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Supervisory control at salvador flotation columns
Minerals Engineering, Vol. 12, No. 7, pp. 733-744, 1999
Pergamon 0892-6875(99) 00060-6
© 1999 Elsevier Science Ltd All rights reserved 0892-6875/99/$ - see front matter
SUPERVISORY CONTROL AT SALVADOR FLOTATION COLUMNS
L.G. BERGH ~, J.B. YIANATOS ~, C.A. ACUlqA ~, H. PI~REZ + and F. LOPEZ + § Chemical Engineering Department, Santa Maria University, Valparafso, Chile E-mail: lbergh @itata.disca.utfsm.cl t Salvador Concentrator, Codelco-Chile, Salvador, Chile (Received 19 November 1998; accepted 25 February 1999)
ABSTRACT The experience of developing, implementing and evaluating a hierarchical control strategy in a flotation column circuit at Salvador is discussed. The supervisory control system was installed in two columns in the copper cleaning circuit. Salvador concentrator produces over 200,000 tons per year of 30% copper concentrate. The column control is organised at two different levels: regulatory and supervisory control. The supervisor, SINCO-PRO, was developed to consider mainly three aspects: process data validation, metallurgical objectives control and operating problems detection. The system was installed in August 1997, and fine-tuning was completed in October 1997. Evaluation of the new implemented system was performed in November and December 1997. The main results were an average increment in the concentrate grade of 1.2% without loss in process recovery, and a decrement in the standard deviation of the concentrate grade from 0.9 to 0.7 %. The global operation of the cleaning circuit was stabilised, increasing the average feed grade from 8 to 10 % and dramatically reducing its standard deviation from 1.8 to 0.4 %. This stabilisation of the whole circuit allowed a tighter pH control with a significant reduction in chemical reagent consumption. The project was paid during the first two month of the evaluation period. © 1999 Elsevier Science Ltd. All rights reserved.
Keywords Froth flotation; sulphide ores; process control; expert systems
INTRODUCTION Flotation columns are now used worldwide as efficient cleaning stages in a large number of sulphide mineral concentrators. More degrees of freedom in their operating variables have led to large variations in metallurgical performance and therefore to much scope for improving their control. In this process, stable operation and consequent consistent metallurgical benefits can only be obtained if basic distributed control
Presented at Minerals Engineering '98, E d i n b u r g h , Scotland, S e p t e m b e r 1998
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systems are implemented. In Figure 1, a representation of typical flotation column instrumentation and control system is shown. In general, at least wash water and air flowrates and froth depth are measured on line, and tailings, air and wash water flowrates are manipulated. On line analysers, tailings and feed flowrates and some other measurements are often incorporated into the system when a supervisory control strategy is implemented on top of a distributed control system.
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Fig.1 Flotation column instrumentation and control system. The primary objectives, as indices of process productivity and product quality, are the recovery and the concentrate grade. However, their on-line estimation usually requires significant amount of work in maintenance and calibration of on-stream analysers, in order to maintain good accuracy and high availability. Therefore, it is common practice to control secondary objectives, such as the froth depth, the gas flowrate and the washwater flowrate [1]. This control is known as a stabilising strategy. Obtaining accurate measurements, non-linear dynamics and high interaction among variables are some of the main problems associated with stabilising control. These characteristics reduce the effectiveness of conventional PID control without a supervisor to co-ordinate the control loops. In practice, heuristic control approaches, based on different techniques, have been implemented on flotation columns. Expert systems applications have been reported in at least three plants, in Canada [2], in Japan [3] and in Chile [4]. Heuristic control based on logical rules (for example, fuzzy logic, and expert systems) is very efficient, preventing the process from moving away from some operating region. However, they are less efficient in handling the dynamic characteristics of the process near a local optimum operating point. Consequently, a manager or supervisor, integrating these two dissimilar control techniques in a hierarchical hybrid control strategy, can take advantage of choosing the right tool to adequately solve the kind of control problem occurring at any moment [1].
