1404 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
downs related to these six categories, with boulders by far
the most likely to cause performance issues. Additionally,
the operation tracks two different types of ore down dura-
tions, namely ‘actual’ and ‘effective’ downs. Actual downs
track the time in which equipment is not operational, while
effective downs are calculated based on the degree of equip-
ment slowdown. For example, if a processing component
is operating at half capacity for 30 minutes, this would be
recorded as an effective down with a 15-minute duration.
DES Model Configuration
The resulting DES model represents the beginning stages
of comminution during crushing and conveying. At the
mine operation, ore is dumped directly from a truck into
the primary crusher. From there, ore exits the crusher and
is dumped onto an apron feeder before passing onto three
other conveyors and then dumped onto an intermedi-
ate ore stockpile. Ore is later drawn from the intermedi-
ate stockpile into the secondary crushing portion of the
mineral processing system, followed by a tertiary crushing
system before entering the grinding circuit. This study is
limited to modeling the section of comminution beginning
at the primary crusher and ending at the intermediate ore
stockpile (Figure 1).
Truckloads of ore in the DES model are dumped
into the crusher on a schedule matching that of the actual
operation throughout 2022. Data on select geometallur-
gical attributes are loaded into the model corresponding
to the actual values for each load as well. These attributes
include the tons, the copper percent, any geological attri-
butes that impact processing performance, as well as the
three attributes which together form a foreign key connect-
ing to other mine operations data sources. Outputs from
the model include data on the same attributes and the time
at which the material from each truckload is added to the
intermediate stockpile. For the primary crusher, most of
the unplanned downtimes relate to hard ore. For this rea-
son, the DES primary crushing model focuses on track-
ing ore hardness and size. As the hardness of an individual
truckload is unlikely to cause an equipment down, a rolling
average was also calculated as periods in which ore is harder
or softer than normal may be more likely to cause equip-
ment failures than a single load of ore that is an outlier.
The DES model was constructed using Arena
Professional edition, version 16.2. As with other DES
software options, components of the system are modeled
using a combination of entities, resources, processes, and
queues. The model simulates the material movement of the
real-world system using a series of probability distributions
governing the timing and connections between each com-
ponent of the system. In this model, there are distributions
governing the time required for one truckload of material
Figure 1. Overview of primary crushing system at the copper operation
downs related to these six categories, with boulders by far
the most likely to cause performance issues. Additionally,
the operation tracks two different types of ore down dura-
tions, namely ‘actual’ and ‘effective’ downs. Actual downs
track the time in which equipment is not operational, while
effective downs are calculated based on the degree of equip-
ment slowdown. For example, if a processing component
is operating at half capacity for 30 minutes, this would be
recorded as an effective down with a 15-minute duration.
DES Model Configuration
The resulting DES model represents the beginning stages
of comminution during crushing and conveying. At the
mine operation, ore is dumped directly from a truck into
the primary crusher. From there, ore exits the crusher and
is dumped onto an apron feeder before passing onto three
other conveyors and then dumped onto an intermedi-
ate ore stockpile. Ore is later drawn from the intermedi-
ate stockpile into the secondary crushing portion of the
mineral processing system, followed by a tertiary crushing
system before entering the grinding circuit. This study is
limited to modeling the section of comminution beginning
at the primary crusher and ending at the intermediate ore
stockpile (Figure 1).
Truckloads of ore in the DES model are dumped
into the crusher on a schedule matching that of the actual
operation throughout 2022. Data on select geometallur-
gical attributes are loaded into the model corresponding
to the actual values for each load as well. These attributes
include the tons, the copper percent, any geological attri-
butes that impact processing performance, as well as the
three attributes which together form a foreign key connect-
ing to other mine operations data sources. Outputs from
the model include data on the same attributes and the time
at which the material from each truckload is added to the
intermediate stockpile. For the primary crusher, most of
the unplanned downtimes relate to hard ore. For this rea-
son, the DES primary crushing model focuses on track-
ing ore hardness and size. As the hardness of an individual
truckload is unlikely to cause an equipment down, a rolling
average was also calculated as periods in which ore is harder
or softer than normal may be more likely to cause equip-
ment failures than a single load of ore that is an outlier.
The DES model was constructed using Arena
Professional edition, version 16.2. As with other DES
software options, components of the system are modeled
using a combination of entities, resources, processes, and
queues. The model simulates the material movement of the
real-world system using a series of probability distributions
governing the timing and connections between each com-
ponent of the system. In this model, there are distributions
governing the time required for one truckload of material
Figure 1. Overview of primary crushing system at the copper operation