XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3891
mills (Qiu et al 2001). Two decades later, a much more
sophisticated DEM model for Vertimill screw liner wear
was developed (Qiu et al 2024). This model can simulate
the Vertimill liner wear process, capturing the wear charac-
teristics (see Figure 3) and delivering physics related data
including power draw, media grinding energy, and colli-
sional energy.
Figure 4 shows additional DEM results for the
Vertimill. The quantity Q is a synthetic derived physical
quantity. Significant effort was necessary to identify this
quantity its definition is undisclosed and proprietary.
Figure 2. DEM model of the Vertimill screw—actual (R) and simulated (L)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
7 9 11 13 15 17 19 21 23 25
Time
Figure 3. Vertimill DEM Q-value results
Q

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Extracted Text (may have errors)

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3891
mills (Qiu et al 2001). Two decades later, a much more
sophisticated DEM model for Vertimill screw liner wear
was developed (Qiu et al 2024). This model can simulate
the Vertimill liner wear process, capturing the wear charac-
teristics (see Figure 3) and delivering physics related data
including power draw, media grinding energy, and colli-
sional energy.
Figure 4 shows additional DEM results for the
Vertimill. The quantity Q is a synthetic derived physical
quantity. Significant effort was necessary to identify this
quantity its definition is undisclosed and proprietary.
Figure 2. DEM model of the Vertimill screw—actual (R) and simulated (L)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
7 9 11 13 15 17 19 21 23 25
Time
Figure 3. Vertimill DEM Q-value results
Q

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3890
Vertimill Wear Sensing
Sudarshan Martins, Xiangjun Qiu
Metso
ABSTRACT: The Vertimill is a highly effective and reliable grinding solution consequently, it has been widely
adopted. However, like all other grinding technologies, it has faced challenges in managing wear life and
measuring charge levels. To address these issues, a new detection system has been developed. It offers a novel
way to determine and manage wear life. This solution is described, highlighting its capabilities and benefits.
Furthermore, the results of DEM simulations of the Vertimill, including wear processes, are presented. The
simulations confirm that the measurements provided by the new solution can estimate the state of wear of the
liners, producing an important tool for effective maintenance and management of the Vertimill. Overall, this
new sensor solution represents a positive advancement in the field of grinding technology and has the potential
to improve the efficiency and effectiveness of the Vertimill.
INTRODUCTION
The Vertimill is a vertical stirred mill used in the mining and
minerals processing industry for grinding materials to a fine
particle size. The motor turns the Vertimill screw, stirring
the grinding media and the slurry, as shown in Figure 1.
This stirring motion promotes a charge motion that
creates an efficient grinding environment for the ore.
However, this effect is not confined to the ore. The grinding
media and the screw liners are also subject to the effects of
the charge motion—they wear. The monitoring of the state
of the liner wear is addressed here. First, a description of
the major components of the technology is given. Next, the
results of one of the field deployments is presented. Finally,
the features and capabilities of the system are discussed.
THE VERTIMILL DEM
DEM, a computational mechanics method addressing
granular flow, has been widely used in the comminution
industry (Qiu 2016). In 2001, a DEM model, enhanced
with Archard’s wear mechanism, was developed to predict
liner wear in horizontal mills such as AG/SAG and Ball
Figure 1. A Vertimill

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Extracted Text (may have errors)

3890
Vertimill Wear Sensing
Sudarshan Martins, Xiangjun Qiu
Metso
ABSTRACT: The Vertimill is a highly effective and reliable grinding solution consequently, it has been widely
adopted. However, like all other grinding technologies, it has faced challenges in managing wear life and
measuring charge levels. To address these issues, a new detection system has been developed. It offers a novel
way to determine and manage wear life. This solution is described, highlighting its capabilities and benefits.
Furthermore, the results of DEM simulations of the Vertimill, including wear processes, are presented. The
simulations confirm that the measurements provided by the new solution can estimate the state of wear of the
liners, producing an important tool for effective maintenance and management of the Vertimill. Overall, this
new sensor solution represents a positive advancement in the field of grinding technology and has the potential
to improve the efficiency and effectiveness of the Vertimill.
INTRODUCTION
The Vertimill is a vertical stirred mill used in the mining and
minerals processing industry for grinding materials to a fine
particle size. The motor turns the Vertimill screw, stirring
the grinding media and the slurry, as shown in Figure 1.
This stirring motion promotes a charge motion that
creates an efficient grinding environment for the ore.
However, this effect is not confined to the ore. The grinding
media and the screw liners are also subject to the effects of
the charge motion—they wear. The monitoring of the state
of the liner wear is addressed here. First, a description of
the major components of the technology is given. Next, the
results of one of the field deployments is presented. Finally,
the features and capabilities of the system are discussed.
THE VERTIMILL DEM
DEM, a computational mechanics method addressing
granular flow, has been widely used in the comminution
industry (Qiu 2016). In 2001, a DEM model, enhanced
with Archard’s wear mechanism, was developed to predict
liner wear in horizontal mills such as AG/SAG and Ball
Figure 1. A Vertimill