Supervisory control A hierarchical control is a supervisor acting above of the control system and its main goal is to increase the operating availability of the process under control, and to optimise the process performance according to some specific objective function relating metallurgical and economic benefits. To achieve this, the control manager should co-ordinate the actions of the distributed controllers, according to the evolution of the process variables and some specific logic rules or functional relationships between them. The integration of algorithmic and heuristic tools in a hybrid strategy is heavily based on experimental evidence obtained from plant operation. This integration requires the development of software to support the strategy in the
Supervisory control at Salvadorflotation columns
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working computational environment [ 1]. Contributions to improve the overall performance of the supervised system mainly come from on time detection of measurement and operating problems and from co-ordination and management of local control loops. In case of failure detection, the supervisor may select a second estimation of the variable using prediction models based on the kind of information still available [5]. A second estimation is expected to contribute with larger estimation errors than the first one. The benefit is in keeping the process under operation, even when a local optimum will become hard to achieve. An application example is the use of an alternative second estimation of concentrate grade, when this is not temporarily available on-line. A hierarchical control should have a routine to analyse the state of some process variable and other information in order to make a diagnosis of the operation. When an operating problem is detected, a sequence of exploring actions is initiated to identify the origin of the failure [5]. Some of the problems that can be detected are sparger failure, column flooding (pulp overflow), deep froth, froth under the lip (no concentrate) and lack of frother. Sometimes, a message is sent to the operator and/or a corrective automatic procedure is implemented. Most columns operate under distributed control of froth depth; gas flowrate and wash water flowrate. Concentrate grade and recovery can be effectively changed by modification of any of these three control loop setpoints. As mentioned before, a strong interaction between these control loops is expected. Therefore, an optimum combination of setpoint changes and an optimum time schedule to implement these control actions can be chosen. In fact, when operators are faced with this kind of problem each one prefers his own strategy, so different actions are taken in different operating shifts. Inconsistent operating rules and lack of control loop co-ordination is therefore usually presented. Some techniques used to co-ordinate distributed control systems are multivariable predictive control, based on multivariable models; expert systems, based on logic rules representing process knowledge (for example, [4]), and neuro-fuzzy systems integrating neural networks, mainly for classification problems, and fuzzy logic as a more refined and powerful representation of process knowledge (for example, [6]). SINCO-PRO means Intelligent Process Control System for Flotation Columns, and was developed and tested first in a pilot flotation column and then installed, tuned and evaluated in a large industrial flotation column. The first large-scale application was implemented in the copper cleaning circuit at E1 Teniente Concentrator of Codelco-Chile [4]. In this paper, a new application of SINCO-PRO to Salvador Concentrator is discussed.
SALVADOR CONCENTRATOR The copper ore, mainly composed of chalcopyrite, pyrite, magnetite and hematite, is quite disseminated in the rock. Lower concentrations of bornite, chalcocite and covellite are also found. The average grade is 0.7-0.75% copper and 0.022-0.026% molybdenum. The circuit tonnage is 34,000 TM/day, the ore typically being upgraded to obtain a concentrate of about 30% copper and 0.8% molybdenum. The flotation circuit was recently modified by substituting two cleaner stages of mechanical cells by a single cleaner stage consisting of two columns. Figure 2 shows the flotation circuit at Divisi6n Salvador. The flotation feed comes from the hydrocyclone overflow of the grinding circuit. The feed pulp, about 23% +212 lam and 47% - 7 5 pro, is distributed to four parallel rougher flotation banks, each one consisting of nine Wemco cells of 1,500 cubic feet. The rougher concentrate is reground and sent to a single cleaning stage or can be partially diverted to a thickener, which allows the control of the feed flowrate to the cleaning circuit. The rougher tailings go to general tails and then, through a 24 km pipe, to Los Amarillos tailings retreatment plant. The single cleaning stage consists of two columns in parallel and produces the copper/moly bulk concentrate. The columns are rectangular in cross-section, of 12 m: (2x6m), and 13 m height. Column tailings are distributed to two parallel scavenger banks, each one consisting of eight Dorr Oliver cells of 1,550 cubic feet. The scavenger concentrate is reground and sent to the cleaning columns. The scavenger tails are sent to general tails. The final collective concentrate, about 30% Cu and 0.8% Mo goes to a thickener and then to the molybdenum plant.
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CIRCUIT DIAGNOSIS
Cleaning circuit mass balance A n overall mass balance was developed on the cleaning circuit by sampling six streams. The selected stream points include the rougher concentrate, the final column concentrate, the column tails and the scavenger tail, allowing the calculation of the global cleaning mass balance as well as the mass balances for columns and scavengers. Four mass balances around the columns were also performed. During the overall sampling of the circuit, the thickener was isolated. When the circuit was operating at steady state, a composite of seven samples of about 1.5 Kg of solids was obtained at each point in a period of one hour. Samples were classified and analysed per class: +53 tam, - 5 3 +45 ~am and - 4 5 ~tm. A mass balance for each size class was performed by using data reconciliation techniques. In all cases, the m a x i m u m copper recovery was found at the m e d i u m size class - 5 3 +45 ~tm. The average copper recovery was 43.4% for columns, 96.1% for the scavenger circuit and 92.7% for the whole cleaning circuit.
Instrumentation and control system The feed flowrate to the cleaning stage is regulated using a variable speed pump, and the feed tank is provided with an overflow connected to a thickener that allows for extra surge capacity. The columns operate with three control loops to regulate the air, wash water and froth depth, as shown in Figure 1. Four in-line A M D E L analysers are also used to monitor the process. Thus, the feed and concentrate grades, of the columns as well as the rougher and scavenger tails, are continuously monitored. Another control
Supervisory control at Salvadorflotation columns
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alternative is the addition of reagents such as frother to increase column froth recovery, and addition of lime to regulate pH for iron control. A typical operation of the process under distributed control is shown in Figures 3 and 4 for a one-day period. Figure 3 shows that the total feed flowrate was in the range of 800 to 900 m3/h, and that the feed copper grade was between 7 and 9%, while the concentrate copper grade oscillated between 26 and 33%. This large variation in the concentrate grade can be attributed to different problems related to (i) disturbances coming into the process, (ii) inconsistent changes in the set points of the local control loops, as shown in Figure 4 and (iii) particularly in the operation and instrumentation limitations that will be discussed later in detail.
