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Automatic Control of Semi-Autogenous Grinding at Los Bronces JORGE JEREZ C. Instrumentation and Control Engineer HECTOR TORO CH. Senior Metallurgist GERHARD VON BORRIES H. Concentrator Operation Head

Compania Minera D,sputada de Las Condes S.A.. Los Bronces Mine. Chile. South America Pedro de Valdivia 291. Santiago. Chile.

Abstract. A brief description of the semi-autogenous grinding (SAG) facilities of Compania Minera Disputada de Las Condes is given. A data-logging and computer system was connected to the plant interfacing the existing analog control system in a supervisory set point control philosophy. The development of a control strategy to maintain maximum power of the SAG mill at steady operation and subjected to process restrictions is shown. The present control scheme is discussed in detail. A supervisory algorithm was designed based on correlations between variables. Associated with this, a direct level of control was developed based on classical control algorithms, process inter-active tuning has been included. Also, an algorithm to prevent overloading of the mill is discussed. Control scheme tests are presented in comparison to manual operator control under the same conditions. It is shown that the control strategy gives a more stable operation and a higher plant throughput.

KEYWORDS:

Computer control, semi autogenous grinding, process control, adaptive control. At least five circuits can be configurated very eaSily by manipulating some gates and valves.

INTRODUCTION

The grinding facilities of Compania Minera Disputada de Las Condes (CMD) are located at 3600 m.a.s.l. in the Andean Cordillera 60 km east of Santiago, Chile.

SA SAB SABC

A porphyry copp e r orebody is mined and milled at a rate of 12000 tons/day. A new semi-autogenous grinding plant was started up in 1981 and in 1983 an automatic computer control project was started t o control the grinding plant.

SACB SAC

Grinding Circuit

SAG mill only, in closed circuit (original plant). SAG mill with secondaries, without on-line crusher. SAG mill and ball mills with on-line crusher sending crushed product back to the mill. SAG mill with on-line crusher sending product to the secondary mills. SAG mill with on-line crusher, without secondary mills.

The plant was designed for 400tons/hour. AT present the plant capacity, including on-line crusher is 500tons/hour. Fig. I shows the grinding plant flowsheet.

Open pit trucks dump the ore into a primary lm x Zm jaw crusher. Primary crushed -8" ore is fed to a 20000 ton stockpile. Six variable speed be lt feeders reclaim the ore from the stockpile to a main feed belt which feeds the ore into the mill.

In November 1984 a new 30" x 46" primary gyratory crusher which delivers a -5.5 inch product was started up.

The main comminution equipment is a 28' ~ x 15' ~ semi-autogenous primary grinding mill with two 3500 HP drives. Mill discharge is classified by a trammel with 3/4" openings. The fine fraction is sent to a 26" diameter cyclone nest. Cyclone under flow goes back to the mill and overflow is final product.

Automatic Control System

The automatic control system at Los Bronces is configurated in a computer supervisory set point control mode as shown in Fig. 2. An existing a nalog control panel was interfaced with a microcomputer which generates the set points to the final controllers. In that way the analog back up is automatically present in case of computer failure.

Trommel oversize (pebbles) is sent back to the SAG mill. In September 1984 an on-line 5.5ft. Symons pebble crusher was installed. Crushed pe bbles are sent back to the mill. As an alternative, a belt system all ows the crushed pe bbles to be sent to the secondary mills.

Field Instru.entation and Analog Panel

From the start-up on, the plant was almost fully instrumented and at the beginning of the computer control project, the emphasis was placed to complete this instrume ntation. Briefly, the plant mass balance including all the streams can be

Two s econdary 9.5' ~ x 12' ~, 650HP ball mills, are normally fed with part of the SAG mill tronl,nel undersize. These mills operate in closed circuit with 20" diameter cyclones whose overflow is also fin a l product.

