Simulation — the modern cost-effective way to solve crusher circuit processing problems

International Journal of Mineral Processing, 29 (1990) 249-265

249

Elsevier Science Publishers B.V., Amsterdam

Simulation - the m o d e m cost-effective way to solve crusher circuit processing problems R.P. King Department of Metallurgyand MaterialsEngineering, Universityof Witwatersrand, 1 Jan SmutsAvenue, Johannesburg (South Africa) (Received April 11, 1989; accepted after revision January 30, 1990)

ABSTRACT King, R.P., 1990. Simulation- the modern cost-effective way to solve crusher circuit processing problems. Int. J. Miner. Process., 29: 249-265. Simulation is an effective technique for the improvement of crusher plant performance, and it is now used routinely by some crusher manufacturers for both plant design and trouble shooting. MODSIM is probably the most versatile ore dressing-plant simulator in general use in the mineral-processing industry today. A case study using MODSIM applied to the crusher circuit of a major uranium producer is described in this paper. This study demonstrates the effectiveness of simulation to improve plant performance when reliable and effective models of the unit operations are available. The study was commissioned to investigate a 2000qon/h 4-stage crusher plant to identify a strategy to increase production at a finer product size. After an intensive technical audit on the plant, successful simulation was achieved for the existing operating conditions. The simulator was then used to identify the production bottlenecks and to establish plant modifications to meet the required production objectives in a cost-effective manner.

INTRODUCTION

Plant simulation techniques are becoming increasingly effective and therefore more frequently used as tools to assess and improve plant performance. This is particularly so with crushing plants because the unit operations of crushing and screening can be described by reliable and accurate models. The study reported here was undertaken to establish cost-effective modifications to the fine crushing plant of Rossing Uranium Ltd., and the application of simulation to address some of the possibilities is described. The study was undertaken by a team consisting of personnel from Nordberg (Pty) Ltd., the Department of Metallurgy and Materials Engineering of the University of Witwatersrand, and Rossing Uranium Ltd. The objectives of the study were: ( 1 ) to investigate and establish all process and operating parameters under the current operating conditions; (2) to es0301-7516/90/$03.50

© 1 9 9 0 - - Elsevier Science Publishers B.V.

250

R.P KING

tablish the complete mass balance and size distribution flowsheet for the present configuration and for the plant under various proposed alternative flowsheet configurations; (3) to estimate energy, steel, and other cost reductions expected from any proposed plant modifications; and (4) to back up all proposals by basic engineering information and detailed flowsheet calculations. Simulation effectively addresses the second and fourth of these objectives and provides the necessary information to permit the calculation of energy and other cost savings to meet the third of the objectives. Nordberg Inc. of Milwaukee, have pioneered this approach and their Circuit Analysis Program (CAP) is now in use worldwide for the development and analysis of crusher circuits. Significant improvements in worker proouctivity and the quality of flowsheet design have been reported (O'Bryan, 1987). The application of simulation to crusher flowsheet design has been well described by Magerowksi and Karra (1982) and there is no doubt that simulation techniques will play an ever-increasing role in the future. This study afforded the opportunity to use both MODSIM and CAP within the context of a real major plant analysis. The application of MODSIM to this problem is discussed in detail in this paper. The first objective was addressed by undertaking a detailed technical audit on the plant which included the measurement and recording of all relevant engineering parameters, together with tonnages and size distributions of key process streams. The most important plant improvement required from this study was the reduction of the final product size from 80% passing 10.5 m m as in the existing circuit to 80% passing 7 mm. DATA COLLECTION

The data collection was undertaken over a period of five days during which the plant was operated sunder conditions close to normal. Production was, however, interrupted to permit the necessary sampling to be undertaken. Great care was taken to ensure that all samples were representative of normal operating conditions. The key process variables measured were the tonnages and size distributions in those streams that were diagnostic of the operation of each of the units in the plant. The size distributions and tonnages were measured by stopping the appropriate conveyor belts in the plant in the plant and carefully cutting 1-m sections from the belt load. Total mass and size distributions of these samples were determined in the usual way. The existing plant flowsheet is shown in Fig. l, and the streams from which samples were taken are identified in Table I. When necessary, flow of material in portions of the plant was stoppexi to allow the sampling of only one of the parallel streams. For example, both east and west secondary crusher products

