t h e e f f e c t o f g r i n d i n g o n m i l l p e r f o r m a n c e

8/3/2019 t h e e f f e c t o f g r i n d i n g o n m i l l p e r f o r m a n c e

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Pergamon0892-6875(00)00030-0

Minerals E ngineering, V o l . 1 3 , N o . 5 , p p . 4 8 5 - - 4 9 5 , 2 0 0 0 2 0 0 0 E l s e v i e r S c i e n c e L t dA l l r i g h t s r e s e r v e d0 8 9 2 - 6 8 7 5 / 0 0 / $ - s e e f r o n t m a t t e r

T H E E F F E C T O F G R I N D I N G O N M I L L P E R F O R M A N C E A TD I V I S I O N S A L V A D O R , C O D E L C O - C H I L E *

J .B . Y I A N A T O S , L . G . B E R G I - I~ an d J . A G U I L E R A C hem ical En gineerin g Department, Santa M aria U niversity, Valparaiso, Chile.E-mail: j yianato@ po_u i.utfsm.cl Divisi6n Salvador, C odelco-C hile, El Salvador, Ch ile(Received 9 November 1999; accepted 17 February 2000)

A B S T R A C TThis pa pe r presen ts a sensitivi ty analysis o f the impact the ore grinding level (% +212 microns) hasupon the rougher f lota t ion performance, where the m ain copper losses are re la ted to f ine p art ic les(less than 12 microns) with high content o f soluble copper a nd coarse par ticles (larger than 2 12microns) that are less l iberatedFirstly , a one ye ar grind ing data set, considering average daily shifts, was an alysed an d i t wa sshow n that the c lass ical B ond correla tion properly .describes the average trend o f the grind ingcircui t operat ion in terms o f ore tonn age, operat ional wor k index , prod uct part ic le s i ze dso andpo we r availabit 'i ty . On the other hand, the rougher f lota t ion k inet ic was characterized fro m pla nttesting. Th us, copper and moly recoveries wer e correlated by Klimpel 's mo del to describe theroug her flota tion performance, at different par ticle size classes, in terms o f design a nd operatingvariables. The copper recovery w as fo un d to be critically dependent on the ore grinding level , %+212 m icrons, an d the soluble copper content.Using the grinding and f lota t ion correla tions, a plan t s imulator , that in tegrates the grinding andf lota t ion capacit ies , w as bu i l t . The simulator w as val idated w i th plan t data fo r a range o f oretonnage, fo r different grind ing levels and at two po we r levels. The simulator is useful in selec tingthe grindin g reference, to identi fy cri tical requirements o f instrumentation, bottlenecks l imitingpla nt capacity, a nd to complement the supervisory control strategy. Thus, a po we rfu l tool toestimate the best comprom ise between ore tonnage a nd grinding le vel , in order to maximize th evalues recovery, was established 2000 Elsevier Science Ltd. Al l rights res erve d

K e y w o r d sGrind ing; flotation kin etics; particle size; m odelling; simulation

INTRODUCTIONT h e c o m p l e x i t y , o f t h e c o p p e r s u l p h i d e o r e a t D i v i s i 6 n S a l v a d o r , C o d e l c o - C h i l e , w i t h l o w f e e d c o p p e rg r a d e s , 0 . 6 - 0 . 8 % , a s w e l l as t h e a c t u a l l o w c o p p e r p r i c e , u s t i fy a n y e f f o rt n o p t i m i z e t h e o p e r a t i n g a n dc o n t r o l s t ra t eg i es . n e o f t h e k e y p a r a m e t e r s u s e d f o r c o n t r o l u r p o s e s i s t h e g r i n d i n g l e ve l , e f m e d a s t h eo r e p a r ti c l e e r c e n t a g e l ar g e r h a n 2 1 2 m i c r o n s , b e c a u s e a b o v e t h i s a r t ic l e i z e t h e c o p p e r r e c o v e r y s h o w sa s h a r p d e c r e a s e .

