards is essential,” asserts Steinhaus. He adds that online analysers with continuous offtake device feeds for ore slurries, or mounted the over-belt conveyors, are still only considered for control (not metallurgical accounting) sampling applications such as at base metal concentrators.

Training

Although equipment and techniques are fundamental in ore sampling, trained personnel play a significant role in quality ore sampling. Steinhaus reckons that training and obtaining knowledge in mineral sampling techniques and principles plays an enormous role and would greatly assist in overcoming the lack of knowledge of users of the equipment and the often unsatisfactory quality of the samples that are collected.

“It would ensure producers of ore products get the most out of the mineral product quality ‘policing’ equipment. Management decisions are only as good as the analysed sampling results. We need to avoid making bad decisions based on poor sampling data, as this can be costly to mining operations,” warns Steinhaus.

Bad sampling

Sample delineation, extraction, weighing and preparation errors are common sources of bias and can be eliminated by correct designs and sampling techniques, according to Steinhaus. “Errors emanating from short- and long-term periodic process fluctuations, material segregation due to density and grouping effects, and mineral variability due to ore lump sizes are more difficult to eliminate and these sampling errors can only be minimised,” explains Steinhaus.

Latest technology

He explains that over-belt, online analysers are increasingly being used for monitoring crushed or milled ore materials in the coal, iron ore and cement industries. This gives continuous, real-time analysis and immediate results, overcoming the time lag of conventional sample preparation and analysis delays associated with mechanical sampling systems. It can be seen as an attractive option for plant operators to help maximise their product yields and even out quality spikes, and is particularly useful for the trending of values of mineral or the ore grade of interest.

“Monitoring qualities of base metal flotation concentrator circuits between stages, to provide unit efficiency data for optimising process efficiencies, is also often desirable. Importantly, these are trending technologies using control sampling and not metallurgical accounting. The latter requires more reliable values with lower levels of uncertainty (thus high precision) to ensure monthly mineral balancing of complex metallurgical circuits is properly managed and adheres to the central tenets of corporate governance and associated official reporting,” says Steinhaus.

Lab analysis

Inside the laboratory, ore sampling is done on a different scale. Yet, the same rule applies where better-quality samples result in better results. Dr Ljiljana Marjanovic, analytical technical specialist, SGS South Africa, believes that sampling forms an integral part of the analysis and it is often referred to as the most difficult step in analytical processes. “Even the most accurate results from the lab would be meaningless if the wrong sampling is performed.”

She adds that only a very small portion of the sample is analysed in the lab and it is, therefore, very important to understand that the sample must resemble the “population” it represents as closely as possible. “This is applicable to the whole process, starting from the identification of the population, gross sample collection, the reduction of gross sample size to laboratory sample size, as well as particle size reduction and sum sampling in the lab,” says Marjanovic.

She says that a proper sampling plan needs to be established with full understanding of the population, including the size of the population that the collected sample needs to represent, its heterogeneity, particle size as well as the levels of analytes of interest. The size of the gross sample needs to be calculated in such a way that the rule of every particle having the same probability of being included in the sample applies.

In practical terms (in addition to the sampling plan), this would mean proper understanding and execution of the sampling procedure in cases of manual sampling and the introduction of semi-automated/automated sampling. It has been shown that the most representative sample can be taken from the “moving” sample, as found on the conveyer belt, etc.

According to a technical paper by Spectro Analytic Instruments, it is important to obtain a properly representative sample. “The physical nature of the sample can also affect the quality of results.”

According to the paper, it is usually necessary to first dry the sample for elemental analysis, and then to grind the dried sample to less than 100 microns in size. This is because water can absorb X-rays and, therefore, influence the results.

“Although it is possible to analyse the loose powder, better results may be obtained if the powder is pressed into a pellet. This helps to remove any unevenness of packing or voids in the material,” states the author in the paper. It is further advised that a hydraulic press, with pressures up to 40 tonnes, should be used with an organic binder, such as wax. In some cases, it may be advisable to prepare the sample as a fused bead 

The author explains that these sample preparation techniques offer one way to eliminate possible errors in Spectro’s range of energy-dispersive, X-ray fluorescence (EDXRF) instruments. “These machines require far less sample preparation than for most other analysing techniques.”

Spectro’s range of three models includes analytical instruments for routine analysis of relevant elements, from sodium to uranium, to determine minor and trace elements, as well as field investigations and surveys. According to the author, EDXRF technology and calibration technology are employed in their instruments to minimise and compensate for matrix effects.

Published by Inside Mining