XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3903
B02 and B03. As shown in the revised simulation
results in Scenario 1, the changeover point between
the bottleneck can be controlled by maintaining the
correct ratio of the bin capacities of B02 and B03.
In practice, it is difficult to maintain the ratio split
in the mass flow between the two streams as there
are multiple sources of variation, such as CSS change
due to wear, screen aperture wear, material change
due to ROM variations, etc. In such a strategy, a suit-
able control system is needed to monitor this.
• Process Response Control and Reduce Interlocks
Triggers: If the strategy is to slow down the process
response to changing mass flow rates, then additional
bin capacity can be added. This will create a slow
reactive system, such as a slower bin-filling level.
However, the resultant total capacity processed by
the circuit over time will remain as the function of
the capacity utilization of the two crushers. As shown
in the revised process simulation Scenario 2, by
adjusting the capacity ratio of bins and CSS settings,
it is possible to reduce the number of interlocks trig-
gered in the circuit. Alternatively, the interlock trig-
ger can also be reduced by adjusting the maximum
feed capacity from SP1.
LIMITATIONS
Other safety and functional considerations are important
to determine the minimum sizing of the bin such as the
frequency of ROM trucks and capacity of the conveyors.
This is an iterative process, if the crusher selected is not suit-
able for the circuit requirements, then, alternative crusher
type and size can be selected. If the strategy is to find a
redundant system, then additional capacities such as add-
ing a parallel crusher can be proposed. The presented case
study is limited and other requirements of the circuit devel-
opment will be studied in future work, such as:
1. sizing of the conveyors using dynamic simulation
response to avoid potential interlocks
2. variation in crusher CSS due to operational
changes
3. wear in screens affecting the balance of the circuit
4. effect of discrete events such as CSS adjustment,
failure, and abrupt stops over operation
5. feed variations.
CONCLUSION
The use of dynamic simulation for the comminution cir-
cuit design resulted in an understanding of the intricate
relationship between the bin sizing, equipment configura-
tion and control system setup resulting in a variable perfor-
mance of the circuit. Dynamic simulation can be used to
optimize the scaling of the sizing of the bins with respect to
the process setup. The steady-state simulation relies on the
instantaneous maximum performance of the circuit, while
the dynamic simulation captures average operational per-
formance calculated with a summation of performance for
a given period of operation. The application is useful in the
early evaluation of conceptual plant layout, equipment size
and type, and deciding on suitable strategy in bin capacity
ratio at different positions in the circuit. The results also
highlighted the bin sizing effect on the interlock trigger
with respect to the process configuration. The iterative pro-
cess is required to fully utilize the potential of dynamic pro-
cess simulation and the results can assist in both equipment
selection as well as assist in the development of a suitable
control system for the circuit. It can also be highlighted that
confidence in the equipment model performance is critical
in such evaluation as the process response is a function of
the equipment model and error propagation evaluation is
required. Future development will include consideration of
other practical effects of discrete events and wear.
REFERENCES
Asbjörnsson, G. (2015). Crushing Plant Dynamics.
PhD Thesis, Chalmers University of Technology.
Gothenburg, Sweden.
Asbjörnsson, G., Bengtsson, M., Hulthén, E., &
Evertsson, C. M. (2016). Modelling of discrete down-
time in continuous crushing operation [Article].
Minerals Engineering,98,22–29.doi:10.1016/j.mineng
.2016.07.003.
Asbjörnsson, G., Hulthén, E., &Evertsson, C. M.
(2013). Modelling and simulation of dynamic
crushing plant behavior with MATLAB/Simulink.
Minerals Engineering, 43, 112–120. doi: 10.1016/j.
mineng.2012.09.006.
Asbjörnsson, G., Tavares, L. M., Mainza, A., &Yahyaei, M.
(2022). Different perspectives of dynamics in commi-
nution processes. Minerals Engineering, 176, 107326.
doi: 10.1016/j.mineng.2021.107326.
Bhadani, K., Asbjörnsson, G., Hulthén, E., &Evertsson, C.
M. (2020). Development and implementation of
key performance indicators for aggregate production
using dynamic simulation. Minerals Engineering, 145,
106065. doi: 10.1016/j.mineng.2019.106065.