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Operation and instrumentation diagnosis During the first weeks a complete diagnosis of the installed instrumentation, piping layout, air spargers, water distribution system and others was made. The main results can be summarised as follows: (i)
The column tailings piping and valves presented problems related to low capacity of pulp discharge and valve cavitation. To temporarily avoid these problems, the feed flowrate was unevenly distributed in both columns and the froth depth in one column was limited to a narrow range of operation. Furthermore, the inappropriate performance of pinch valves lead to their excessive wear
Supervisory control at Salvadorflotation columns
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and frequent replacement. Fluid mechanic studies of the discharging circuit showed that piping layout and valve dimension have to be changed in order to operate both columns normally. This means that the feed flowrate should be evenly distributed in both columns, and the froth depth setpoint in both columns can be set for the whole normal operating range. (ii)
The variable feed flowrate management system was affected by three major problems leading to instabilities in the operation of both columns. The first was related to the difficulties found in stabilising the froth depth at a constant value, presenting continuous oscillations mainly caused by the limitations in the column discharge circuit as mentioned before. Second, the feed flowrate control loop measures the feed flowrate with a magnetic flowmeter and acts on the speed of the feeding pump. The measurement was very noisy, leading to excessive control actions and pulse flow, thus creating instability in the operation of both columns. A third kind of problem was the operation of the feed flowrate control loop independently of the pulp level in the feeding tank. Under certain conditions, especially when some ball mills were out and the feed flowrate to the rougher circuit decreased, the feeding tank level also decreased rapidly and the flowrate control system started to increase the pump speed. When the upstream operation was normalised, a large pulse of feed flowrate was produced leading to a large period of damping of the flowrate oscillations. In order to decrease these effects, a sonar type pulp level sensor was installed in the feeding tank. These measurements will be used to override the actual feed flowrate control when the pulp level is approaching a low limit. In the mean time, some arrangements were made in the management of the thickener flowrates to and from the feeding tank, to ensure that pulp level in the tank is always at a high level. The feed flowrate pump was also manually set to obtain the desired feed flowrate. This arrange permitted more stable operation.
(iii)
Due to the facilities in this circuit to adjust the feed flowrate over a certain range, once the problems, mentioned before, are solved, it was suggested that the administration of this resource should take into account several aspects. Among them, the accomplishment of the metallurgical benefits (concentrate grade in a band and recovery over a minimum specified value), the consumption of reagents (to handle pH and iron grade in the concentrate) and the availability of other operating resources such as air flowrate, wash water flowrate and froth depth.
(iv)
The wash water distribution on top of the column was working properly and no further design modifications were necessary. However, some problems associated with plugged pipelines and stacked valves were limiting the water flowrate under normal values. To achieve normal flowrates the flowrate control by pass has to be open, thus limiting its proper performance. Most of these problems were solved with a tight cleaning and maintenance programme.
(v)
The froth depth control loop estimated the froth-pulp interface position by measuring the pressure in an inverted tube. This measurement system permitted fast and off line maintenance as compared to other devices installed inside the column, which had more accuracy and repeatability of measurements, but their maintenance demanded the column to be out of service. Preliminary tests performed in order to contrast the accuracy and the repeatability of the measurements with a manually operated floater device showed that frequent recalibration of the device was needed to keep a reasonable estimation over time. This periodic calibration programme became a need when the kind of problems, previously discussed, that affected the performance of the froth depth control loop were solved.
(vi)
Normal air flowrate was achieved with the control bypass valve opened, due to problems in the air supply system. Different kinds of sparger systems existed and very basic maintenance and cleaning programmes were performed. It was recommended that a study be undertaken to increase the air pressure supplied in order that it work with the air flowrate control loop efficiently. It was also suggested that the existing sparger maintenance programme be expanded in order to improve on-time detection of sparger malfunction and to statistically analyse the differences between spargers over time.
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(vii)
The formation of large air bags beside the internal launders in each column was observed. The large air bubbles produced undesirable mixing pattern in the froth, decreasing the recovery efficiency in the froth. This phenomenon was tttributed to the plane design of the launder bottom, so it was modified to a triangular form.
(viii)
Between the columns, a discontinuous overflow of concentrate in the discharging channel produced a very dirty area around the instrumentation associated with the measurement and control of the wash water and air flowrates. This situation increased the difficulties in checking and maintaining these devices. A modification of the original design was made.
(ix)
To improve the amount and quality of the information the following instrumentation needs were detected. (a) Pressure transmitters in each air manifold to check possible on-line malfunction of the air distribution system into the column. (b) An on-stream analyser to measure the tailings grade in order to have a better estimation of the column recovery and the performance of the scavenger circuit. (c) A local manually operated floater system in each column to contrast the on-line measurement of the inverted tube pressure device and therefore to improve the estimation of the froth depth. (d) A pulp level transmitter in the feeding tank to improve the feed flowrate control strategy.
SINCO-PRO IMPLEMENTATION The supervisor SINCO-PRO was developed in Control Language in the Application Module of a TDC-3000 Honeywell system. A scheme of the computational platform used is shown in Figure 5. All process data is collected and displayed on screen in a TDC-3000 system and sent through a PCNM software interlace system to a PC network. The data in the PC is compacted and stored in historical files for further analysis. The operator interface is located at specially designed interactive displays on screen in the TDC-3000 system. Filtered data, calculated performance indices, setpoint values and messages to operators are returned to the system to implement the control actions and to display consistent process variables values, performance indices and messages.