* Presented a t Minerals Engineering 99, Falmouth, Cornw all , U.K . , September 1999

485


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486 J.B. Yianatos et aL

E ! S a l v a d o r c o n c e n t r a t o rThe mine ope r a t i on i s unde r g r ound a nd t he mi l l i s l oc a t e d a t 2600 m a bove se a l e ve l i n t he A nde sC o r d i l le r a . T h e p l a n t tr e a ts a b o u t 3 4 0 0 0 t p d o f o r e c o n ta i n in g 0 . 6 - 0 . 8 % C u a n d 0 . 0 2 5 % M o . T h e g r i n d i n gc i r c u i t c ons i s ts o f f i ve pa r a ll e l s e c ti ons . F our s e c t i ons ope r a t e w i th a ba r m i l l 3 .05x4 .27m (10 ' x14 ' ) a nd tw oba l l mi l l s 3 .05x4 .27m (10 ' x14 ' ) , i n c onv e n t iona l a r r a nge me nt , wh i l e the f i f t h s e c t ion ope r a t e s w i th a ba rm i l l 4 .12x5 .49 m (13 .5 ' x l 8 ') a nd a s i ng l e ba l l mi l l 5 .03x5 .79m (16 .5 ' x l 9 ' ). Th e f l o t a t i on c i rc u i t c ons i s t s o ff i ve pa r a l le l r ough e r f l o t a t i on ba nk s , e a c h b a nk p r ov ide d w i th 9 W e m c o c e l l s o f 42 .5 m 3 (1500 f t3 ) , i na r r a n g e m e n t 3 - 3 - 3 . T h e c l e a n i n g st a g e c o n s is t s o f t w o r e c ta n g u l a r c o l u m n s ( 2 x 6 x 1 3 m ) i n p a r a ll e l a n d t w osc a ve ng e r ba nke s , e a c h p r ov id e d w i th 8 Do r r -O l ive r c e l ls o f 42 .5 m 3 (1500 f t3 ) , i n a r r a nge m e nt 2 - 2 - 2 - 2 .F igu r e I sho w s a n e xa m ple o f t he t yp i c a l c oppe r r e c ove r y d i s tr i bu t i on i n t he r ough e r f l o t a t i on ci r c u i t, i nt e r ms o f pa r t i c l e s iz e a t two g r ind ing l e ve l s , 22 .2% a nd 25 .6% +212 m ic r ons . B o th c u r ve s a r e s imi l a r a nd ,f o r t he r a nge o f i n te r e s t, no s i gn i f i c a n t e f f e c t o f t he g r i nd ing l e ve l upo n t he c oppe r r e c ove r y pe r s i z e c l a s sw a s ob se r ve d . T he m a in c opp e r l os se s i n rough e r f l o t a t ion ar e r e l a te d t o t he p r e se nc e o f f ine pa r t ic l e s , l e s stha n 12 mic r ons , w he r e , de sp i t e t he c oppe r mine r a l s be ing w e l l l ibe r a t e d , t he r e i s a s i gn i f i c a n t de c r e a se i nthe pa r t i c l e - bub b l e c o l l i s i on e f f i c i e nc y . A l so , a bou t 90% o f t he f r e e s t c l a s s, l e s s t ha n 12 mic r ons , w a sf ou nd a s so lub l e c oppe r . H ow e ve r , c oa r se pa rt i c le s l a r ge r t ha n 212 mic r ons c a use s i gn i f i c a n t l o s se s due t othe l a c k o f l i be r a ti on a nd f r o th t ra nspor t l imi t a t ions .T h i s s t u d y f o c u s e d o n e v a l u a t in g t h e i m p a c t th e c h a n g e o f th e g r i n d i n g l e v e l ( % o f o r e c o a r s e r t h a n 2 1 2mic r on s ) ha s upo n t he ove r a l l f l o t a ti on r e c ove r y a nd upon t he o r e th r oug hpu t ( tpd) . I n t h i s w or k , t he ove r a l lf l o t a t i on r e c ov e r y wa s c o ns t r a ine d t o t he r oughe r re c ove r y , s i nc e the m a in c opp e r l os se s oc c u r t he r e , wh i l et h e c l e a n i n g s ta g e c o p p e r r e c o v e r y w a s m o r e s t a b le a r o u n d 9 4 - 9 6 % .