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Before the intensive data logging campaign, all the field instrumentation was rigorously checked independently from the maintenance routines. Several (20) sampling campaigns were carried out using sizing data and direct measurements of pulp density to check the cyclone feed mass flow rates. MSD-95 calibration was carried out sizing 1 to 2 ton samples taken from the feed belt. As an alternative, a pre- det e rmined size distribution of acrylic sheets were placed on the running empty belt comparing this distribution with the output of the instrument. Acceptable results were obtained. The actuators are the vari a ble speed feeders, pneuma tic water valves and continuous ly adjustable splitter gates in the on-line crushing system.

CO M PUTER

All the 4-20mA in and output signals are centralized in a Foxboro Spec 200 analog pane l which contains PI controllers, recorders, integrators and indi cators. Digital Configuration

Fig. 2.

Computer Supervisory Set Point Control Structure.

obtained continuously by means of weightometers, pulp and water magnetic flowmeters and nuclear pulp density meters. Other important instruments are a PSM-IOO particle size monitor at the cyclone overflow, a MSD-95 coarse particle size monitor on the main feed belt to the SAG mill, bearing back pressure transducers on both SAG mill main bearings to obtain an indirect measure of the holdup and power transducers on the primary and secondary mi lls. The manual operator control used from start up on allows maintenance of a feed rate setpoint. Power (J) and bearing back pressure (BBP) are monitored visually by the operator and action on the feedrate setpoint is taken.

The digital system was a locally configured 1 microcomputer based on a ISBC 8024 Inte1 CPU. The configuration includes AID converters for 60 inputs, isolated digital input-output channel s , a 256Kb bubble memory, 64Kb EPRO ~! memory and a high speed mathematical logic unit. A DEC VT 100 is used as operator interface. A Hewlett Packard 87 personal computer connected to the front end microcomputer, is used as a developme nt computer.

(1)

The computer was made by Fundacion Chile, ITT supported Research Centre.

Semi-autogenous Grinding at Los Brollces All lower level software such as data acquisition, date preprocessing, high frequency filtering, conversion to engineering units or calculation of some virtual variables, communication and self- diagnostics, are stored in EPROM. Minute averages of all the analog and digital inputs as well as alarms and equipment status are stored in the bubble memory using a FIFO structure.

FEED

Hain Process Disturbances Intrinsic ore hardness and feed size distribution are the main disturbances. Feed size distribution variations result from the following facts: An heterogeneous ore body with variable natural clast size and matrix distribution which results in different size distribution after blasting. Segregation in the coarse ore stockpile which on one hand has only a 6000 ton 11 ve c harge and on the other is fed fro~ one single point causing peripheral segregation of coarse particles. Due to the low live charge, any lengthy shutdown of the primary crusher forces the use of front loaders in the stockpile, which present batches of pure coarse or fine material to the mill. Start up and shutdown of the on-line crusher also changes significantly the amount of intermediate, say -1", particles fed to the mill. The first fact can be considered as a long term variation since the open pit operation delivers batches of 20 to 60Ktons of the same ore to the plant, usually without blending, meanwhile the latter are short term, say hour to hour disturbances. The effects of changes in size distribution caused by segregation or circuit configuration are shown in Figs. 3 and 4 respectively.

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Some difficulties arose in the communication between the computer and the analog controllers, to provide an effective analog backup and an easy and bumpless comput e r-analog control transfer and vice-versa. A special interface card, designed by CMD Instrumentation staff, was installed which transfers the setpoint changes in the form of up and down pulses to the existing controllers and maintains the last setpoint value in case of computer failure (Jerez, 1983).

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The development computer is used to retrieve the data stored in the bubble memory, to perform data analysis or to run control progra ms during the test phase. This computer can be used with online data or in stand-alone applications. Since the main effort was placed in developing a systetn which permits data handling and manipulation by metallurgists and control engineers, the operator-machine interface is quite limited. It allows changes in control strategy parameters, activation of the computer control and display of two pages of numerical figures of the main process variables.