SIMULATION OF CRUSHER CIRCUIT PROCESSING

PROBLEMS

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TABLE I Stream identification and sample point location Stream number

Identification

Comments

Coarse ore reclaim conveyor Secondary crusher feed - west Secondary crusher feed - east Secondary crusher product - west Secondary crusher product - east Tertiary screen under size - west Tertiary screen under size - east Tertiary crusher product - west Tertiary crusher product - east Quaternary crusher product Quaternary screen underflow Final mill-feed product Tertiary screen top-deck overflow Tertiary screen lower-deck overflow Quaternary screen overflow

1

2 3 4 5 31 35 37 25 45 46 36 10 17 40

No No No No

flow through east secondary flow through west secondary flow through east tertiary flow through west tertiary

TABLE 1I Important operating variables in existing plant Unit

Type

Operating parameters

Secondary crushers

7-ft standard Symons cone crushers

Closed-side settings: west 49.1 ram; east 51.7 m m

Tertiary screens Double-deck polyurethane

i

¢

Topdeck:

49-ram square opening 4 l-ram ribs 23.4% open area 5.486 m × 2 . 1 3 4 m 18 ° inclination Lower deck: 15.2-mm square opening 10.3-ram ribs 25.01% open area 6.094 m × 2,134 m 18 ° inclination

Tertiary crusher

7-ft short-head cone crushers

Closed-side settings west:No. 1 13.1 mm, No. 2 11.9ram east: No. 3 13.7 ram, No. 4 12.6 m m

Quaternary crushers

7-It short-head cone crushers

Closed-side settings No. 1 8.17 ram, No. 2 8.6 m m

Quaternary

6 X single-deck polyurethane

20.0-mm square opening 11.5-mm ribs 27.7% open area 5.48 m X 2.0 m m 18 ° inclination

s~'eens

253

SIMULATION OF CRUSHER CIRCUIT PROCESSING PROBLEMS TABLE III

Measured size distributions (percent passing indicated size) Size (ram)

Stream Stream Stream 1 Stream Stream Stream Stream Stream Stream Stream Stream Stream 2

3

reeonstr. 4

5

31

35

37

100.0 99.6 94.8 90.9 78.0 64.3 52.3 47.3 40.0 30.7 27.5

. . . . 100.0 99.6 97.5 80.1 71.2

. . . .

970

366

366 +352 718

25

45

46

36

from 2&3 150 100 70 63 50 37.5 25 19 12.7 6.4 4.7

88.3 76.1 66.2 63.5 57.3 48.1 40.5 35.1 29.4 23.1 20.8

Flowrate 1071 (tons/

81.7 61.1 51.6 48.6 44.6 38.0 33.0 29.8 25.6 22.3 20.0 933

85.2 69.1 59.4 56.6 51.4 43.4 37.0 32.6 27.6 22.7 20.4 2004

100.0 91.9 87.9 75.5 59.6 48.9 42.9 35.6 26.9 24.2 1150

h)

. . . . 100.0 99.3 82.1 73.2

. . . . . . . . . . . . . . . . 100.0 . . . 99.7 100.0 100.0 93.6 94.4 99.5 80.7 81.4 95.2 55.7 53.5 70.4 37.2 30.0 39.4 29.4 25.6 33.1 856 724 +724 1580

677

. 100.0 99.0 96.5 79.6 50.0 43.0 1403

100.0 88.3 58.0 50.6 2270

were sampled on the conveyor indicated as stream 35 in Fig. 1. Only one of the parallel crusher lines was operated while loading the belt for sampling. Crusher gaps were determined by leading, and when necessary, gaps were adjusted to ensure uniform operation during the entire the entire audit period. Current drawn by the crusher motors under operating load, as well as under no-load conditions, was determined from existing plant instrumentation. Screen dimensions and screen apertures were measured by direct observation. Screen vibration amplitudes and motions were recorded for each screen. Samples of screen overflows were taken by the manual lunge method and are consequently less reliable than the belt samples taken. Conveyor belt speeds were determined from measurements of the drive drum diameters and rotational speed. The key operating variables that were measured are listed in Table II. The measured size distributions and tonnages are given in Table III. SIMULATION