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Supervisory control at Salvador flotation columns SINCO-PRO
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strategy
The SINCO-PRO strategy contributes to better control by validating all data used in control decisions, by opportunely detecting measurement and operating problems and by consistently co-ordinating control actions by managing the local control loop setpoints. The main objective function is defined as follows. The concentrate grade should be inside a narrow band, the upper and lower limits of which are parameters that may be changed by the operator. The column recovery should be always over a minimum value. When the recovery cannot be estimated from measured data, it is replaced by an equivalent criterion using the scavenger tailings grade. The feed flowrate should be the maximum that satisfies the previous objectives. The constraints that should be explicitly taken into account are: the froth depth, air and wash water flowrates must be always inside a band (upper and lower limits are parameters) and as far as possible to their limits (availability principle). The pulp pH is mainly used to adjust the iron grade in the concentrate. The frother dosage should be at a minimum, unless the operational variables are saturated and no decrement in the feed flowrate is desired. When the recovery decreases to a certain limit, the concentrate grade strategy is overruled and a procedure to increase the process recovery is initiated. Similarly, the concentrate grade strategy may be overruled if the process is close to meeting an operation constraint. For example, if a plugging condition is detected, a procedure to avoid this problem is executed with high priority. To implement this strategy the following modules were developed: • Checking grades availability and consistence, mass balances and recovery estimation • Checking availability of variables under local control loops • Obtaining process data and system parameters • Expert routine to make decisions based on control strategy • Registration of events and compressed process data on disk • Reporting states and actions to operator interface • Implementation of setpoint changes in local controllers After mass balance calculations and grade estimations, the expert system evaluates the performance criteria, producing two possible actions: either increase the concentrate grade or increase the cleaning process recovery. The next step is to decide which one of the available resources is to be used to achieve the objective. In Salvador, five resources are available: air flowrate, froth depth, wash water flowrate, feed flowrate and frother dosage. Each variable may belong to one of three categories: low, normal or high. A resource can be available with high priority if the current setpoint value of this variable is under (or above) its normal region if the direction of the corrective action is to increase (or decrease) its setpoint value. All variables satisfying this requirement may be used in a predetermined order. On the other hand, a resource is not available if its setpoint value is saturated at the maximum (or minimum) limit of the high (or low) band, when the direction of the corrective action is to increase (or decrease) its setpoint value. Some other less extreme cases are when the setpoint value is in the normal or high (or low) band. The idea is that all resources are commonly operated as close as possible to their normal bands. Usually feed flowrate is set to the maximum normal value and can be decreased only if no other resources in the list are available. Frother dosage is set to a minimum normal value and will not be incremented unless other resources are not available and the objective conditions are not met. The use of the other resources is more complex and the selection routine is based on the fact that each resource can belong to either three segments: a low, a normal or a high band. The routine will pick up the resource by privileging their migration to their normal band, that is using the availability principle. For example, the procedure to increase the concentrate grade is illustrated in Figure 6.
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Supervisory control at Salvador flotation columns
743
approaches, such as the use of fuzzy logic, to the decision problem have been studied by simulation [6] and more recently by pilot plant experimentation. Even though preliminary results have been shown to improve the overall performance of the process, and to adequately handle the specific problem of oscillations around band limits, it was decided to evaluate first the expert control strategy and then include, if necessary, other techniques. The expert control strategy supervises the system every ten minutes. In this particular case the control time interval is not restricted by the on-line analysers, which provide continuous information, but it is for the response time of the process. If the control interval is changed then the parameters defining the magnitude of the maximum changes in each setpoint must also be modified accordingly.
EVALUATION A circuit performance comparison was made for a period of two months of operation under supervisory control (November and December 1997) and almost a year before that (August and September 1996) under DCS control. The main results are shown in Figure 7. In this Figure, one can observe the feed grade to the flotation circuit, the feed grade to the columns and the concentrate grade. The feed grade to the plant remained almost constant, between 0.7% and 0.8%, during both periods of evaluation. An important change can be seen in the copper feed grade to the columns. As a result of a stabilisation of the whole cleaning circuit by the supervisor the feed grade was increased on average from 8.6% to 10.1% and the standard deviation was reduced from 1.3% to 0.4%. This stabilisation decreased the circulating load on the circuit and helped to significantly decrease the consumption of chemical reagents used to control pH. The concentrate copper grade increased by an average of 1.2% without loss in process recovery. The circuit stability was improved, reducing the standard deviation of the concentrate grade from 0.9 to 0.7%. 1
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CONCLUSIONS The development and implementation of the new control strategy leads to the following general conclusions: The cleaning circuit controllability is usually constrained, due to of instrumentation malfunctions, mainly due to inappropriate calibration and maintenance methodologies. Thus a complete diagnostic programme should be carried out before implementing any control strategy. Once the major problems detected are solved, there is great opportunity for appropriate use of the information available. Distributed control systems are not sufficient to achieve tight metallurgical objectives, a supervisor with different attributes being needed. Supervisory control systems should be adaptable to different computation platforms, and should consider at least modules for: validation and reconciliation of process data, detection of operation and instrumentation problems and co-ordination of local control loops under an overall strategy. Other important aspects in the success of a supervisory control system are the operator involvement in the project and the ability of the system to be running even when some information is not temporarily available. In our experience, the joint training programme for control room and field operators, instrumental and maintenance personnel, on all the aspects related to the project, has been extremely helpful in co-ordinating all the efforts in relaxing different constraints on the process controllability. In particular the economical benefits of the project exceeded the company expectations, and the payoff period of the project was reduced to two months.