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percentage. The soft ore presents a moderate sericitic alteration and a higher matrix percentage (Walker, 1984). Attempts to characterize these ore variations through the in pit drilling rate have been successful. Good correlations between the drilling rate and the plant unit grinding power consumption (kwh/ton) were obtained, Nevertheless it has not been possible to include a predictive para~eter in a feed-forward scheme into a control strategy. Finally, environmental factors like winter time, where the pit operation becomes irregular and considerable proportions of ice and snow are fed with the ore to the mill, are important disturbances. Feeder blockage due to frozen ore makes the feed to the plant unstable, but any control scheme, including manual control must be able to handle these situations. Relationships Between Operating Variables During a 6 month data logging campaign the following relationships between process variables have been investigated empirically. Mill Power (J) vs. bearing back pressure (BBP) At the beginning the typical power-load curve was found as shown in Fig. 5.

Greater than the size distribution is the influence of ore hardness. Throughput variations from 300tons/hour to 600tons/hour are usual. Two clearly defined ore types can be recognized in th orebody. Both are composed by two main

This curve was obtained plotting J vs. BBP during several overload situations and could be characterized by a well correlated mathematical expression.

lithological types (quartz monzonite and monzodiorite). The hard ore presents a weak sericitic alteration and a lower matrix

After the startup of the new primary crusher and the on-line pebble crusher, both contributing to a finer feed to the mill, a new behaviour arose.

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This is characterized by an almost constant power and a rising pressure curve at constant feedrate. Usually the bearing pressure rises during 3-4 hours and when the feed rate is turned off at this point, an increasing power and decreasing pressure shows that the mill was overloaded. This implies that the specific instant, when overload occurs cannot be detected under these circumstances. Fig. 6.

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Many visual inspections of mill charge showed that at the same load level the mill takes less power when the load is finer (or almost no coarse rocks are present). Hence there is a family of J vs. BBP curves each one depending on size distribution of the load. This leads to interpretation of this overload as shown in Fig.

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If feed or load size distribution becomes finer, then overloading can occur without the typical power down, BBP up scheme. It must be noted that ball charge is maintained usually at the lowest level, that is balls are added until full available power can be drawn. Three years experience showed that this ball level is about 9.5% balls by volume (Tarifeno and von Borries,

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Mill Power vs. Fresh Feed Rate (W) Steady state power was plotted versus throughput, parameterising the relationship between these two variables by the average kwh/ton (p) ratio of the period. This ratio reflects all the effects like intrinsic ore hardness, feed size distribution, ball charge, pulp density, etc. Fig. 8 shows a family of J vs. W curves parameterised by p. It can be observed that dispersion is low at higher p values and the averag e is also higher. This

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Power vs Feed Rate Parameterized by p(kwh/ton) •

reflects essentially that at manual control, on one hand operators take less care about power when ore is "softer" (high throughput), and on the other hand when ore is "softer" maximum available power often cannot be reached without overloading the mill. This last fact was frequently observed and it is attributed to the fact that "soft" ore is characterised by a high breakage rate of coarse particles, hence the mill load is finer and the overload des c ribed in the previous sections occurs. The maximum power which can be reached at each p, is shown in Fig. 8 as an envelope curve. Fresh Feed Rate vs. Feed Size Distribution Steady state data of throughput were plotted vs. one output channel of the MSU-95, again para~eterised by p. Influence was less than expected but it can be masked since p also receives a contriDution from the feed size distribution. Anyhow, the relationship shows that finer feed ore media leads to higher throughput, provided that there is no lack of grinding media (see Fig. 9). Other Variables Circuit alternatives cause drastic changes in the steady state and dynamic behaviour of the mill. At steady state throughput demands changes when another circuit is used which is quite obvious,

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but the mill also shows different response times when the circuit is perturbed (e.g. changes in feed characteristics). All the effects due to circuit changes have still to be studied which demands a long data logging period. Figures 10 and 11 show the contribution of the secondary ball mills and on-line crusher respectively on the base (SAB) circuit throughput. The previously presented relationships between variables and quantification of effects are the process support to the control strategy that will be described in the next section. These relationships were complemented with a great number of step response experiments, mainly with feed rate steps under different operating conditions.