OF THE EXISTING

FLOWSHEET

MODSIM is a modular simulator that can simulate any or dressing-plant flowsheet. Models are required for the description of the operation of each unit in the plant. For use within MODSIM, a model must be capable of accepting as input the complete description of the feed to the unit and calculating the nature of the product stream in detail sufficient for the needs of the simulation. The parameters that described the size and operating conditions

254

R P KING

of each unit must be supplied to the simulator. When simulating an existing plant, these operating parameters must match the values actually set up on the plant. For the Rossing crusher circuit, models were required for the segregating action of the 1000-ton coarse ore bin, for the standard and short-head cone crushers, and for the double- and single-deck screens. A model was developed to describe the measured segregation in the coarse ore bin because the segregation was too large to be ignored. Tow effects were modelled: the unequal discharge rates caused by variations in the operation of the two apron feeders under each discharge and the tendency of coarser particles to discharge preferentially to the east side stream because of segregation in the bin. The measured flowrates and size distributors in the products permitted the development of a simple empirical model. The fine material (up to 10 m m ) splits in direct proportion to the overall mass flows. Intermediate sizes ( 10 m m to 50 m m ) favoured the west side to the extent of 20%. Larger sizes (over 50 m m ) favoured the east side increasingly as size increased. The recovery to the west side decreased by 7.2% as the size increased by a factor of 2. The model used for the cone crushers is based on the well-known classification and breakage-zone developed by Whiten at the Julius Kruttschnitt Mineral Research Centre (Whiten, 1973; Whiten et al., 1979 ). Karra ( 1982 ) has demonstrated that this model can be used to describe the operation of the short-head cone crusher as well as the standard cone crusher. The behaviour of the crusher is modelled through a classification function and a breakage function. The classification function defines t h e chance that a particle of a given size will actually be crushed during the nipping period of the crusher cycle. Thus the function C(x) is the fraction of material of size x that will be crushed during a nip. Material that is not crushed, is presumed to be discharged directly through the crusher into the product stream. Material that is crushed, produces an entire spectrum of particle sizes. The size distribution of the products of breakage is described by a breakage function B (x,y) which is defined to be the fraction of daughter particles smaller than size x that result from the breakage of particles on size y. The daughter particles are themselves subject to further classification to select those that will be broken further during subsequent crusher nips. The operation of the crusher can be completely described by the classification function and the breakage function. The forms of these functions used are given by:

C(x) =0

x~d~

=1

dl <<.x <~d2

= 1.0

kd,

x>d2

(1)

SIMULATION OF CRUSHER CIRCUIT PROCESSING PROBLEMS

255

and: B(x,y) = G(x/y)

"l + ( 1 - G ) ( x / y ) n2

(2)

The parameters in these functions must be related to the way the crusher is set up. In eq. 1, dl represents the smallest size that the crusher can nip and therefore break, while d2 represents the largest particle that can pass through the crusher during the fully open part of the cycle, dl and dE are affected largely by the closed-side setting of the machine. Whiten et al. (1979) and Karra (1982) have found a linear dependence between those variables. Careful experimentation by Whiten et al. (1979) has revealed a weak inverse dependence of dE on the feed rate to the crusher, but our data were not sufficiently comprehensive to reveals this effect. We have accordingly modelled dl and dE by: dl =0.653 CSS

(3)

dE = a CSS

(4)

The value of a was found to vary with crusher type, being close to 1.7 for the standard cone crushers used as secondaries, and 3.5 for the short-head cone crushers used in the tertiary and quaternary stages. A value of n = 1 was used for the standard cone crushers, and n = 3 for the short-head crushers. The parameters in the breakage function eq. 2 are also machine-specific, n l and n2 were fixed at the values suggested by Whiten et al. (1979) for the standard cone crusher and by Karra ( 1982 ) for the short-head crusher. Thus: n, = 0.5 standard = 0.518 short-head and: n2 =

