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

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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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XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3889
Clark, D., Rodabough, D., Kane, A., Kone, B., Rajala,
J., Avenido, N., Bartholomew, K. and McIvor, R.E.
(2023). Improvements in grinding performance at the
Fekola gold mill, Mali West Africa. SAG Conference
Proceedings, Vancouver, 25 p.
Conger, W., DuPont, J-F, McIvor, R.E. and Weldum, T.P.
2018. Ball mill media optimization through functional
performance modelling. Mining Engineering, Nov.,
28–37.
Davis, E.W. 1925. Ball mill crushing in closed circuit with
screens. Bulletin of the University of Minnesota School
of Mines Experimental Station, v. 28, no. 42, p. 14–18.
Davis, E.W. 1946. Pulp densities (and size distributions*)
within operating ball mills. AIME Trans., v. 169,
p. 155–159. (*important content not mentioned in
title of article.).
Epstein, B. 1948. Logarithmico-normal distribution of
breakage of solids. Industrial and Engineering Chemistry,
v. 40, no. 12, p.2289–2291.
Finch, J.A. and Ramirez-Castro, J. 1981. Modeling min-
eral size reduction in the closed-circuit ball mill at Pine
Point concentrator. International Journal of Mineral
Processing, v. 8, p. 61–78.
Hinde, A.L. and Kalala, J.T. 2009. The application of a
simplified approach to modelling tumbling mills,
stirred media mills and HPGR’s. Minerals Engineering,
v. 22, p.633–641. (ag sag Mills +HPGRs uses.).
Laplante, A.R., Finch, J.A. and del Villar, R. 1987.
Simplification of the grinding equation for plant simu-
lation. Trans. IMM, Sec. C, v.96, C108–112.
McIvor, R.E., Bartholomew, K.M., Arafat, O.A., Daavettila,
S. and Savola, E. 2021. Coarse particle retention test-
ing on a ball mill at Lundin’s Eagle Mine Humboldt
concentrator, Proceedings of Australian Institute of
Mining and Metallurgy Mill Operators Conference,
Brisbane.
McIvor, R.E. 1988. Technoeconomic analysis of plant
grinding operations, Ph.D. thesis, McGill University,
Montreal.
McIvor, R.E., Lavallee, M.L., Wood, K.R., Blythe, P.M.
and Finch, J.A. 1990. Functional performance char-
acteristics of ball milling. Mining Engineering, March,
p.269–276.
McIvor, R.E. 1988. Classification effects in wet ball milling
circuits. Mining Engineering, Aug., p. 815–820.
McIvor, R.E. 1984. A material balance calculation proce-
dure for grinding circuit hydrocyclone selection. CIM
Bulletin, Dec., p. 50–53.
McIvor, R.E., Duval, L. and Leclercq, L. 1991. Use of func-
tional performance analysis for plant grinding media
testing and selection. Cobre ’91, v.2, p.145–155.
McIvor, R.E., Roux, Y. and Roy, M. 1994. Comparative
efficiency determinations of open circuit ball milling at
la Compagnie Miniere Quebec Cartier. CIM Bulletin,
July-Aug., p. 69–70.
McIvor, R.E., Weldum, T.P., Mahoski, B.J. and Rasmussen,
R.S. 2000. Systems approach to grinding improve-
ments at the Tilden concentrator. Mining Engineering,
Feb., p.41–47.
McIvor, R.E. 2006. Industrial validation of the functional
performance equation for ball and pebble milling cir-
cuits. Mining Engineering, Nov., p. 47–51.
McIvor, R.E. and Finch, J.A. 2007. The Finch-McIvor
functional performance-based grinding circuit model-
ing system, Proceedings of the Annual Meeting of the
Canadian Mineral Processors, Ottawa.
McIvor, R.E. 2014. Plant performance improvements
using grinding circuit “classification system efficiency.”
Mining Engineering, Sept., p.72–76.
McIvor, R.E., Bartholomew, K.M., Arafat, O.A. and Finch,
J.A. 2017. Ball mill classification system optimization
through functional performance modelling. Mining
Engineering, Nov., 18–31.
McIvor, R.E. and Makni, S. 2023. The effects of discharge
design on wet ball milling performance. SME Annual
Meeting, Denver, preprint 23-057, 5 p.
McIvor, R.E., Finch, J.A., and Makni, S. 2023. The truth
about population balance modelling. CIM Journal,
DOI: 10.1080/19236026.2023.2204708.
Metcom Technologies, Inc. 2023. On-line training program
to measure and improve the processing performance of
plant grinding operations. www.metcomtech.com.
Plitt, L.R. (1976). A mathematical model of the hydrocy-
clone classifier. CIM Bulletin, Dec., p.114–123.
Roberts, E.J. 1950. The probability theory of wet ball mill-
ing and its application. AIME Trans., v. 187, Mining
Engineering, Dec.: p. 1267–72.