B02 and B03. As shown in the revised simulation
results in Scenario 1, the changeover point between
the bottleneck can be controlled by maintaining the
correct ratio of the bin capacities of B02 and B03.
In practice, it is difficult to maintain the ratio split
in the mass flow between the two streams as there
are multiple sources of variation, such as CSS change
due to wear, screen aperture wear, material change
due to ROM variations, etc. In such a strategy, a suit-
able control system is needed to monitor this.
• Process Response Control and Reduce Interlocks
Triggers: If the strategy is to slow down the process
response to changing mass flow rates, then additional
bin capacity can be added. This will create a slow
reactive system, such as a slower bin-filling level.
However, the resultant total capacity processed by
the circuit over time will remain as the function of
the capacity utilization of the two crushers. As shown
in the revised process simulation Scenario 2, by
adjusting the capacity ratio of bins and CSS settings,
it is possible to reduce the number of interlocks trig-
gered in the circuit. Alternatively, the interlock trig-
ger can also be reduced by adjusting the maximum
feed capacity from SP1.
LIMITATIONS
Other safety and functional considerations are important
to determine the minimum sizing of the bin such as the
frequency of ROM trucks and capacity of the conveyors.
This is an iterative process, if the crusher selected is not suit-
able for the circuit requirements, then, alternative crusher
type and size can be selected. If the strategy is to find a
redundant system, then additional capacities such as add-
ing a parallel crusher can be proposed. The presented case
study is limited and other requirements of the circuit devel-
opment will be studied in future work, such as:
1. sizing of the conveyors using dynamic simulation
response to avoid potential interlocks
2. variation in crusher CSS due to operational
changes
3. wear in screens affecting the balance of the circuit
4. effect of discrete events such as CSS adjustment,
failure, and abrupt stops over operation
5. feed variations.
CONCLUSION
The use of dynamic simulation for the comminution cir-
cuit design resulted in an understanding of the intricate
relationship between the bin sizing, equipment configura-
tion and control system setup resulting in a variable perfor-
mance of the circuit. Dynamic simulation can be used to
optimize the scaling of the sizing of the bins with respect to
the process setup. The steady-state simulation relies on the
instantaneous maximum performance of the circuit, while
the dynamic simulation captures average operational per-
formance calculated with a summation of performance for
a given period of operation. The application is useful in the
early evaluation of conceptual plant layout, equipment size
and type, and deciding on suitable strategy in bin capacity
ratio at different positions in the circuit. The results also
highlighted the bin sizing effect on the interlock trigger
with respect to the process configuration. The iterative pro-
cess is required to fully utilize the potential of dynamic pro-
cess simulation and the results can assist in both equipment
selection as well as assist in the development of a suitable
control system for the circuit. It can also be highlighted that
confidence in the equipment model performance is critical
in such evaluation as the process response is a function of
the equipment model and error propagation evaluation is
required. Future development will include consideration of
other practical effects of discrete events and wear.
REFERENCES
Asbjörnsson, G. (2015). Crushing Plant Dynamics.
PhD Thesis, Chalmers University of Technology.
Gothenburg, Sweden.
Asbjörnsson, G., Bengtsson, M., Hulthén, E., &
Evertsson, C. M. (2016). Modelling of discrete down-
time in continuous crushing operation [Article].
Minerals Engineering,98,22–29.doi:10.1016/j.mineng
.2016.07.003.
Asbjörnsson, G., Hulthén, E., &Evertsson, C. M.
(2013). Modelling and simulation of dynamic
crushing plant behavior with MATLAB/Simulink.
Minerals Engineering, 43, 112–120. doi: 10.1016/j.
mineng.2012.09.006.
Asbjörnsson, G., Tavares, L. M., Mainza, A., &Yahyaei, M.
(2022). Different perspectives of dynamics in commi-
nution processes. Minerals Engineering, 176, 107326.
doi: 10.1016/j.mineng.2021.107326.
Bhadani, K., Asbjörnsson, G., Hulthén, E., &Evertsson, C.
M. (2020). Development and implementation of
key performance indicators for aggregate production
using dynamic simulation. Minerals Engineering, 145,
106065. doi: 10.1016/j.mineng.2019.106065.