O

8c-o

1009 080706 05 04 03020100

1 10 100A v e r a g e p a r t i c l e s i z e , m i c r o n s

Fig . l Cop per recovery versus par t ic le s ize .

. . . . . . 1

1000

G R I N D IN G M O D E L L I N G B A S E D O N O P E R A T I N G V A R I A B L E SI n o r d e r t o d e v e l o p a g r i n d i n g m o d e l b a s e d o n o p e r a t in g v a r ia b l es , d a t a f r o m o n e y e a r p l a n t o p e r a t io n w a suse d t o l i nk t he g r ound p r oduc t c ha r a c t e r i s t i c s w i th t he p r oc e s s va r i a b l e s , a c c or d ing t o t he f o l l owingr e l a t i onsh ips ,


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Effectof grindingon mill performance 4871 - - E n e r g y - O r e t h ro u g h p u t2--Pa r t ic le S ize D i istdbution3-C um ula t ive M eta l D i s tr ibu tionTh e f i r s t s tep w a: ; the val idat ion of the classical B ond's M odel in orde r tO correlate pow er (kW ') , orethroug hpu t ( tpd) ~nd gr inding level (% +212 microns) .F igure 2 shows the dai ly gr inding data , f rom January tO Decem ber 1998 , wh ere the c i r cu i t opera tes a tnorm al levels of u t il izat ion (95-98 %) o f the available pow er . Du r ing this t ime there was a per iod o f 80days where the gr inding ci rcui t was operated wi thout the largest bal l mi l l of the f i f th sect ion, whichdecre ased by 20 % the total avai lable pow er . F igure 2 shows the operat ion at 100% an d 80% p ow er level ,toge ther wi th pre~l ict ions f rom B on d' s m odel for an average min eral hardness (Wo rk Inde x was relat ive lyconstant 14.0 + 0 .4 k W/ton) and a n average feed part ic le s ize ((IF = 11200 + 120 0 microns) . Th e typica lopera t ion o f the m i l l a t f u ll power capac i ty was in the r ange o f 32000-34000 tpd o f minera l t h roughpu t ,f rom Janu ary to M ay , whi l e the g rind ing l eve l va ri ed f rom 18-23 % +212 microns. Du r ing the low p ow erper iod , June to Augu s t , the m inera l t h roughpu t was pu shed up to 30000 tpd w hi l e the g r ind ing l eve l va r iedin the range 23-2"V % +212 microns. A f ter restart ing the operation at fu l l powe r in September , the m ineralthroug hpu t reac hed the highe r levels 34000-37000 tpd by keeping the gr inding levels a t 23-2 6 % +212microns .

4 0 O O O

3oooo

25OOO

2 0 0 0 0

io P o w e r 1 0 0 % P o w e r 8 0 % ~ 1B o n d ' s M ode l - _ ~ 3~ o . ~ ~ ~ O o

iII

I I I I I

10 15 20 25 30 35Grind ing . leve l, % +2 12 m icro ns

Fig.2 Effect of gr inding on m ineral t reatmen t a t two p ow er levels .A l inear co r re l a t ion be tw een dso o f the g r ind ing p roduc t and the cor r espond ing g r ind ing l eve l (% +212microns) w as observed fo r the w hole r ange o f g r ind ing leve ls . F igu re 3 shows the m ode l f i t ti ng o f g r ind ingda ta from pa rticle size distr ibutions at differen t plant operating conditions, thus, th e correlations us ed tol ink the pow er consumption, the ore throughp ut and the gr inding level are ,B o n d ' s m o d e l

PT (tph) = (1)

10 Wi (1/~/dp - l /~/dr)w here T is the o re throughpu t (tpd), P i s the avai lable pow er (kW), W i is the Wo rk Index (kWh/t), dF and t ipare the fee d and produ ct s izes (80% passing) in microns, and


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488 J.B . Yianatos t al.T h e 8 0 % p a s s in g s iz e m o d e ldp (mic rons) = 8 .64 ( G ) + 38.62 (2)w he r e G i s t he g r i nd ing l e ve l (% +212 mic r ons ) .

