OPTIMISATION OF A SAG MILL THROUGH TRAJECTORY AND POWER ... · PDF file-Mill Filling -Ball...

OPTIMISATION OF A SAG MILL THROUGH TRAJECTORY AND

POWER MODELLING

Paul Toor

- Problem Statement

- Case Study

- Trajectory Modelling

- Power Modelling

- Identifying Optimum Region of Operation

- Results & Benefits

- Summary & Conclusion

September 2015 Metplant Optimisation of a SAG Mill Through Trajectory and Power Modelling 2

Presentation Summary

Mill performance is very sensitive to total filling.

September 2015 Metplant Optimisation of a SAG Mill Through Trajectory and Power Modelling

Powell, M.S., van der Westhuizen, A.P. & Mainza, A.N. (2009). Applying grindcurves to mill operation and optimisation. Minerals. Engineering, 625–632.

Problem Statement

September 2015 Metplant Optimisation of a SAG Mill Through Trajectory and Power Modelling

However no mill filling

percentage is reported to the

control room, instead a

calculated mill load is

provided.

Problem Statement

The reported mill load is a arbitrary measure and is comprised of liner weight, the charge weight plus an offset. The inclusion of liner weight is particularly problematic as it is dynamic.

Load Reading= Charge mass + Liner mass + Offset

Problem Statement

Toor, P., Franke, J., Powell, M.S., Perkins, T., (2011), Quantifying the Influence of Liner Shape on Mill Performance. Proceedings International autogenous and semiautogenous grinding technology 2011, Sep. 25-28, Ed. Flintoff et al, Published CIM. .

Problem Statement

Ball trajectory is another critical parameter. •Overthrow causes liner damage and reduced efficiency.

•Underthrow causes damping of grinding action also leading to reduced efficiency.

Problem Statement

The assessment of ball trajectory cannot be done in isolation as the toe of the charge needs to be determined to make any meaningful assessment

Problem Statement

Proposed Methodology

•SABC

•Fixed Speed

•F80 50-100 mm (Dependant on ore source).

•Ball Top Size 125 mm

•Very little autogenous grinding. (BAG Mill)

Background Case Study

Trajectory Modelling

• Trajectories calculated at two week intervals.

• Outermost trajectory when liners new.

• Innermost trajectory when liners fully worn.

• 25 % Mill Filling required when liners are new

• Decrease in trajectory constant over time.

• Virtually impossible to overthrow media after 4 weeks of liner wear.

• Significant depletion in trajectory. Liner redesign recommend.

A model which relates the two most critical parameters in SAG milling

(Ball charge and Total Charge (%)) to a readily available output, Power

JKMRC Power Model

Power Curves

Ball Charge Is Reasonably Estimated from Inspections

and Mass Balancing

Power Curves

Example: Power = 1400 kW Ball Charge = 15% Total Charge=21.5%

Power Curves

Power Curves: Determining Optimum Regions

Target Power <97% Or 1450 kW

Target Power >1300 kW=86.67%

Target Mill Filling < 25%

Target Mill Filling > 18%

Target Ball Filling < 17.5%

Target Ball Filling > 12.5%

Case 1 Tph:~220 Power:~ 1300 kW Ball Charge:-13.3% Mill Load:~ 60t Mill Filling=21% Rock Filling=7.7% Rock to Ball Ratio~1:2

Case 2 Tph:- 205 Power:- 1410 kW Ball Charge:- 11 % Mill Load:~65 t Mill Filling=28 % Rock Filling=17% Rock to Ball Ratio~3:2

Real World Example

Case 2 Tph:- 210 Power:- 1410 Ball Charge:- 11 % Mill Load:~65 t Mill Filling=28 % Rock Filling=17% Rock to Ball Ratio~3:2

Actions Required

• Reduction in mill load set point 15t

• Addition of 2 tonnes of media

Real World Example

•Allows the calculation and tracking of critical parameters - Mill Filling - Ball Filling - Rock Filling

•Data can be coupled with Trajectory models for improved insight

•Not affected by liner mass

•Use of actual mill parameters rather than inference from mill load and or power.

Power Curves: Major Benefits

•Power curves/modelling utilised on a daily basis on site to determine ball charging regime and load set point.

•Improved mill performance

- Mill operating more consistently due to tight regulation of rock and ball filling. - Faster ramp ups post relines

•Methodology can be utilised for both fix and variable speed mills.

Power Curves: Major Benefits

• Load cells are adequate in informing the DCS, metallurgist and operators the rate of change of mill filling. However they do not provide information on the total mill filling or the composition of rock and ball.

•Mill filling is a critical parameter, with its optimisation the mill may be optimised.

•Power Modelling allows for an accurate method to determine mill filling in real time with no or few mill stoppages.

Conclusion

•Having developed power models it is reasonably straight forward to determine optimum operating regions.

•Furthermore ensuring the mill remains in the optimum region becomes significantly easier with knowledge of Total, Ball and Rock Filling.

•The end result being increased mill performance and improved liner management.

Conclusion

company/metso metsogroup metsoworld metsoworld metsogroup

www.metso.com

OPTIMISATION OF A SAG MILL THROUGH TRAJECTORY AND POWER ... · PDF file-Mill Filling -Ball...

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