Control Objectives In this particular case, control objectives were stated as follows: Maximize mill throughput by using maximum available power. Maintain the mill operation in the stable zone, thus preventing overload. Maintain the cyclone overflow particle size below a maximum. Se c ondary objectives as a specific percent solids in the mill (or optimum if there is any) can also be mentioned.

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At the development of the control scheme, the mill and the sump-cyclone system have been regarded as fairly decoupled systems and interactions (which surely exist) have been neglected. All the attention has been focused on the mill control problem, that is to achieve the first two objectives. Control Strategy The first control strategy which was tested in August 1984 consisted of a power controller (PlO) cascaded to a feed rate controller. The output of the power controller was added to an operator fixed feedrate set point. This strategy resulted in hunting cycles and could not be adjusted properly. Mill overload could neither be prevented nor be successfully carried back to stable state. From this pOint on, the development of a control scheme was divided into a direct level and a supervisory level.

ORE HARDNESS

Fig. 10.

Contribution to Throughput by Secondary Ball Mills.

Figure 12 shows the direct control level. It consist s basically of a PlO for the power control. This controller can receive its set point from the operator or from the supervisory routine. Need was detected, to make the proportional and integral gain factors error

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insufficient. Thus, logarithmic equations were chosen arbitrarily. The integral base gain showed to be ore dependent, that is with higher p (kwh/ton) higher integral factors were obtained. This has not been definitely included in the control scheme since more step response experiments have to be carried out under different ore hardness conditions. In parallel with this power controller, there is a BBP controller which takes the control over when it is activated by the supervisory routine. Since the general level of the BSP signal depends on factors like the temperature of the oil, and the settings of some valves in the oil circuit, no absolute BBP value can be established as a set point. Hence a strongly filtered signal is used as set point to this controller (Toro, von Borries and Jerez, 1984). The direct level generates the following set points: feed rate as explained before. flow to the SAG mill from water/ore fixed by the supervisory routine. flow to the sump according to a manual cyclone feed density set point.

In future water addition to the sump will be related to the overflow particle size indicated by the PSM 100. Supervisory Control Level This level performs basically the following tasks:

T HE SUPERVISORY ROUTINE

Direct Control Level Structure.

dependent including a dead band. Linear equations used at the beginning were shown to be

Fresh Water ratio Water fixed

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It avoids overload and checks if the mill is operating in an overload condition (Anderson, 1981), (Mular, 1~79), (McManus and Allen, 1977). It fixes the water/fresh feed ratio. It corrects the feed rate set point if feed size distribution changes. For the first task the routine checks periodically (each 5 minutes) the sign and value of the J and BBP first derivatives and compares these values with the patterns obtained from the J vs. BBP correlation explained before. In this way, the algorithm finds out if the mill is operating in an overload zone. If overload occurs two actions can be taken, which are chosen previously by the process engineer: Override by a BBP PlO which brings the mill back to the stable region. Decrease the power set point automatically step by step during several 5 minute periods until the mill is again in a stable operating condition. Once the mill is again in the stable region, control is returned to the power PlO taking the last power reading as the set point, then, step by step, the power is again raised to the nominal one. The atypical overload conditions are avoided by a second routine. BSP is filtered with a long term filter. The output of this filter is compared with the measurement and if the latter exceeds the former by a certain percentage, then the control is transferred to a SBP PID as explained in the direct control level. This PID will generate the ore feed set point until the BSP is again below the long term filter output. If this

Semi-autogenous Grinding at Los Brollces occurs, control is again transferred to the power control algorithm (Toro, von Borries and Jerez, 1984) •

Conclusions and Future Development

A control strategy which produces a marginal throughput increase and more plant stability has been developed successfully at Disputada, solving the power control problem of a semi-autogenous grinding mill.

