868 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
should be differentiated from measured data so that any
potential calculation errors are considered before making
decisions based on that data. A verification mechanism
should be applied to artificially created data to ensure it is
credible.
Sensors should integrate easily with plant networks to
minimize data transfer delays and improve data visibility.
Data accessed via cloud storage or processing may prove
less reliable than data directly transmitted between sensor
and plant. Remote access to sensors may also significantly
reduce costs to a remote site. Direct supply of sensor out-
put to the process control system has proven very effective
at many mining and processing sites. This has also assisted
in prompt resolution of any data generation interruptions
which could otherwise be blamed on data access problems.
CONCLUSIONS
Commercially proven technologies provide accurate, repre-
sentative and timely data in mining and processing opera-
tions to control and improve conveyed ore quality and
consistency. This has resulted in improved process efficien-
cies, reductions in GHG emissions, reductions in cost per
ton of product, and higher revenues. High specification
PGNAA elemental analyzers provide multi-element mea-
surements for concurrent applications of the data enabling
better and more consistent ore quality supply to process
plants. Benefits are achieved through ore blending, parcel
diversion to either minimize processing or remove waste,
feed forward control, ore reconciliation and metal account-
ing. The technology is expected find more geometallurgical
applications in future in feed forward control as interest
and opportunities for both incremental and step-change
improvement increase.
Moisture analysis using transmission microwaves has
proven effective in dry tons determination, dust manage-
ment, dewatering applications, materials handling and
transport. PSD analysis by 3D Infrared camera technology
has proven effective under conditions unsuitable for optical
and laser-based systems. Fragmentation analysis has assisted
with blasting, crushing and oversize detection improve-
ments and prevented damage to downstream equipment.
Volume, belt speed, mass flow data and foreign object
detection capability are also available from the system
where needed. Developments in sensor fusion have shown
the benefits in combining multi-sensor data to recognize
parameters affecting process performance. Technologies
discussed have proven successful in digitalization strategies
implemented at mining and processing sites in multiple
commodities and their capabilities continue to improve to
ensure suitability for new applications.
Source: Scantech International Pty Ltd
Figure 7. Simplified model with mined ore input showing basic real time sensor data integration and
response options
should be differentiated from measured data so that any
potential calculation errors are considered before making
decisions based on that data. A verification mechanism
should be applied to artificially created data to ensure it is
credible.
Sensors should integrate easily with plant networks to
minimize data transfer delays and improve data visibility.
Data accessed via cloud storage or processing may prove
less reliable than data directly transmitted between sensor
and plant. Remote access to sensors may also significantly
reduce costs to a remote site. Direct supply of sensor out-
put to the process control system has proven very effective
at many mining and processing sites. This has also assisted
in prompt resolution of any data generation interruptions
which could otherwise be blamed on data access problems.
CONCLUSIONS
Commercially proven technologies provide accurate, repre-
sentative and timely data in mining and processing opera-
tions to control and improve conveyed ore quality and
consistency. This has resulted in improved process efficien-
cies, reductions in GHG emissions, reductions in cost per
ton of product, and higher revenues. High specification
PGNAA elemental analyzers provide multi-element mea-
surements for concurrent applications of the data enabling
better and more consistent ore quality supply to process
plants. Benefits are achieved through ore blending, parcel
diversion to either minimize processing or remove waste,
feed forward control, ore reconciliation and metal account-
ing. The technology is expected find more geometallurgical
applications in future in feed forward control as interest
and opportunities for both incremental and step-change
improvement increase.
Moisture analysis using transmission microwaves has
proven effective in dry tons determination, dust manage-
ment, dewatering applications, materials handling and
transport. PSD analysis by 3D Infrared camera technology
has proven effective under conditions unsuitable for optical
and laser-based systems. Fragmentation analysis has assisted
with blasting, crushing and oversize detection improve-
ments and prevented damage to downstream equipment.
Volume, belt speed, mass flow data and foreign object
detection capability are also available from the system
where needed. Developments in sensor fusion have shown
the benefits in combining multi-sensor data to recognize
parameters affecting process performance. Technologies
discussed have proven successful in digitalization strategies
implemented at mining and processing sites in multiple
commodities and their capabilities continue to improve to
ensure suitability for new applications.
Source: Scantech International Pty Ltd
Figure 7. Simplified model with mined ore input showing basic real time sensor data integration and
response options