ACKNOWLEDGEMENTS
The financial support of Conicyt (Fondef D96T- 1022) and the Santa Maria University (Project 972723), and the invaluable contribution of Salvador Concentrator personnel at different stages of this work and its permission to present these results are greatly acknowledged.
REFERENCES l,
2.
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4.
5.
6.
Bergh, L.G. & Yianatos, J.B., Control Alternatives for Flotation Columns, Minerals Engineering, 6, N ° 6, 631-642 (1993). Kosics, G.A., Dobby, G.S. & Young, P.D., ColumnEx: a Powerful and affordable Control System for Column Flotation, Proceedings International Conference on Column Flotation, Sudbury, Canada, 359-373 (1991). Hirajima, T., Takamori, T., Tsunekawa, M., Masubara, T., Oshima, K., Imai, T., Sawaki, K. & Kubo, S., The Application of Fuzzy Logic Control Concentrate Grade in Column Flotation at Toyaha Mines, Proceedings International Conference on Column Flotation, Sudbury, Canada, 375-389 (1991). Bergh, L.G., Yianatos, J-B., Acufia, C.P. & Cartes, F., SINCO-COL Application to Flotation Columns in El Teniente Concentrator, Proceedings International Conference Column "96, Montreal, Canada, August, 583-591 (1996). Bergh, L.G., Yianatos, J.B. & Acufia, C.P., Hierarchical Control Strategy for Flotation Columns, Minerals Engineering, 8, N°12, 1583-1591 (1995). Bergh, L.G., Yianatos, J.B. & Leiva, C.A., Fuzzy Supervisory Control for Flotation Columns, Minerals Engineering, 11, N°8, (1998).
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 in M i n e r a l s Engineering is i n v i t e d , p r e f e r a b l y b y em a i l to b w i l l s @ m i n - e n g . c o m , or b y F a x to + 4 4 - ( 0 ) 1 3 2 6 - 3 1 8 3 5 2
Pergamon 0892-6875(99) 00060-6
© 1999 Elsevier Science Ltd All rights reserved 0892-6875/99/$ - see front matter
SUPERVISORY CONTROL AT SALVADOR FLOTATION COLUMNS
L.G. BERGH ~, J.B. YIANATOS ~, C.A. ACUlqA ~, H. PI~REZ + and F. LOPEZ + § Chemical Engineering Department, Santa Maria University, Valparafso, Chile E-mail: lbergh @itata.disca.utfsm.cl t Salvador Concentrator, Codelco-Chile, Salvador, Chile (Received 19 November 1998; accepted 25 February 1999)
ABSTRACT The experience of developing, implementing and evaluating a hierarchical control strategy in a flotation column circuit at Salvador is discussed. The supervisory control system was installed in two columns in the copper cleaning circuit. Salvador concentrator produces over 200,000 tons per year of 30% copper concentrate. The column control is organised at two different levels: regulatory and supervisory control. The supervisor, SINCO-PRO, was developed to consider mainly three aspects: process data validation, metallurgical objectives control and operating problems detection. The system was installed in August 1997, and fine-tuning was completed in October 1997. Evaluation of the new implemented system was performed in November and December 1997. The main results were an average increment in the concentrate grade of 1.2% without loss in process recovery, and a decrement in the standard deviation of the concentrate grade from 0.9 to 0.7 %. The global operation of the cleaning circuit was stabilised, increasing the average feed grade from 8 to 10 % and dramatically reducing its standard deviation from 1.8 to 0.4 %. This stabilisation of the whole circuit allowed a tighter pH control with a significant reduction in chemical reagent consumption. The project was paid during the first two month of the evaluation period. © 1999 Elsevier Science Ltd. All rights reserved.
Keywords Froth flotation; sulphide ores; process control; expert systems
INTRODUCTION Flotation columns are now used worldwide as efficient cleaning stages in a large number of sulphide mineral concentrators. More degrees of freedom in their operating variables have led to large variations in metallurgical performance and therefore to much scope for improving their control. In this process, stable operation and consequent consistent metallurgical benefits can only be obtained if basic distributed control
Presented at Minerals Engineering '98, E d i n b u r g h , Scotland, S e p t e m b e r 1998
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systems are implemented. In Figure 1, a representation of typical flotation column instrumentation and control system is shown. In general, at least wash water and air flowrates and froth depth are measured on line, and tailings, air and wash water flowrates are manipulated. On line analysers, tailings and feed flowrates and some other measurements are often incorporated into the system when a supervisory control strategy is implemented on top of a distributed control system.