4.5 standard

= 2.475 short-head The parameter G represents the fractional production of fines from singleparticle breakage events within the crusher. The value of this parameter is assumed to be a function of the machine type and of the ore, but is assumed to be independent of the crusher setting. Values of a and G were found for each crusher in the circuit to match the measured size distributions in the streams that were sampled. No special parameter estimation procedures were used. The parameters were simply varied until a good fit was obtained with the measured data. MODSIM does not offer an automatic parameter estimation mode although its companion program MICROSIMI~ does The values used are given below:

256

R.P. KING

Secondary crushers

West East

Tertiary crushers Quaternary crushers

G = 0.15, G=0.20, G=0.32, G = 0.32,

a = 1.8 a=l.6 a=3.5 a = 3.5

These parameters are entirely reasonable, and the correspondence between the predicted size distributions and those measured can be seen in Fig. 2. The agreement can be considered to be very satisfactory, and the crusher model used can be regarded as reliable. The model used to describe the operation of the screens in the plant was adapted from a model described by Karra ( 1979 ). This is a predictive model of screen behaviour and is based on the conventional description of screening behaviour through a set of capacity factors which depend on the tonnage and size distributions of the material fed to the screen and on the nature of the screen itself. Karra's model is based on considerable operating data and was developed to provide a description of screening behaviour that is as close as possible to conventional industrial practice for the design and assessment of screening performance. Consequently, Karra's model can be related directly to well-established industrial practice. The model can be evaluated using wellunderstood procedures. Karra was able to establish the parameters in the model using the accumulated experience of screen performance available within his company. The model is considered to be robust and reliable and is

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SIMULATION OF CRUSHER CIRCUIT PROCESSING PROBLEMS

2 57

used in MODSIM without change. It was found to be entirely satisfactory for the present study and was very effective in allowing a useful characterization of the behaviour of the screens in the Rossing circuit. A brief description of the model is given here, and those aspects of the model that can be specially exploited by MODSIM are highlighted. The model is based on the well-known procedure for assessing the capacity of a vibrating screen through the basic capacity factor, A, which defines the tonnage of undersize that a particular screen can transmit per unit screen surface area. This basic factor is increased or decreased depending on the nature of the feed and conditions on the screen. A number of capacity factors allow for the amount of oversize in the feed (factor B), the amount of half-size in the feed (factor C), the check location (factor D), wet or dry screening (factor E), and material bulk density (factor F). These factors all have a value of unity at the nominal standard operating condition and move down or up as the screen duty becomes more or less arduous. Thus the model makes use of an index that defines the duty of the screen in its position in the flowsheet. This index which Karra designates as K is defined as: tons of undersize in the feed/unit area of screen

K-

ABCDED

(5)

Karra gives formulas for the calculation of each of the factors A to F, and these are programmed into the MODSIM screen model. These formulas relate the factors to the physical characteristics of the screen and to the nature of the feed. Thus Karra's model can be selected for use in a MODSIM simulation only if the physical characteristics of the screen have been completely specified. MODSIM supplies all information about the feed for every screen in the circuit. Karra has found that the capacity of a screen is reduced if there is a considerable quantity of near-size material in the feed. He defines an additional near-size capacity factor Gc and calculates it from

X. ~o51,

Gc =0.975(1 - 1--~/

(6)

where Xn is the percentage of near-size material in the feed. Thus the theoretical amount of undersize that can be transmitted by the screen is given by:

T h = A . B . C . D . E . F . G ¢ X screen area A screen will be well designed to handle its duty in the circuit if Th is approximately equal to the quantity of undersize in the feed. In practice, not all of the undersize is transmitted because of various physical factors that impair the efficiency of the screen. This effect is described by

258

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the screen partition function. Several standard functional forms are available to describe this effect, and Karra uses the function: Partition factor = 1 - exp [ ( - 0.693 (d/dso) 5.9 ]

(7 )

The parameter that will determine the screening efficiency is dso. Values of dso smaller than the screen mesh size will lead to low efficiencies, and values ofdso greater than the mesh size give high efficiencies. The actual dso achieved will depend primarily on the effective throughfall aperture of the wire mesh used on the screen. The throughfall aperture is in turn related to the actual mesh size, h, by:

h-r = ( h+ dw )cosO-dw

(8)

where 0 is the inclination angle of the screen, and dw is the wire diameter. Karra's analysis of experimental data from an extensive test program produced the following relationship for the prediction of dso: dso Gc hv - K 0"148

