1132 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
IDEAS IPOPT algorithm. The objective function is mini-
mized by changing the manipulated variables, typically
operator setpoints.
The Digital Twin is integrated into the control system
and works along with the PID loops to make adjustments
that reduce energy consumption. Designing these types of
solutions can slowly drive towards finding ideal running
conditions and decreasing operator intervention, ultimately
leading toward autonomous operation.
REFERENCES
[1] Parthasarathi, P., Szaruga, V., and Szatkowski, M.
(2009), “Benefits of Dynamic Simulation for Mineral
Industry,” Recent Advances in Mineral Processing
Plant Design, pp. 84–92.
[2] Schug, B., and McGarry, M. (2016), “Utilizing and
Operator Training Simulator on a New Copper
Concentrator in Peru,” SME conference, Phoenix,
USA.
[3] Tripathi, A., Jara, M.I., Carvajal, C., and Gomez
Araya, F. (2016), “A Real-Time Dynamic Simulation
of Selective Molybdenum Flotation, Thickening and
Filtering Process,” SME conference, Phoenix, USA.
[4] Schug Brett, Anderson Caelen, Nazari Sohail,
Cristoffanini Carlos (2019) “Real World Improvement
Through Virtual Instrumentation at Oceana Gold
Haile,” Mining Engineering Magazine, pp. 20–25.
[5] Sepulveda Juan, Anderson Caelen, Schug Brett,
Cristoffanini Carlos (2019) “Digital Twin technology,
applied as virtual instrument at Oceana Gold Haile,”
World Gold Conference AusiMM, Conference
Proceedings, pp. 647–652.
[6] Cristoffanini Carlos, Gupta Arpit, Rana
AmandeepSingh (2020) “Uses of Digital Twins
in Mining,” Automining2020 7th International
Congress on Automation in Mining.
[7] Nazari Sohail and McGarry Matt (2018) “Digital
Twin in mineral processing,” McEwen Mining’s
Innovation Lunch and Learn Series.
[8] Wächter, A. and Biegler, L.T., 2006. “On the imple-
mentation of an interior-point filter line-search
algorithm for large-scale nonlinear programming.”
Mathematical programming, 106(1), pp.25–57.
IDEAS IPOPT algorithm. The objective function is mini-
mized by changing the manipulated variables, typically
operator setpoints.
The Digital Twin is integrated into the control system
and works along with the PID loops to make adjustments
that reduce energy consumption. Designing these types of
solutions can slowly drive towards finding ideal running
conditions and decreasing operator intervention, ultimately
leading toward autonomous operation.
REFERENCES
[1] Parthasarathi, P., Szaruga, V., and Szatkowski, M.
(2009), “Benefits of Dynamic Simulation for Mineral
Industry,” Recent Advances in Mineral Processing
Plant Design, pp. 84–92.
[2] Schug, B., and McGarry, M. (2016), “Utilizing and
Operator Training Simulator on a New Copper
Concentrator in Peru,” SME conference, Phoenix,
USA.
[3] Tripathi, A., Jara, M.I., Carvajal, C., and Gomez
Araya, F. (2016), “A Real-Time Dynamic Simulation
of Selective Molybdenum Flotation, Thickening and
Filtering Process,” SME conference, Phoenix, USA.
[4] Schug Brett, Anderson Caelen, Nazari Sohail,
Cristoffanini Carlos (2019) “Real World Improvement
Through Virtual Instrumentation at Oceana Gold
Haile,” Mining Engineering Magazine, pp. 20–25.
[5] Sepulveda Juan, Anderson Caelen, Schug Brett,
Cristoffanini Carlos (2019) “Digital Twin technology,
applied as virtual instrument at Oceana Gold Haile,”
World Gold Conference AusiMM, Conference
Proceedings, pp. 647–652.
[6] Cristoffanini Carlos, Gupta Arpit, Rana
AmandeepSingh (2020) “Uses of Digital Twins
in Mining,” Automining2020 7th International
Congress on Automation in Mining.
[7] Nazari Sohail and McGarry Matt (2018) “Digital
Twin in mineral processing,” McEwen Mining’s
Innovation Lunch and Learn Series.
[8] Wächter, A. and Biegler, L.T., 2006. “On the imple-
mentation of an interior-point filter line-search
algorithm for large-scale nonlinear programming.”
Mathematical programming, 106(1), pp.25–57.