.oE

09(/J

n

32O3OO28O26O24 022O20O2O

IiJ

I i_JI22 24 26 28 30 32Grinding evel, % +212 microns

F ig .3 P r od uc t pa s s ing s i z e (ds0) ve r sus g r i nd ing l e ve l (% +2 12 m ic r ons ) .Th e se c o nd s t e p w a s t he s e l e c t i on a nd f i t t i ng o f a pa rt i c le s i z e d i s tr i bu t i on m ode l i n t e r ms o f t he g r i nd ingl e v el . F o r t h i s p u r p o s e a S c h u h m a n n ' s t y p e m o d e l w a s a d a p t e d t o d e s c r ib e t h e s i ze d i s t r ib u t i o n b e l o w t h er e f e r e nc e s i z e (+212 mic r ons ) . Thus , t he s i z e modu lus d i * wa s se t e qua l t o 212 mic r ons , c o r r e spond ing t ot h e m a x i m u m s iz e c la s s , a n d t h e d i st r ib u t i o n m o d u l u s ' ~ " w a s f o u n d t o b e a l m o s t c o n s t a n t a n d e q u a l t o0 . 4 4 8 f o r t h e w h o l e r a n g e o f p l a n t d at a . F ig u r e 4 s h o w s g o o d a g r e e m e n t o f t h e m o d e l w i t h p l a n t d a t a f o rt he w ho le r a ng e o f g r ind ing l e ve l s , a nd t he r e su l ti ng c o r r e la t i on wa s ,T h e p a r t i c l e s i ze d i s t r ib u t i o n m o d e lYi" = ( I0 0 - G ) (d i /2 12 ) '44s (3)w he r e Y i" i s t he c um ula t i ve pe r c e n t l e s s t ha n d i s i z e c la s s a nd G i s t he g r i nd ing l e ve l (% +2 12 mic r ons ) .

8 0

7 0c

Q s o

5 o

2-io 4O3 0

0

~ ~ 22.2%+212 m icrons0 2 5 .6 % + 2 1 2 m ic rons 31.0%+212 m icrons~ M o d e l

5 0 1 0 0 1 5 0 2 0 0Par t i c l e S ize , m ic rons

2 5 0

F ig .4 F e e d s i z e d i s tr i bu t i on mode l .


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Effectof grinding on m ill performance 489Th e third s tep wa. ,; the correlation o f the m etal d is t ribut ion as a fun ct ion o f the feed s iz e dis t ribut ion,cons ider ing the g oo d f it ting o f the correlation repor ted by Ba zin e t a l . ( 1994) and E dwards and Vien[1999]. F igu re 5 show s the exper imental data f rom dif ferent p lant operat ing condit ions (M -I , M -2 and M -3) and the m ode l f it ting.

' 1

0 . . . . . I0 2 0 4 0 6 0 8 0 1 0 0

CumulaUve % P assing S izeFig.5 C umulat ive cop per dis tr ibut ion mod el .

A cu b ic po lynom ia l m ode l wa s found to descr ibe the p lan t da ta p roper ly , w h ich i s in goo d agreem ent w i thprev ious observ at ions , and the resul t ing correlation w as ,T h e c u m u l a t i v e c o p p e r d i s t r i b u t i o n m o d e lZ i" = 1.11 2 Yi" + 0.00688 (Yi ')2 - 0.0000 8 CYi')3 ( 4 )w here Z { is the curau lat ive copp er dist r ibut ion corresponding to Yi '. Equat ion (4) w as con s traine d to e nsuretha t the bou ndary cond i t ions a t Yf equ a l 0 and 100% , a l so co r respond to Z i" equa l s 0 and 100 % ,respect ively . In summary, the s imple models to descr ibe the gr inding operat ion are l inked as shown inF igu re 6 .

