calibre mill optimisation case study

8/9/2019 Calibre Mill Optimisation Case Study

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Presentation to The Mill Optimisation Summit 2011

Presented by:Paul Wilson

Technology Manager

Calibre Automation, Communications & Technology roup

Optimising SAG mill throughput:A case study in tuning


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Two SAG mills

1


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Porgera Mine, P!

"#$ Mega%att, ariable spee' 'rie

About $00 tonnes per hour per mill

(ighly ariable lithology %ith grin'ing )actors )rom* to 1+ ilo%att hours per tonne

The mills

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The mills

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The mills %ere o)ten unstable, seen as oscillationsin the )ee'rate tren' graphs

Unstable behaviour

"


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Loss of production

.

As much as 15% on bad days

Up to 380 ounces of gold per day on bad

days

At $425 U per ounce ! $1"0#000 per day

ou could hre a &ery good plant operatorfor that 'nd of money


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atural instability

+

(oor tunng causes natural nstablty


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Operator!caused instability

+

(oor operator s'lls also forces nstablty


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The control system

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(ighest leel

Minnoe epert system control

Optional top leel controlConstraint control

Mi'leel

Close' loop control

ottom leel

3elta4 'istribute' control system


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The "innove# e#pert system

/

A )u55y rules base' arti)icial intelligence system

6unning on a 2 epert system shell

6unning on a Win'o%s !T PC plat)orm

Taes 'ata )rom, & )ee's setpoints to, the loop

controllers on the 3elta4


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Performance comparison

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7pert system control is )ar better than poor operator control


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$hy mills go unstable %&'(

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)lls stall *bog or centrfuge+, -he beha&ourat ma.mum throughput s hghly non/lnear


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$hy mills go unstable %&)(

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ynamc beha&our of a mll s type 1

ontrol engneers recognse that type 1

systems are more l'ely to be unstable thantype 0 systems

aused by the nherent ntegraton n the mlltransfer functon


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Mill loa' 8leel9 is the integral o) the nett)ee'rate

level * + %,in- ,out(.dt

This in'uces a /0o

phase shi)t in the trans)er)unction %hich lea's to re'uce' stability


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-he ntegraton causes a phase shft


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Simulated integral response

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1# When a mill stalls it stops %oring#

2# The mill )ills %ith ungroun' material#

-# :t taes time to grin' out the roc an' get theout)lo% going again

So; the control system < plant operator must be;PAT/0T

$hy mills go unstable %&1(

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The result of operator impatience

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"ill under tuned e#pert system control

1-


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Section A to is the maimum spee' o) recoery to

preent stalling the mill again

0#pert system recovers from a motoroverheat event

1-


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The result

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:n 200" < 200$ mill pro'uction rose )rom

+$0,000 ounces to 1,000,000 ounces

At ="2$ >S per ounce that %as

231.45 million US increase per year

!ot possible %ithout increasing SA mill throughput


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0#tra energy used

.

-he dfference n energy usage beteenthe unstable one and the stable one s

the unstable one a&erages

25% more motor energy per tonne of product

than the stable one and produces

15% less product

hch adds 10% to the energy costs for the remander ofthe processng plant


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6ow was it done7

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3eelop a mathematical mo'el

>se tren' plots an' tests to characterisethemill 8)in' the characteristics o) mill behaiour9

7stimate )astest possible recoery times onthe %orstcase ores

6etune the epert system rules )or robust,al%aysstable behaiour


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6ow was it done7

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loc 'iagram mo'el o) mill behaiour


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6ow was it done7

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Trans)er )unction o) mill loa' to ore )ee'rate


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Additional development

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The 'ecision to secon'ary crush the har'er

ores#

A secon'ary crusher %as installe'# With a bit o) cleer

mathematics %e %ere able to estimate SA millgrin'ing )actor at the primary crusher# We use' this

to )ee' some o) the har' ore 8? @ 10 Whr per

tonne9 through the secon'ary crusher thusincreasing SA mill throughput on the har'er ore#


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,uestions

our Buestions are %elcome

Plant characterisation & trans)er )unction 'eelopmentis a comple process# : am happy to 'iscuss some

o) the metho's a)ter%ar's %ith anyone intereste'#

calibre mill optimisation case study

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