(9)

A further refinement must be added to Karra's model before it can be used as a general simulation model for operating screens. Karra makes no allowance for the percent open area of the screen cloth used. His formula for the calculation of capacity A is based on industrial light-medium woven wire mesh. For other screen cloths and surfaces, A must be adjusted in proportion to the open area. The percent open area for light-medium wire mesh is related to the mesh size h by: OA=21.5 logl0h+ 101.5

(with h in meters)

(10)

Thus capacity A must be adjusted to: A X actual % open area OA The model provides a simulation of the actual performance of the screen in the circuit. This performance can be compared with the design capacity of the screen and the screen performance evaluated. In particular, the actual operating efficiency can be calculated from: Simulated efficiency =

tonnage in underflow tonnage of undersize in feed

The effective utilization of the screen area can be calculated from: Area utilization factor = A U F tonnage of undersize in feed theoretical ability of the screen to pass undersize -

SIMULATIONOF CRUSHERCIRCUITPROCESSINGPROBLEMS

259

An A U F equal to unity indicates that the screen capacity is exactly balanced to the required duty. A U F ~< 1 indicates that the screen is underloaded, while A U F >I 1 indicates that the screen is overloaded.

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Fig. 3. The simulated and measured size distributions in the overflow streams from the top deck of a tertiary screen (stream 10) the lower deck of a tertiary screen (stream 17 ) and the overflow from the quaternary screens. TABLE IV Simulated ~rformance of crushers in the existing flowsheet Unit

Secondary crushers: West East

Design tonnage

Simulated tonnage

Installed net power

Measured net power

Simulated net power

(kW)

(kW)

(kW)

1000 1000

1069 935

171 158

126 136

130 167

Te~iarycrushers: Westl West2 Eastl East2

445 440 464 450

354 354 289 289

151

108 108 86 96

102 113 76 84

Quaternarycrushers: No.l No. 2

390 396

235 235

34 80

47 42

145

158 148

260

RP. KING

TABLE V Simulated performance of screens in the existing flowsheet Unit

Simulated tonnage (tons/h)

Simulated tonnage to underflow (tons/h)

Calculated dso (mm)

Simulated efficiency (%)

Area utilization factor

Tertiary screens: West top deck lower deck East top deck lower deck

534 317 468 293

317 180 293 179

34.9 12.4 35.6 12.8

82.7 94.0 84.0 95.8

1.60 1.14 1.40 1.04

Quaternary screens

293

214

15.8

86.8

0.94

A particular advantage of the Karra screen model is that no free parameters are required to be estimated from operating data. The adequacy of the model for the screens in the Rossing plant can be judged by comparing the measured and predicted size distributions in the screen overflow streams as shown in Fig. 3. With the exception of the overflow from the lower deck of the secondary screens, the agreement is remarkably good. A summary of the simulated behaviour of all of the units in the flowsheet is given in Tables IV and V. ASSESSMENT OF EXISTING FLOWSHEET OPERATION

The models used for the crushers and screens in the simulation required very little tuning to achieve a very good match between the simulator output and the observed behaviour of the plant. The models provide he necessary information that is required to diagnose the plant bottlenecks and to suggest modifications to enable the plant to meet its operating objective of 80% passing 7 mm in the final product. The simulation of the existing flowsheet predicted an 80% passing size of 10.4 mm against the measured value of 10.5 mm. The summarized simulator data in Tables IV and V identify the important operating characteristics immediately. The power drawn by each crusher was calculated by the simulator using the known impact work index of the ore (9kWh/ton) using formula: Power= TW, ( 1 IP~so - 1 IF~so)

where T= tonnage handled by the crusher, IV~the impact work index,/'so the 80% passing size in the product from the crusher and Fso the ~ passing size in the feed to the crusher. It is evident from Table IV that all the crushers in