W i, P S, d * Ao . .A 3 X F

t , 0 I 1% + 2 1 2 u m

, - .= 1 M O D E Lv I z ;P O W E R P A R T I C L E

S I Z ED I S T R I B U T I O NC U M U L A T I V EM E T A LD I S T R I B U T I O N

Fig.6 Grinding plant simulation.


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490 J.B. Yianatos e t a l .

FLOTATION MODELLING BASED ON OPERATING VARIABLESThe rougher circuit at Salvador consists of 5 parallel lines, each one provided with 3 banks of 3 mechanicalcells, in series. The rougher flotation kinetics were described by Klimpel's model, which has beenpreviously used by Cort6s e t a l . [1995] to describe other plant operations with a very good agreement.Klimpel's model considers a rectangular rate constant distribution, that allows for a more realistic andflexible approach, while keeping the parsimony principle of using the minimum number of parameters. Inthis case the parameters are two, the maximum rate constant kr~x and the maximum recovery at infinitetime, R~.Figure 7 shows the flow of information. The input data considers the mineral throughput, feed grade andmetal content of valuable minerals, solids percent, cumulative size and metal distribution and circuitcharacteristics such as the effective volume of each cell. The model output gives the cumulative recoveryand grade, and the residence times along the rougher bank.

CUMULATIVESIZE AND METALDISTRIBUTIONS

Roo k max

J 1:[ FLOTATIONM O D E L "

t Ttpd, % Sol ids CIRCU ITCHARACTERISTICS

R E C O V E R YG R A D E

Fig.7 Rougher flotation simulation.The correlation to describe the flotation operation of N cells in series was,K l i m p e l ' s m o d e l

Ri Plant = R ioo 1 - ki(N-1) x(5 )

where Ri Plant, and Ri, represent the actual plant recovery and the maximum plant recovery at infinite time,of the i species, ki is the maximum rate constant of the i species and x is the effective residence time o f thepulp in one cell of the bank. The calculation of the cumulative recovery cell by cell along the bank allowedestimation of the effective residence time.P a r a m e t e r e s t im a t i o nIn order to estimate the model parameters, two approach were used. Firstly, kinetic sampling of the rougherflotation banks allowed adjustment of mass balances from assays of different species and size classes.Thus, the fitting of Klimpel's parameters for different size classes was developed from plant data. Figure 8shows an example of the kinetic data per size class from plant tests, together with the model fitting.A second approach was to scale-up the Klimpel parameters from laboratory batch data. In this case, thebatch tests that arc regularly performed in order to predict the behaviour of the future mineral during the


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E f f e c t o f g r i n d i n g o n m i l l p e r f o r m a n c e 4 9 1

next month, were 1ased to match the average results of the actual rougher flotation operation for the samemonth. Thus, scale-up factors were derived to predict the plant operating parameters from batch tests.

1 0 0

8 0

~ . 6 08

4 00

2 0

0

A

" - 4 5 umA " - 2 1 2 + 7 5 u m[ ] " + 2 1 2 um " - 7 5 + 4 5 u m

Kl impel 's Model[ ]

i I i i i t i i i i

0 1 2 3 4 5 6 7 8 9 1 0C e l l r u b b e r

Fig.8 R oughe r f lotat ion k inet ics pe r size classes.

S c a l e - u p f a c t o rsThe firing of the average rougher recovery with the recovery estimated from monthly batch tests, for 7months, allowed tile following scale-up factors to be fittedRi oo, p lan = 0.989 Rioo, Lab (6)ki, Plant = ki, Lab / 2.5 (7)Effect of so luble c .opperA critical problem affecting flotation recovery is the presence of soluble copper. A mineralogical studyshowed that soluble copper was mainly related to the presence of oxide minerals and other non-sulphidecomplex species. Figure 9 shows the copper rougher recovery versus the ratio between soluble copper andtotal copper in the feed ore. It can be seen that the amount of soluble copper varies typically from 6 to 15%of the total copper in the feed, which causes significant variations (5-7%) in the overall copper recovery. Inorder to account for the presence of soluble copper in model predictions, laboratory batch tests weredeveloped to characterize the kinetics of soluble copper and non-soluble copper.Figure 10 shows an example of experimental results from batch tests and the fitting of Klimpel's model forsulphide copper and soluble copper, in order to get the batch parameters. A final recovery higher than 90%for the sulphide copper and lower than 30% for the soluble copper was typically observed.