Previous Page Next Page

Extracted Text (may have errors)

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3889
Clark, D., Rodabough, D., Kane, A., Kone, B., Rajala,
J., Avenido, N., Bartholomew, K. and McIvor, R.E.
(2023). Improvements in grinding performance at the
Fekola gold mill, Mali West Africa. SAG Conference
Proceedings, Vancouver, 25 p.
Conger, W., DuPont, J-F, McIvor, R.E. and Weldum, T.P.
2018. Ball mill media optimization through functional
performance modelling. Mining Engineering, Nov.,
28–37.
Davis, E.W. 1925. Ball mill crushing in closed circuit with
screens. Bulletin of the University of Minnesota School
of Mines Experimental Station, v. 28, no. 42, p. 14–18.
Davis, E.W. 1946. Pulp densities (and size distributions*)
within operating ball mills. AIME Trans., v. 169,
p. 155–159. (*important content not mentioned in
title of article.).
Epstein, B. 1948. Logarithmico-normal distribution of
breakage of solids. Industrial and Engineering Chemistry,
v. 40, no. 12, p.2289–2291.
Finch, J.A. and Ramirez-Castro, J. 1981. Modeling min-
eral size reduction in the closed-circuit ball mill at Pine
Point concentrator. International Journal of Mineral
Processing, v. 8, p. 61–78.
Hinde, A.L. and Kalala, J.T. 2009. The application of a
simplified approach to modelling tumbling mills,
stirred media mills and HPGR’s. Minerals Engineering,
v. 22, p.633–641. (ag sag Mills +HPGRs uses.).
Laplante, A.R., Finch, J.A. and del Villar, R. 1987.
Simplification of the grinding equation for plant simu-
lation. Trans. IMM, Sec. C, v.96, C108–112.
McIvor, R.E., Bartholomew, K.M., Arafat, O.A., Daavettila,
S. and Savola, E. 2021. Coarse particle retention test-
ing on a ball mill at Lundin’s Eagle Mine Humboldt
concentrator, Proceedings of Australian Institute of
Mining and Metallurgy Mill Operators Conference,
Brisbane.
McIvor, R.E. 1988. Technoeconomic analysis of plant
grinding operations, Ph.D. thesis, McGill University,
Montreal.
McIvor, R.E., Lavallee, M.L., Wood, K.R., Blythe, P.M.
and Finch, J.A. 1990. Functional performance char-
acteristics of ball milling. Mining Engineering, March,
p.269–276.
McIvor, R.E. 1988. Classification effects in wet ball milling
circuits. Mining Engineering, Aug., p. 815–820.
McIvor, R.E. 1984. A material balance calculation proce-
dure for grinding circuit hydrocyclone selection. CIM
Bulletin, Dec., p. 50–53.
McIvor, R.E., Duval, L. and Leclercq, L. 1991. Use of func-
tional performance analysis for plant grinding media
testing and selection. Cobre ’91, v.2, p.145–155.
McIvor, R.E., Roux, Y. and Roy, M. 1994. Comparative
efficiency determinations of open circuit ball milling at
la Compagnie Miniere Quebec Cartier. CIM Bulletin,
July-Aug., p. 69–70.
McIvor, R.E., Weldum, T.P., Mahoski, B.J. and Rasmussen,
R.S. 2000. Systems approach to grinding improve-
ments at the Tilden concentrator. Mining Engineering,
Feb., p.41–47.
McIvor, R.E. 2006. Industrial validation of the functional
performance equation for ball and pebble milling cir-
cuits. Mining Engineering, Nov., p. 47–51.
McIvor, R.E. and Finch, J.A. 2007. The Finch-McIvor
functional performance-based grinding circuit model-
ing system, Proceedings of the Annual Meeting of the
Canadian Mineral Processors, Ottawa.
McIvor, R.E. 2014. Plant performance improvements
using grinding circuit “classification system efficiency.”
Mining Engineering, Sept., p.72–76.
McIvor, R.E., Bartholomew, K.M., Arafat, O.A. and Finch,
J.A. 2017. Ball mill classification system optimization
through functional performance modelling. Mining
Engineering, Nov., 18–31.
McIvor, R.E. and Makni, S. 2023. The effects of discharge
design on wet ball milling performance. SME Annual
Meeting, Denver, preprint 23-057, 5 p.
McIvor, R.E., Finch, J.A., and Makni, S. 2023. The truth
about population balance modelling. CIM Journal,
DOI: 10.1080/19236026.2023.2204708.
Metcom Technologies, Inc. 2023. On-line training program
to measure and improve the processing performance of
plant grinding operations. www.metcomtech.com.
Plitt, L.R. (1976). A mathematical model of the hydrocy-
clone classifier. CIM Bulletin, Dec., p.114–123.
Roberts, E.J. 1950. The probability theory of wet ball mill-
ing and its application. AIME Trans., v. 187, Mining
Engineering, Dec.: p. 1267–72.