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Fig.1 Flotation column instrumentation and control system. The primary objectives, as indices of process productivity and product quality, are the recovery and the concentrate grade. However, their on-line estimation usually requires significant amount of work in maintenance and calibration of on-stream analysers, in order to maintain good accuracy and high availability. Therefore, it is common practice to control secondary objectives, such as the froth depth, the gas flowrate and the washwater flowrate [1]. This control is known as a stabilising strategy. Obtaining accurate measurements, non-linear dynamics and high interaction among variables are some of the main problems associated with stabilising control. These characteristics reduce the effectiveness of conventional PID control without a supervisor to co-ordinate the control loops. In practice, heuristic control approaches, based on different techniques, have been implemented on flotation columns. Expert systems applications have been reported in at least three plants, in Canada [2], in Japan [3] and in Chile [4]. Heuristic control based on logical rules (for example, fuzzy logic, and expert systems) is very efficient, preventing the process from moving away from some operating region. However, they are less efficient in handling the dynamic characteristics of the process near a local optimum operating point. Consequently, a manager or supervisor, integrating these two dissimilar control techniques in a hierarchical hybrid control strategy, can take advantage of choosing the right tool to adequately solve the kind of control problem occurring at any moment [1].
Supervisory control A hierarchical control is a supervisor acting above of the control system and its main goal is to increase the operating availability of the process under control, and to optimise the process performance according to some specific objective function relating metallurgical and economic benefits. To achieve this, the control manager should co-ordinate the actions of the distributed controllers, according to the evolution of the process variables and some specific logic rules or functional relationships between them. The integration of algorithmic and heuristic tools in a hybrid strategy is heavily based on experimental evidence obtained from plant operation. This integration requires the development of software to support the strategy in the
Supervisory control at Salvadorflotation columns
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working computational environment [ 1]. Contributions to improve the overall performance of the supervised system mainly come from on time detection of measurement and operating problems and from co-ordination and management of local control loops. In case of failure detection, the supervisor may select a second estimation of the variable using prediction models based on the kind of information still available [5]. A second estimation is expected to contribute with larger estimation errors than the first one. The benefit is in keeping the process under operation, even when a local optimum will become hard to achieve. An application example is the use of an alternative second estimation of concentrate grade, when this is not temporarily available on-line. A hierarchical control should have a routine to analyse the state of some process variable and other information in order to make a diagnosis of the operation. When an operating problem is detected, a sequence of exploring actions is initiated to identify the origin of the failure [5]. Some of the problems that can be detected are sparger failure, column flooding (pulp overflow), deep froth, froth under the lip (no concentrate) and lack of frother. Sometimes, a message is sent to the operator and/or a corrective automatic procedure is implemented. Most columns operate under distributed control of froth depth; gas flowrate and wash water flowrate. Concentrate grade and recovery can be effectively changed by modification of any of these three control loop setpoints. As mentioned before, a strong interaction between these control loops is expected. Therefore, an optimum combination of setpoint changes and an optimum time schedule to implement these control actions can be chosen. In fact, when operators are faced with this kind of problem each one prefers his own strategy, so different actions are taken in different operating shifts. Inconsistent operating rules and lack of control loop co-ordination is therefore usually presented. Some techniques used to co-ordinate distributed control systems are multivariable predictive control, based on multivariable models; expert systems, based on logic rules representing process knowledge (for example, [4]), and neuro-fuzzy systems integrating neural networks, mainly for classification problems, and fuzzy logic as a more refined and powerful representation of process knowledge (for example, [6]). SINCO-PRO means Intelligent Process Control System for Flotation Columns, and was developed and tested first in a pilot flotation column and then installed, tuned and evaluated in a large industrial flotation column. The first large-scale application was implemented in the copper cleaning circuit at E1 Teniente Concentrator of Codelco-Chile [4]. In this paper, a new application of SINCO-PRO to Salvador Concentrator is discussed.
SALVADOR CONCENTRATOR The copper ore, mainly composed of chalcopyrite, pyrite, magnetite and hematite, is quite disseminated in the rock. Lower concentrations of bornite, chalcocite and covellite are also found. The average grade is 0.7-0.75% copper and 0.022-0.026% molybdenum. The circuit tonnage is 34,000 TM/day, the ore typically being upgraded to obtain a concentrate of about 30% copper and 0.8% molybdenum. The flotation circuit was recently modified by substituting two cleaner stages of mechanical cells by a single cleaner stage consisting of two columns. Figure 2 shows the flotation circuit at Divisi6n Salvador. The flotation feed comes from the hydrocyclone overflow of the grinding circuit. The feed pulp, about 23% +212 lam and 47% - 7 5 pro, is distributed to four parallel rougher flotation banks, each one consisting of nine Wemco cells of 1,500 cubic feet. The rougher concentrate is reground and sent to a single cleaning stage or can be partially diverted to a thickener, which allows the control of the feed flowrate to the cleaning circuit. The rougher tailings go to general tails and then, through a 24 km pipe, to Los Amarillos tailings retreatment plant. The single cleaning stage consists of two columns in parallel and produces the copper/moly bulk concentrate. The columns are rectangular in cross-section, of 12 m: (2x6m), and 13 m height. Column tailings are distributed to two parallel scavenger banks, each one consisting of eight Dorr Oliver cells of 1,550 cubic feet. The scavenger concentrate is reground and sent to the cleaning columns. The scavenger tails are sent to general tails. The final collective concentrate, about 30% Cu and 0.8% Mo goes to a thickener and then to the molybdenum plant.