3892 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
The Q-values show large differences initially. Over the
life of the liner, the differences in Q diminish and converge.
From the DEM, it is possible to isolate and identify the spe-
cific dynamic phenomena responsible for this behaviour:
wear.
THE WEAR SENSOR
The wear sensor system, as outlined in Figure 4, consists of
a detection system fixed the mill. The data is collected by an
edge panel. After some processing, the edge panel forwards
the data to the cloud where the full analysis is completed,
producing the full Q-values. From this Q, the wear state of
the screw can be quantified. The system has been released
by Metso as VertiSense ™.
TRIALS AND RESULTS
The system has been installed at several locations. The
selected mills are of various sizes, with different duties. The
results of one of the trials are presented in Figure 5. In this
case, the life of the liners was approximately 25 weeks. At
the end of that period, new liners were installed during a
brief shutdown.
When compared to the simulation results in Figure 4, a
strong correlation is observed, as illustrated in Figure 6. The
correlation coefficient between the measured and DEM
results is 0.86, indicating a high degree of correlation.
Therefore, the measurement system can determine the
Q-values of the Vertimill.
DISCUSSION
The strong relationship between the measurement and
DEM Q-values provides the ability to construct a system
which can associate the sensor measurements with screw
wear. VertiSense ™ as a Vertimill screw wear sensor works.
Due to the strong relationship between the measure-
ments and some of the dynamics within the mill, it may be
possible to use the measurements to tune the DEM simula-
tion, increasing the accuracy of the model. This coupling
between DEM and measurements is to be further explored.
Finally, the Q-value is found to be sensitive to the
charge level. There is potential for it to be used as an indica-
tion of the charge level in the mill.
Detection
System
Edge Control
Panel Analytics
Figure 4. VertiSense™ architecture
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 500 1000 1500 2000 2500 3000 3500 4000
Time (h)
Figure 5. Vertimill 1250 measured trial Q-values
Q

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Extracted Text (may have errors)

3892 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
The Q-values show large differences initially. Over the
life of the liner, the differences in Q diminish and converge.
From the DEM, it is possible to isolate and identify the spe-
cific dynamic phenomena responsible for this behaviour:
wear.
THE WEAR SENSOR
The wear sensor system, as outlined in Figure 4, consists of
a detection system fixed the mill. The data is collected by an
edge panel. After some processing, the edge panel forwards
the data to the cloud where the full analysis is completed,
producing the full Q-values. From this Q, the wear state of
the screw can be quantified. The system has been released
by Metso as VertiSense ™.
TRIALS AND RESULTS
The system has been installed at several locations. The
selected mills are of various sizes, with different duties. The
results of one of the trials are presented in Figure 5. In this
case, the life of the liners was approximately 25 weeks. At
the end of that period, new liners were installed during a
brief shutdown.
When compared to the simulation results in Figure 4, a
strong correlation is observed, as illustrated in Figure 6. The
correlation coefficient between the measured and DEM
results is 0.86, indicating a high degree of correlation.
Therefore, the measurement system can determine the
Q-values of the Vertimill.
DISCUSSION
The strong relationship between the measurement and
DEM Q-values provides the ability to construct a system
which can associate the sensor measurements with screw
wear. VertiSense ™ as a Vertimill screw wear sensor works.
Due to the strong relationship between the measure-
ments and some of the dynamics within the mill, it may be
possible to use the measurements to tune the DEM simula-
tion, increasing the accuracy of the model. This coupling
between DEM and measurements is to be further explored.
Finally, the Q-value is found to be sensitive to the
charge level. There is potential for it to be used as an indica-
tion of the charge level in the mill.
Detection
System
Edge Control
Panel Analytics
Figure 4. VertiSense™ architecture
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 500 1000 1500 2000 2500 3000 3500 4000
Time (h)
Figure 5. Vertimill 1250 measured trial Q-values
Q