XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 863
either underground prior to moving ore to surface or in-pit.
Analyzer data has shown that ore quality variability is much
higher and more frequent than predicted from geological
models and ore schedules, particularly at the scale of a few
or tens of tons able to be measured by advanced analyzers.
Figures 2 shows examples of analyzer data in different com-
modities over a 24 hour period and the size of two minute
parcels.
Such variability indicates the potential to utilize
measured data for quality improvements and ongoing
Source: Scantech International Pty Ltd
Figure 1. Cross-section through GEOSCAN high specification PGNAA analyzer showing main components and an example of
elemental results for a two minute measurement increment
Source: Scantech International Pty Ltd
Figure 2. Quality variability over 24 hours of conveyed flow of copper ore, zinc-lead ore, iron ore and limestone
demonstrating significant natural quality variability
either underground prior to moving ore to surface or in-pit.
Analyzer data has shown that ore quality variability is much
higher and more frequent than predicted from geological
models and ore schedules, particularly at the scale of a few
or tens of tons able to be measured by advanced analyzers.
Figures 2 shows examples of analyzer data in different com-
modities over a 24 hour period and the size of two minute
parcels.
Such variability indicates the potential to utilize
measured data for quality improvements and ongoing
Source: Scantech International Pty Ltd
Figure 1. Cross-section through GEOSCAN high specification PGNAA analyzer showing main components and an example of
elemental results for a two minute measurement increment
Source: Scantech International Pty Ltd
Figure 2. Quality variability over 24 hours of conveyed flow of copper ore, zinc-lead ore, iron ore and limestone
demonstrating significant natural quality variability