3914 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
20:20:60 were simulated that satisfies a wide range of pro-
portion for each of the components.
Actual ore multi-component simulation: This repre-
sents the actual proportions of hard, medium and soft com-
ponents within Sample A. That is, 24% hard (A×b=30),
43% medium (A×b=52) and 33% soft (A×b=88), detailed
in Table 3.
Single component simulation: This assumes that either
of the components constitutes the entire mill feed, that is
100:0:0 for hard (A×b=30), 0:100:0 for medium (A×b=52)
and 0:0:100 for soft (A×b=88). While it is unlikely that
these percentile fractions might constitute the complete
mill feed for Sample A, the objective of these simulations
is to estimate the maximum variations which might occur.
As a single component model, the simulation estimates are
likely to underestimate effects of harder material in the load.
One of the main SAG milling operational challenges
imposed by feed competence variability is the challenge
of maintaining a steady load due to changes in SAG mill
comminution characteristics and discharge rate. In SABC
circuits (depending on operational constraints of a process
plant), ore variability may induce imbalance of installed
power between the SAG and ball milling units which can
result in the circuit shifting from SAG to ball mill limi-
tation, increasing the risk of under-utilisation of available
power and hence throughput restriction (i.e., processing a
feed with high amount of very soft components). It should
be noted that this possibility is not considered in this work
in which the SAG milling circuit is specifically studied.
IMPLICATIONS FROM THE SIMULATION
RESULTS AND DISCUSSION
The method proposed for the multi-component modelling
assisted with estimating the breakage potential, A×b and
the amount of hard, medium and soft components within
the Sample A ore type. The breakage rates for each com-
ponent changes depending on their ratio in the SAG mill
fresh feed. That is, different feed blends generate different
mill content compositions, which act as grinding media.
Several scenarios were defined to estimate Barrick Cortez
SAG mill performance, by integrating the ExDWT data
into the JKMRC SAG mill model.
If the ball milling circuit is not a limitation, then the
response of the SAG mills to a softer ore is usually found to
be an increased throughput for it breaks readily down to a
suitable discharge size. On the contrary, the hard compo-
nent tends to dominate the mill content due to its natural
resistance to breakage (Napier-Munn et al., 1996). This
explanation is well-illustrated in Figure 9 that gives simu-
lated scenarios in a multi-component manner including
the actual ore (24% hard with A×b=30, 43% medium with
A×b=52 and 33% soft with A×b=88) as well as single com-
ponent simulation outcomes. As it is shown for different
SAG mill ball charges, the mill content is mainly dictated
0
100
200
300
400
500
600
700
800
900
1000
0
20
40
60
80
100
120
Feed Components %(Hard:Medium:Soft)
Hard Component Medium Component Soft Component
Throughput (t/h) @Jb=5.0% Throughput (t/h) @Jb=10% Throughput (t/h) @Jb=12.1%
Throughput (t/h) @Jb=15%
Figure 9. Simulated scenarios presenting the impact of different ratios of hard, medium and soft components in the feed on
SAG mill content (%)and its throughput (t/h) at different ball loads
Thr
ut
(t
SAG
Mill
ContentComponents
(%)
20:20:60 were simulated that satisfies a wide range of pro-
portion for each of the components.
Actual ore multi-component simulation: This repre-
sents the actual proportions of hard, medium and soft com-
ponents within Sample A. That is, 24% hard (A×b=30),
43% medium (A×b=52) and 33% soft (A×b=88), detailed
in Table 3.
Single component simulation: This assumes that either
of the components constitutes the entire mill feed, that is
100:0:0 for hard (A×b=30), 0:100:0 for medium (A×b=52)
and 0:0:100 for soft (A×b=88). While it is unlikely that
these percentile fractions might constitute the complete
mill feed for Sample A, the objective of these simulations
is to estimate the maximum variations which might occur.
As a single component model, the simulation estimates are
likely to underestimate effects of harder material in the load.
One of the main SAG milling operational challenges
imposed by feed competence variability is the challenge
of maintaining a steady load due to changes in SAG mill
comminution characteristics and discharge rate. In SABC
circuits (depending on operational constraints of a process
plant), ore variability may induce imbalance of installed
power between the SAG and ball milling units which can
result in the circuit shifting from SAG to ball mill limi-
tation, increasing the risk of under-utilisation of available
power and hence throughput restriction (i.e., processing a
feed with high amount of very soft components). It should
be noted that this possibility is not considered in this work
in which the SAG milling circuit is specifically studied.
IMPLICATIONS FROM THE SIMULATION
RESULTS AND DISCUSSION
The method proposed for the multi-component modelling
assisted with estimating the breakage potential, A×b and
the amount of hard, medium and soft components within
the Sample A ore type. The breakage rates for each com-
ponent changes depending on their ratio in the SAG mill
fresh feed. That is, different feed blends generate different
mill content compositions, which act as grinding media.
Several scenarios were defined to estimate Barrick Cortez
SAG mill performance, by integrating the ExDWT data
into the JKMRC SAG mill model.
If the ball milling circuit is not a limitation, then the
response of the SAG mills to a softer ore is usually found to
be an increased throughput for it breaks readily down to a
suitable discharge size. On the contrary, the hard compo-
nent tends to dominate the mill content due to its natural
resistance to breakage (Napier-Munn et al., 1996). This
explanation is well-illustrated in Figure 9 that gives simu-
lated scenarios in a multi-component manner including
the actual ore (24% hard with A×b=30, 43% medium with
A×b=52 and 33% soft with A×b=88) as well as single com-
ponent simulation outcomes. As it is shown for different
SAG mill ball charges, the mill content is mainly dictated
0
100
200
300
400
500
600
700
800
900
1000
0
20
40
60
80
100
120
Feed Components %(Hard:Medium:Soft)
Hard Component Medium Component Soft Component
Throughput (t/h) @Jb=5.0% Throughput (t/h) @Jb=10% Throughput (t/h) @Jb=12.1%
Throughput (t/h) @Jb=15%
Figure 9. Simulated scenarios presenting the impact of different ratios of hard, medium and soft components in the feed on
SAG mill content (%)and its throughput (t/h) at different ball loads
Thr
ut
(t
SAG
Mill
ContentComponents
(%)