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CIRCUIT DIAGNOSIS
Cleaning circuit mass balance A n overall mass balance was developed on the cleaning circuit by sampling six streams. The selected stream points include the rougher concentrate, the final column concentrate, the column tails and the scavenger tail, allowing the calculation of the global cleaning mass balance as well as the mass balances for columns and scavengers. Four mass balances around the columns were also performed. During the overall sampling of the circuit, the thickener was isolated. When the circuit was operating at steady state, a composite of seven samples of about 1.5 Kg of solids was obtained at each point in a period of one hour. Samples were classified and analysed per class: +53 tam, - 5 3 +45 ~am and - 4 5 ~tm. A mass balance for each size class was performed by using data reconciliation techniques. In all cases, the m a x i m u m copper recovery was found at the m e d i u m size class - 5 3 +45 ~tm. The average copper recovery was 43.4% for columns, 96.1% for the scavenger circuit and 92.7% for the whole cleaning circuit.
Instrumentation and control system The feed flowrate to the cleaning stage is regulated using a variable speed pump, and the feed tank is provided with an overflow connected to a thickener that allows for extra surge capacity. The columns operate with three control loops to regulate the air, wash water and froth depth, as shown in Figure 1. Four in-line A M D E L analysers are also used to monitor the process. Thus, the feed and concentrate grades, of the columns as well as the rougher and scavenger tails, are continuously monitored. Another control
Supervisory control at Salvadorflotation columns
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alternative is the addition of reagents such as frother to increase column froth recovery, and addition of lime to regulate pH for iron control. A typical operation of the process under distributed control is shown in Figures 3 and 4 for a one-day period. Figure 3 shows that the total feed flowrate was in the range of 800 to 900 m3/h, and that the feed copper grade was between 7 and 9%, while the concentrate copper grade oscillated between 26 and 33%. This large variation in the concentrate grade can be attributed to different problems related to (i) disturbances coming into the process, (ii) inconsistent changes in the set points of the local control loops, as shown in Figure 4 and (iii) particularly in the operation and instrumentation limitations that will be discussed later in detail.
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Operation and instrumentation diagnosis During the first weeks a complete diagnosis of the installed instrumentation, piping layout, air spargers, water distribution system and others was made. The main results can be summarised as follows: (i)
The column tailings piping and valves presented problems related to low capacity of pulp discharge and valve cavitation. To temporarily avoid these problems, the feed flowrate was unevenly distributed in both columns and the froth depth in one column was limited to a narrow range of operation. Furthermore, the inappropriate performance of pinch valves lead to their excessive wear
Supervisory control at Salvadorflotation columns
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and frequent replacement. Fluid mechanic studies of the discharging circuit showed that piping layout and valve dimension have to be changed in order to operate both columns normally. This means that the feed flowrate should be evenly distributed in both columns, and the froth depth setpoint in both columns can be set for the whole normal operating range. (ii)
The variable feed flowrate management system was affected by three major problems leading to instabilities in the operation of both columns. The first was related to the difficulties found in stabilising the froth depth at a constant value, presenting continuous oscillations mainly caused by the limitations in the column discharge circuit as mentioned before. Second, the feed flowrate control loop measures the feed flowrate with a magnetic flowmeter and acts on the speed of the feeding pump. The measurement was very noisy, leading to excessive control actions and pulse flow, thus creating instability in the operation of both columns. A third kind of problem was the operation of the feed flowrate control loop independently of the pulp level in the feeding tank. Under certain conditions, especially when some ball mills were out and the feed flowrate to the rougher circuit decreased, the feeding tank level also decreased rapidly and the flowrate control system started to increase the pump speed. When the upstream operation was normalised, a large pulse of feed flowrate was produced leading to a large period of damping of the flowrate oscillations. In order to decrease these effects, a sonar type pulp level sensor was installed in the feeding tank. These measurements will be used to override the actual feed flowrate control when the pulp level is approaching a low limit. In the mean time, some arrangements were made in the management of the thickener flowrates to and from the feeding tank, to ensure that pulp level in the tank is always at a high level. The feed flowrate pump was also manually set to obtain the desired feed flowrate. This arrange permitted more stable operation.
(iii)
Due to the facilities in this circuit to adjust the feed flowrate over a certain range, once the problems, mentioned before, are solved, it was suggested that the administration of this resource should take into account several aspects. Among them, the accomplishment of the metallurgical benefits (concentrate grade in a band and recovery over a minimum specified value), the consumption of reagents (to handle pH and iron grade in the concentrate) and the availability of other operating resources such as air flowrate, wash water flowrate and froth depth.
(iv)
The wash water distribution on top of the column was working properly and no further design modifications were necessary. However, some problems associated with plugged pipelines and stacked valves were limiting the water flowrate under normal values. To achieve normal flowrates the flowrate control by pass has to be open, thus limiting its proper performance. Most of these problems were solved with a tight cleaning and maintenance programme.