SIMULATION OF CRUSHER CIRCUIT PROCESSING PROBLEMS

261

the plant are operating at or within their installed design capacity. The secondary crushers are working just within capacity, the tertiaries on the east side at about 65% of capacity. Table V shows that the tertiary screens are overloaded, particularly on the upper decks. The calculated area utilization factors are 1.6 and 1.4 on the top decks and this indicates that the screens are being required to transmit 60% more material than their design capacity. Screening efficiencies are relatively low. The lower decks are operating in a slightly overloaded condition, but in spite of this, the simulated efficiency is quite high. However, the measured size distribution of the lower deck overflow, as shown in Fig. 3, indicates some carry over of undersize material, and that would be consistent with the simulated overloaded conditions. The reason for the overloading of the front end of the circuit is not difficult to see. The plant feed on the coarse ore reclaim conveyor has a large quantity of fine material with aproximately 50% smaller than the closed-side setting of the secondary crushers. All of this material must be handled by the secondary crushers and the tertiary screens before leaving the plant in the tertiary screen underflow. All material that leaves in the tertiary screen underflow reduces the load on the tertiary crushers and the quaternary circuit. The calculated load on the quaternary circuit was found to be 1286 tons/h with a circulating load of 37%. Two strategies for the improvement of plant performance immediately suggest themselves. STRATEGIES FOR IMPROVEMENT

Strategy A. Increase the circulating load in the quaternary circuit and utilize the existing quaternary screening and crushing capacity more effectively to produce a fine product. Strategy B. Install secondary screens ahead of the secondary crushers to remove final product-size material before it enters the crusher circuit and utilize the released crushing and screening capacity to produce a finer product. Strategy A The circulating load in the quaternary circuit is increased if the mesh size of the quaternary screens is decreased. Even modest increases in the circulating load lead to an overload condition on the quaternary screens. This effect is shown by the simulator, and the pertinent data are summarized in Table VI in lines 1, 2 and 3, for simulations of the existing flowsheet with the quaternary screen mesh reduced from 20 m m to 17.5 m m and 15.2 ram. The latter condition increases the circulating load from 37% to 89%, and the quaternary screens and quaternary crushers become overloaded. It is necessary

262

R P KIN(I

"FABLE VI

Simulation of effect of finer crushing in the quaternary circuit Simulation Nr,

Quaternary screen aperture (mm)

Quaternary crusher CSS (ram)

Circulating load (%)

% - 7.41 mm in final product

1.1 2 3

20 17.5 15.2

8.17 and 8.6 8.17 and 8.6 8.17 and 8.6

37 56 89

63 68 74

4 5 6 7

20 17 15.2 15.2

6.5 6.5 6.5 6.5

28 40 48 45

66 72 75 74

Comments

Screens are overloaded Screens and crushers are overloaded Screens are overloaded No overloads Screens are overloaded No overloads. Quaternary screens increased from 6 to 8

*~Existing flowsheet base case.

to reduce the closed-side setting of the quaternary crushers ot keep the quaternary circuit in balance, and the effect of this can be seen in rows 4, 5 and 6 of Table VI. To relieve the overload on the quaternary screens, a further two screens can be installed in the quaternary circuit, and a product having 74% of material ~<7.4 mm is produced by the circuit.

Strategy B A modified circuit having additional secondary screening capacity installed is shown in the flowsheet in Fig. 4. These screens remove product-size material, allowing the secondary crusher to be set finer. The settings chosen for each unit in the modified plant are summarized in Table VII, and the simulator confirmed that no unit was overloaded in the circuit. MODSIM provides detailed operating information on the operation of the screens so that it is easy to select screens appropriate to the duty to be performed. In this case two pairs o f double-deck screens 6.1 m × 2.13 m are required, the apertures and other information are specified in Table VII. The apertures were chosen to balance the load on each deck so that the AUF is approximately equal to 1.0 for each. The addition of the secondary screens reduced the load on the quaternary circuit from 1286 to 1186 tons/h, so that a product having 75%~< 7.4 mm can be produced without additional screening capacity in the quaternary circuit.