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492 J.B. Yianatos e t a l .

00 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8n,.- Iot -.- 1Orr

9 0

8 0

70

6 0

50

O

i ~ i i i i i

4 6 8 10 12 14 16 18 20Ratio Soluble Cu / Total Cu, %

F ig . 9 E f fec t o f so lub le coppe r on rougher f lo ta t ion r ecovery .

100

8 Se0

w w

Of . )

4 0

Sulphide Cuo Soluble Cu

Klimpel

020

n o 0

/0 I I I I I

0 5 10 15 20 25 30Time, min

Fig. 10 Klim pel ' s mo del f i t.F igu re 11 shows an e xam ple o f the rougher f lo tat ion s im u la tion , ce l l by ce l l , u s ing param ete r s f rom ba tchscale-up.I n genera l, p red ic t ions w ere in goo d agreem ent w i th p lan t da ta in te rm s o f the f 'm al cum ula t ive r ecov eryand g rade . F igu re 12 show s the ag reem ent be tw een the rougher f lo ta t ion opera tion , in te rm s o f averagecopp er r ecove ry f rom 7 m onths, and the co r respond ing es t im ated copp er r ecovery based on s ca le -up f ac to r sf rom b a tch da ta.


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Effecto f grindingon m ill performance 493

100 504 5

80 Reco:v. " 40eo C - u r n .

~o --e-- Cum . G rade 25 .,_8 4 0 20 8

152O 10

5o d ( . . . . . . ,~ ~ ~ o

0 1 2 3 4 5 6 7 8 9 .10Cel l number

8 6

8 8 4

8O

g.I

F ig . 11 R o ugh e r f l o t a ti on simu la t i on .

7 6 K . . . .7 6 7 8 8 0 8 2 8 4 8 6

R o u g h e r re c o v e r y , % C uF ig . 12 R ou ghe r r e c ove r y p r e d i c t ion f r o m sc a l e - up .

E F F E C T O F G R I N D IN G O N M I L L P E R F O R M A N C ET h e g r i n d i n g a n d f l o t at i o n m o d e l s d e r i v ed a n d v a l i d a t e d f o r t h e w h o l e r a n g e o f p la n t d a t a c a n b e i n t eg r a t edt o p r e d i c t t h e e f f e c t o f g r i n d i n g o n m i l l .p e r f o rm a n c e . F i g u r e 1 3 s h o w s t h e r o u g h e r c o p p e r r e c o v e r y ( % ) a n dt h e c o p p e r t o n n a g e ( tp d ) r e c o v e r e d t o t h e c o n c e n tr a te i n te r m s o f t h e g r i n d i n g l e v e l ( % + 2 1 2 m i c r o n s ) . I tc a n b e s e e n t h a t a m a j o r c h a n g e i n t h e g r in d i n g l ev e l, f r o m 3 0 % t o 2 0 % + 2 1 2 m i c r o n s , i n cr e as e s t h e c o p p e r


10/11

494 J.B . Yianatos t a l .rougher r ecov ery by 4 . 5% , w hi le decreasing the copper p roduc t ion by 13 .6% . Here , i t can be s een tha t fo rthe actual c i rcui t character is t ics and metal pr ices the ope rat ion at grinding levels less than 2 0% +21 2mic rons w as not econom ical ly optimal , due to the s ignificant dec rease in cop per concentrate produc t ion,despi te the increase in f lo tat ion recov ery .

9 0 7 r 2 2 . 0#

8 8ok . .

