XXXI International Mineral Processing Congress 2024 Proceedings Page 994 (1018 of 3836)

1040 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
FLOWSHEET APPLICATION
Cu Recovery Prediction for Year 2023
The integrated flowsheet was employed to project copper
recovery from March to December 2023 as part of the
mine’s medium-term planning. Currently, the mine uti-
lizes a Geomet model to forecast copper recovery for its
operations. In Figure 8, a comparison of copper recovery
between the IES model prediction and the Geomet model
prediction reveals a reasonably strong agreement. However,
it is crucial to note that the throughput was maintained at
-25%
-15%
-5%
5%
15%
25%
35%
45%
5000
5500
6000
6500
7000
7500
8000
8500
Error Actual IES
Figure 6. Actual and IES predicted plant daily throughput for September 2022
-25%
-5%
15%
35%
55%
75%
95%
150
160
170
180
190
200
210
220
230
240
Error Actual IES
Figure 7. Actual and IES predicted plant daily grind size for September 2022
the same level as the Geomet model throughput during the
model development phase.
Figure 9 illustrates the potential for further improve-
ment in copper recovery through the IES model compared
to the Geomet model prediction. This enhancement can be
achieved by optimizing the grinding process, as highlighted
in the figure.
The two figures above illustrate that by optimizing the
grinding process through the IES model, there is potential
for enhanced copper recovery in the plant compared to the
GEOMET model prediction.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Monthly
Error
(%)Throughput
(t/h)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Monthly
Error
(%)
Grind
Size
(μm)

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1040 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
FLOWSHEET APPLICATION
Cu Recovery Prediction for Year 2023
The integrated flowsheet was employed to project copper
recovery from March to December 2023 as part of the
mine’s medium-term planning. Currently, the mine uti-
lizes a Geomet model to forecast copper recovery for its
operations. In Figure 8, a comparison of copper recovery
between the IES model prediction and the Geomet model
prediction reveals a reasonably strong agreement. However,
it is crucial to note that the throughput was maintained at
-25%
-15%
-5%
5%
15%
25%
35%
45%
5000
5500
6000
6500
7000
7500
8000
8500
Error Actual IES
Figure 6. Actual and IES predicted plant daily throughput for September 2022
-25%
-5%
15%
35%
55%
75%
95%
150
160
170
180
190
200
210
220
230
240
Error Actual IES
Figure 7. Actual and IES predicted plant daily grind size for September 2022
the same level as the Geomet model throughput during the
model development phase.
Figure 9 illustrates the potential for further improve-
ment in copper recovery through the IES model compared
to the Geomet model prediction. This enhancement can be
achieved by optimizing the grinding process, as highlighted
in the figure.
The two figures above illustrate that by optimizing the
grinding process through the IES model, there is potential
for enhanced copper recovery in the plant compared to the
GEOMET model prediction.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Monthly
Error
(%)Throughput
(t/h)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Monthly
Error
(%)
Grind
Size
(μm)

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XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1039
which are not considered in the models, particularly when
throughput is constrained by events occurring upstream or
downstream of the comminution circuit. Despite these lim-
itations, the predictions generally exhibit a reasonable align-
ment with the observed trends for the variables accounted
for in the model. The average absolute error, indicating the
deviation between predicted and actual values, was found
to be 3.3%. Figure 4 depicts the comparison of the SAG
power predicted over fourteen months period and then
compared that with the actual data. The figure shows IES
was capable of predicting SAG mill power as well as mill
load with an average error of 1.5%. The combined cyclone
overflow P80 and IES predicted P80 is shown in Figure 5
The average absolute error was 4.3%.
A more refined validation of the flowsheet was con-
ducted utilizing data from September 2022. This step aimed
to assess the flowsheet’s predictability using a dataset distinct
from the one employed in the tuning process. Despite the
less-than-ideal frequency of daily simulations, constrained
by day-to-day operational and maintenance issues within
the operation, the flowsheet demonstrated commendable
capability in forecasting throughput and grind size trends
observed during that month refer to Figure 6 and Figure 7.
Remarkably, the flowsheet exhibited a monthly average
error of merely 0.5% for throughput and 2.2% for grind
size, indicating its robust predictability. These results affirm
that the flowsheet can be reliably employed for both plan-
ning and optimization.
-20%
0%
20%
40%
60%
80%
100%
12000
12500
13000
13500
14000
14500
Error Actual IES
Figure 4. Actual and IES predicted plant SAG Mill power from Jan 2021 to Mar 2022
-20%
0%
20%
40%
60%
80%
100%
150
160
170
180
190
200
210
220
230
Error Series1 Series2
Figure 5. Actual and IES predicted combined cyclone overflow from Jan 2021 to Mar 2022
Error
(%)
SAG
Mill
Power
(kW)
Error
(%)
Grind
Size
(
)

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XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1041
Process Commissioning of New Grinding Line
The site also utilized the fine-tuned flowsheet to forecast the
value chain’s response by integrating a new grinding line
into the existing circuit. This addition was necessitated by
the heightened hardness of the ore body. The flow sheet pre-
diction retained the same SAG mill, Ball Mill, and screen
model, given the absence of process data for calibrating the
new grinding line. Preliminary simulations at the target
grind size indicate a notable upswing in plant throughput,
a marginal incease in specific energy and enhancements in
overall metal production (Figure 10).
The simulation was conducted at a target grind size
of 204µm, both with the new production line activated
and deactivated. Table 2 presents a comparative analy-
sis illustrating the additional benefits the plant can attain
by incorporating the new SAG and Ball mill line (line
4). The simulation results indicate a notable improve-
ment in plant throughput, rising from 6980 t/h to 8740
t/h. There was a marginal uplift of 3% in specific energy
while water consumption rate per tonne of ore processed
remained unchanged as percent solids in the flotation cir-
cuit was always maintained at 32%. That means the water
consumption per day increased by 25.3% equivalent to the
increase in throughput. The operation has limitations in
water resources during dry seasons that are considered in
month by months throughput forecast.
CONCLUSION
Orica Digital Solutions’ technical services have success-
fully created a comprehensive value chain flow sheet for a
87.0
88.0
89.0
90.0
91.0
92.0
GEOMET Model IES Model
Figure 8. Comparison IES practiced Cu recovery against the GEOMET model when grinding process was not optimised
87.0
88.0
89.0
90.0
91.0
92.0
GEOMET Model IES Model
Figure 9. Comparison IES practiced Cu recovery against the GEOMET model when grinding process was optimised

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Page 1Plenary Program click to expand contents

Page 22Keynote Presentations click to expand contents

Page 163Innovation and R&D click to expand contents

Page 445Dry Processing click to expand contents

Page 562Water Management click to expand contents

Page 756Human Capital click to expand contents

Page 808Process Control, Modeling, and Simulation click to expand contents

Page 1126Strategic Minerals click to expand contents

Page 1325Geometallurgy and Process Mineralogy click to expand contents

Page 1535Extractive Metallurgy click to expand contents

Page 1842Physical Separations click to expand contents

Page 2016Flotation click to expand contents

Page 3021Energy Minerals click to expand contents

Page iTailings click to expand contents

Page 3420Plant Design click to expand contents

Page 3526Comminution click to expand contents

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