SIMULATION

OF CRUSHER

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263

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T A B L E VII Settings o f operating p a r a m e t e r s in m o d i f i e d flowsheet Unit

Type

Secondary screens

Double-deck polyurethane

Secondary

7-ft standard Symons cone

crushers

crushers

Tertiary screens

D o u b l e - d e c k polyurethane

Tertiary crushers

7-fi short-head

Quaternary

6b'ingle-deck polyurethane

screens

Quaternary crushers

7-ft s h o r t - h e a d

Topdeck:

7 0 - m m square opening 5 0 - m m ribs 6.1 m × 2 . 1 3 m 18 ° inclination Lower deck: 1 6 - m m square opening 1 2 - m m ribs 6.1 m x 2 . 1 3 m 18 ° inclination

Closed-side setting: 35 m m

Topdeck:

1 5 - m m square opening 1 0 - m m ribs 6.1 m X 2 . 1 3 m 18 ° inclination Lower deck: 1 2 - m m square opening 8 - m m ribs 6.1 m X 2 . 1 3 m 18 o inclination Closed-side setting: 8 m m 15.2-mm square opening 1 0 . 3 - m m ribs 5.46 m × 2.0 m 18 ° inclination Closed-side setting: 6.5 m m

DISCUSSION

The main observation to be made from the simulations is that the product size distribution is determined primarily by the set-up of the quaternary crushing circuit. It is necessary to utilize both screening and crusher capacity in this section of the plant in an optimal fashion to achieve the best product. The simulations indicate that this can be done by appropriate choice of mesh size on the quaternary screens and settings in the quaternary crushers. The introduction of additional secondary screens has apparently very little potential for increasing the capacity of the plant. The reduction in load on the quaternary circuit from 1286 to 1186 tons/h cannot be regarded as a very attractive incentive for the introduction of four large double-deck screens. Improved

SIMULATION OF CRUSHER CIRCUIT PROCESSING PROBLEMS

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plant operation should be sought first by exploiting the capacity o f the quaternary circuit to the greatest possible extent before additional secondary screening capacity can be considered. Space does not permit a comprehensive presentation o f all the data obtained from M O D S I M , which is very voluminous. A complete set o f data from the study is available in King, 1987b and c. ACKNOWLEDGEMENTS The opportunity to participate in this important plant study was made possible by Rossing U r a n i u m and by Nordberg Manufacturing Company. The expert assistance and co-operation o f these companies is greatly appreciated. Continuing development of modelling and simulation techniques has been made possible by a grant from the Foundation for Research Development.

REFERENCES Karra, V.K., 1979. Development of a model for predicting the screening performance of a vibrating screen. CIM Bull., April 1979, pp. 167-171. Karra, V.K., 1982. A process performance model for cone crushers. Proc. 14th Int. Mining Congr., Toronto, III: 6.1-6.14. King, R.P., 1986. A User's Guide to MODSIM. University of the Witwatersrand, Department of Metallurgy and Materials Engineering, Johannesburg, Rept. GEN?l/86, 66 pp. King, R.P., 1987a. MODSIM: A Modular Method for the Design, Balancing and Simulation of Ore Dressing Plant Flowsheets. University of the Witwatersrand, Department of Metallurgy and Materials Engineering, Johannesburg, Rept. GEN/2/83, 77 pp. King, R.P., 1987b. The Fine Crushing Circuit of Rossing Uranium Ltd. Simulation of the Existing Flowsheet. University of the Witwatersrand, Department of Metallurgy and Materials Engineering, Johannesburg, Rept. GEN/8/87, 262 pp. King, R.P., 1987c. The Fine Crushing Circuit of Rossing Uranium Ltd. Simulation of Modified Flowsheets. University of the Witwatersrand, Department of Metallurgy and Materials Engineering, Johannesburg, Rept., GEN/13/87, 262 pp. Magerowski, A.J. and Karra, V.K., 1982. Computer-aided crushing circuit design. In: A.L. Mular and G.V. Jorgensen (Editors), Design and Installation of Comminution Circuits. Society of Mining Engineers, New York, N.Y., p. 288. O'Bryan, K., 1987. Crushing flowsheet simulation: increased productivity and improved flowsheet design. APCOM 87. Proc. 20th Int. Symp. Application of Computers and Mathematics in the Mineral Industries, Vol. 2, Johannesburg, SAIMM, pp. 167-178. Stange Wayne, 1989. Strategies for more flexible sequential-modular simulation. In: A. Weiss (Editor), Proc. 21st Int. Symp. Application of Computers and Operations Research in the Minerals Industry. Society of Mining Engineers, New York, N.Y., pp. 811-825.