Water/ore ratio is modified by a "hill climbing" routine (Mular, 1979) which computes and compares the p (kwh/ton) value of two consecutive periods of say 30 minutes and increases or decreases the water ratio according to the obtained effect. Large experimental campaigns showed that the mill has a better performance in terms of p with lower dilutions. It seems to be beneficial to evacuate the fine particles from the mill constantly using high water flowrate.

A combination of conventional control algorithms with override, adjustable tuning and interactive process tuning concepts have proven to be suitable for the SAG control problem. However, an extensive data logging and evaluation program had to be carried out to obtain the necessary process knowledge to support the control strategy. At present a minimum variance control algorithm based on a stochastic plant model for the power control is being tested. As a first step this algorithm has one input and one output. During 1985 the same concept with multivariable control will be applied (Box and Jennings, 1970), (Cuper, 1978) (Astrom and Wittenmark, 1973).

Finally, from the correlation between ore feedrate and the MSD-95 signal a bias is generated when the feed size distribution changes. This bias is added to the feedrate set point. Control Results During a trial period manual control was compared with automatic control Three factors were considered:

A large sampling campaign has been carried out between May 1984 and January 1985. Complete mass balances were obtained with size distribution of all the mass streams including mill load. The objective is to develop a phenomenological model to be included at the supe rvisory level into the c ontrol scheme. This work is being carried out by the J~~KC at Brisbane (Toro, 1984).

Stability: The control strategy maintains the circuit in a more stable condition, that is, feedrate variations are smoother than with manual control. Power deviation from the set point is lower with automatic control. Fig. 1 shows manual and control strategy reaction to an overload condition.

ACKNOWLEDGEMENTS

The authors wish to thank very especially the Operations Vice-President, Mr. Johann G. von Loebenstein and the Los Bronces Area Manager, Mr. Nelson Pizarro C., for having permitted the publication of the present work.

Throughput: The trial has shown consistent throughput increase with the automatic control strategy. Table 1 shows the comparative results of manual (operator) and automatic control. Knowledge: The data logging system and the careful e x perimental plant work have improved the knowledge of the process. Intuitive control by the operators has become a control based on a real knowledge of the process phenomena. Table 1:

REFERENCES Jerez, J.C., (1983). Internal Report SAG Process Control Phase I.

Hanual/ Automatic Control Comparison

Period

Feed Rate (MTPH)

Mill Power (HP)

Walker, C.A., (1984). Internal Report by CMD Geological Staff.

Kwh/Ton


550.3

6~39

9.40

Tarifeno, E.V. and von Borries, G.H., (1984). Analisis del Desgaste de Bolas en al Molina Semi-Autogeno de CMD. Armco-Chile IV Grinding Symposium.

Automati c

585.1

7152

9.12

Anderson, L., (1~81). Island Copper Process Control SAG Grinding Circuit.

Manual After Automatic

568.8

7035

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Mular, A.L., (197~). Automatic Control of Semi-Autogenous Grinding Circuits in North America. (Internal Report for Exxon Research Co.) • McManus, J. and Allan, P., (1977). Process Control in the Lornex Grinding Circuit. C.I.M. District 6 Meeting, Victoria, B.C. BOX, G.E.P. and Jennings, G.M., (197U). G.M. Time Series Analysis, Forecasting and ContrOl Holden Day.

Cuper, D.D., (1978). Control Suboptimo de Varianza Minima incluyendo Ajuste de Parametros para un Sistema de Fase No Minima. Univer s id ad de Chile. AstrOID, K.J. and Wittenmark, B., (1973). On Self Tuning Regulators. Automatica, Vol. 9., 18 5-199. Toro, H.C., (1~84). Internal Report by CMD Metallurgical Staff. Toro, H., von Borries, G. and Jerez, J., (1984). Control Strategy. Internal Report SAG Proc e ss Control Phase 11.