QEMScan Services for Plant Audit

PLANT OPTIMIZATION AUDITS & PROGRAMS
Characterization of metallurgical products such as feed, concentrate and tailing samples is essential to the evaluation, development and optimization/control of metallurgical processes and the improvement of plant efficiency and economics. Traditionally, this analysis has been performed using classical ore microscopy, which is highly labor intensive. QEMSCAN analysis provides an automated, statistically superior determination of bulk sample mineralogy, and mineral liberation by class and association.

Liberation analysis typically is performed on sized products. The samples are subjected to both screening and cyclosizer separation, and fractions are recombined to create up to seven fractions for mineralogical analysis. The photograph below shows a rich copper flotation froth. This concentrate was analysed in four size fractions (+53 µm, +23 µm, +10 µm and –10 µm).

During polished section preparation, the sample fractions are mixed with graphite to ensure homogenization and the random orientation of particles. Chemical analyses are performed on the sized fractions to provide a quality control benchmark.

BULK MINERAL ANALYSIS (BMA)
For each product size fraction, QEMSCAN provides the bulk mineral assemblage, a calculated bulk chemical analysis and mineral-by-mineral deportment of target metals.

The weight distribution of the mineral components of the copper concentrate is mapped by size fraction. Copper minerals consist of chalcopyrite (CuFeS ), covellite (CuS) and chalcocite (Cu S), while diluents consist of silicate minerals, pyrite and molybdenite.

LIBERATION ANALYSIS
QEMSCAN provides detailed mineral liberation analysis by particle mineral composition and particle class, ranging from 0 to 100%. This detail of analysis provides a clear indication of when mineral liberation occurs, something that is not possible using classical optical microscopy.

CASE STUDY: LIBERATION CHARACTERISTICS OF CASSITERITE TAILING

Mineral Association



Cassiterite mineral association is shown as a 3 dimensional bar plot with sample size fraction along the x-axis and mineral association (middling attachment) along the z-axis. Cassiterite occurs as liberated grains (green columns) in the finest size fraction (-21 µm) and as complex ternary intergrowths with gangue minerals (pink columns) in the two coarsest size fractions (+53 and +106 µm). The +21 µm size fraction shows liberated cassiterite and a variety of middling and complex associations.

Liberation Class



Liberation curves for cassiterite in the four size fractions studied above and for the combined, weighted cassiterite (red) are shown. Liberation class is a ranking of mineral liberation ranging from 0% (at left) to 100% (at right).

The curves show a progressive decrease of cassiterite liberation into the coarser size fractions with an average cassiterite liberation of 30% in the 90-100% class for the entire tailing.

PARTICLE MAPPING
Particle maps (bellow) graphically illustrate mineral liberation and intergrowth textures. These maps can be sorted by various criteria including

• particle size
• dominant mineral species
• shape
• calculated metal content
• density

Particle maps can be edited to demonstrate the effect that various mineral-processing techniques potentially might have on concentrate and/or tailing grades and reveal the deportment of liberated and locked particles in various products and size fractions.

This grade-predictive tool is highly effective as a first step in the development of mineral processing strategies.

THEORETICAL GRADE - RECOVERY CURVES
Grade-recovery curves can be created to be mineralogically limited from QEMSCAN analysis which, when compared with metallurgical results, are valuable in evaluating whether liberation or chemical selectivity is driving flotation performance.

CASE STUDY: GRADE-RECOVERY CURVES

1. From a secondary copper ore, shows the actual flotation performance to be far inferior to the calculated mineralogical limit. Poor flotation chemical selectivity resulted in the activation of pyrite and dilution of concentrates.

2. Is from a primary copper ore. Here, the actual performance approaches the mineralogical limit indicating that regrinding, rather than flotation chemical changes, is the route to better flotation performance.

With such analysis, SGS metallurgists can better define flotation problems and then optimize performance.