0 .0 .o 8 4ot~

e-O)- ' 8 2on~

8 0

7 8

- - e - - C u re c o v . %- - - [ - - o - C a c o n c . t p d I

1 5r i

2 0 2 5G r in d i n g le v e l , % + 2 1 2 m ic r o n s

2 1 0 e "2 0 o

p. 1 8 0 " i0 .1 7 0 oO

I 1 6 03 0

Fig. 13 C opp er recover y and coppe r product ion versus gr inding level .How ever , the c i r cu i t opera tion near the l im i t o f c ir cui t capac i ty inc reased the f r equency o f o ther po ten t ia lt roub les ( over f low, b lockage , shu t -down) tha t cause was te o f t im e and low er equ ipm ent u t i li zat ion . I nsum m ary , the bes t opera t ing po in t was found c loser to 22-24% +212 m icrons , in a good com prom isebe tw een cop per r ecovery , copp er p roduc t ion and the l im i ting capac it ies o f the p lan t.

C O N C L U S I O N SUsing s imple gr inding and f lotat ion models , a s imulator was bui l t to in tegrate the gr inding and f lotat ioncapac i t i es. The s im u la to r was va l ida ted w i th p lan t da ta fo r the r ange o f typ ica l opera t ing con d i t ions , on ao n e y e a r p e r i od .The r esu l t s were use fu l in s e lec t ing the p roper g r ind ing leve l ( 20-25% +212 m icrons ) accord ing to themineral throu ghpu t required (3000 0-35 000 tpd), to ident i fy cr it ical ins trumentat ion (need for on- l inepar t ic le s ize ana lys is ) and circui t bott lenecks .Max im um copper p roduc t ion ( tpd) was observed a t the m ax im um c i r cu i t capac i ty ( tpd) , desp i te thedecrease in the rougher copp er recovery .A po w er fu l too l to es t im ate the bes t com prom ise be tw een the o re tonnage and the g r ind ing leve l wases tabl ished, in order to maximize v alu es ' produc t ion and benef its.A h igher l eve l o f au tom at ion and a su perv i so ry con t ro l st r a tegy w i l l soon he lp to im prove the m i l lperform ance, b y adding direct mea surem ent of par tic le s ize, on-l ine x -ray analis is o f the roug her co ppe rconce ntrate and autom ation o f the air and level control in rough er f lo tat ion.


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Effectof grindingon mill performance 495A C K N O W L E D G E M E N T S

Th e au thors are grateful to E1 Salvado r Division o f Codelco-Chile for providing access to thei r p lant andfor valuable assistance in the exper imental work. Funding for process model l ing and control research isp rov ided by CONICYT, p ro jec t Fondecy t 1990859 , and San ta M ar ia Univer si t y , p ro jec t 992723 .

R E F E R E N C E SBazin, C . , Grant, R . , Cooper , M . and Tessier, R . , Predict ion of metallurgical p er form ances as a funct ion off ineness of gr ind, In Pr oc. o f the 26 h Annua l G eneral Meeting o f Canadian Mineral Processors,Ottawa, 1994Edw ards , R . and Vien , A . , Appl ica tion o f a m ode l based s i ze - r ecovery methodo logy , In Control andOptimization in Minerals, Metals an d Materials Processing, ed. D. Hodouin, C. Baz in and A. D esbiens,CIM , Quebec , 1999, pp .147-159Cor tes, F .L., Yianatos, J .B. an d Ur tubia , H.C. , C haracterization o f the co pp er-m oly col lect ive f lotat ioncircuit at Divisi6n Andina, Codelco-Chile, In Copper'95: M ineral Processing an d Environment, ed . A .Casal i, G .S. Dobby , C. M ol ina and W. Thoburn, I IM Ch-CIM -AIME, Sant iago, Chi le, 1995, pp. 37-51

C o r r e s p o n d e n c e ; o n p a p e r s p u b l i s h e d i n M i n e r a l s E n g i n e e r i n g i s in v i te d , p r e f e r a b l y b ye - m a i l t o b w i l l s @ , m i n - e n g . c o m , o r b y F a x t o + 4 4 - ( 0 ) 1 3 2 6 -3 1 8 3 5 2

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