(v)
The froth depth control loop estimated the froth-pulp interface position by measuring the pressure in an inverted tube. This measurement system permitted fast and off line maintenance as compared to other devices installed inside the column, which had more accuracy and repeatability of measurements, but their maintenance demanded the column to be out of service. Preliminary tests performed in order to contrast the accuracy and the repeatability of the measurements with a manually operated floater device showed that frequent recalibration of the device was needed to keep a reasonable estimation over time. This periodic calibration programme became a need when the kind of problems, previously discussed, that affected the performance of the froth depth control loop were solved.
(vi)
Normal air flowrate was achieved with the control bypass valve opened, due to problems in the air supply system. Different kinds of sparger systems existed and very basic maintenance and cleaning programmes were performed. It was recommended that a study be undertaken to increase the air pressure supplied in order that it work with the air flowrate control loop efficiently. It was also suggested that the existing sparger maintenance programme be expanded in order to improve on-time detection of sparger malfunction and to statistically analyse the differences between spargers over time.
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(vii)
The formation of large air bags beside the internal launders in each column was observed. The large air bubbles produced undesirable mixing pattern in the froth, decreasing the recovery efficiency in the froth. This phenomenon was tttributed to the plane design of the launder bottom, so it was modified to a triangular form.
(viii)
Between the columns, a discontinuous overflow of concentrate in the discharging channel produced a very dirty area around the instrumentation associated with the measurement and control of the wash water and air flowrates. This situation increased the difficulties in checking and maintaining these devices. A modification of the original design was made.
(ix)
To improve the amount and quality of the information the following instrumentation needs were detected. (a) Pressure transmitters in each air manifold to check possible on-line malfunction of the air distribution system into the column. (b) An on-stream analyser to measure the tailings grade in order to have a better estimation of the column recovery and the performance of the scavenger circuit. (c) A local manually operated floater system in each column to contrast the on-line measurement of the inverted tube pressure device and therefore to improve the estimation of the froth depth. (d) A pulp level transmitter in the feeding tank to improve the feed flowrate control strategy.
SINCO-PRO IMPLEMENTATION The supervisor SINCO-PRO was developed in Control Language in the Application Module of a TDC-3000 Honeywell system. A scheme of the computational platform used is shown in Figure 5. All process data is collected and displayed on screen in a TDC-3000 system and sent through a PCNM software interlace system to a PC network. The data in the PC is compacted and stored in historical files for further analysis. The operator interface is located at specially designed interactive displays on screen in the TDC-3000 system. Filtered data, calculated performance indices, setpoint values and messages to operators are returned to the system to implement the control actions and to display consistent process variables values, performance indices and messages.
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Supervisory control at Salvador flotation columns SINCO-PRO
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strategy
The SINCO-PRO strategy contributes to better control by validating all data used in control decisions, by opportunely detecting measurement and operating problems and by consistently co-ordinating control actions by managing the local control loop setpoints. The main objective function is defined as follows. The concentrate grade should be inside a narrow band, the upper and lower limits of which are parameters that may be changed by the operator. The column recovery should be always over a minimum value. When the recovery cannot be estimated from measured data, it is replaced by an equivalent criterion using the scavenger tailings grade. The feed flowrate should be the maximum that satisfies the previous objectives. The constraints that should be explicitly taken into account are: the froth depth, air and wash water flowrates must be always inside a band (upper and lower limits are parameters) and as far as possible to their limits (availability principle). The pulp pH is mainly used to adjust the iron grade in the concentrate. The frother dosage should be at a minimum, unless the operational variables are saturated and no decrement in the feed flowrate is desired. When the recovery decreases to a certain limit, the concentrate grade strategy is overruled and a procedure to increase the process recovery is initiated. Similarly, the concentrate grade strategy may be overruled if the process is close to meeting an operation constraint. For example, if a plugging condition is detected, a procedure to avoid this problem is executed with high priority. To implement this strategy the following modules were developed: • Checking grades availability and consistence, mass balances and recovery estimation • Checking availability of variables under local control loops • Obtaining process data and system parameters • Expert routine to make decisions based on control strategy • Registration of events and compressed process data on disk • Reporting states and actions to operator interface • Implementation of setpoint changes in local controllers After mass balance calculations and grade estimations, the expert system evaluates the performance criteria, producing two possible actions: either increase the concentrate grade or increase the cleaning process recovery. The next step is to decide which one of the available resources is to be used to achieve the objective. In Salvador, five resources are available: air flowrate, froth depth, wash water flowrate, feed flowrate and frother dosage. Each variable may belong to one of three categories: low, normal or high. A resource can be available with high priority if the current setpoint value of this variable is under (or above) its normal region if the direction of the corrective action is to increase (or decrease) its setpoint value. All variables satisfying this requirement may be used in a predetermined order. On the other hand, a resource is not available if its setpoint value is saturated at the maximum (or minimum) limit of the high (or low) band, when the direction of the corrective action is to increase (or decrease) its setpoint value. Some other less extreme cases are when the setpoint value is in the normal or high (or low) band. The idea is that all resources are commonly operated as close as possible to their normal bands. Usually feed flowrate is set to the maximum normal value and can be decreased only if no other resources in the list are available. Frother dosage is set to a minimum normal value and will not be incremented unless other resources are not available and the objective conditions are not met. The use of the other resources is more complex and the selection routine is based on the fact that each resource can belong to either three segments: a low, a normal or a high band. The routine will pick up the resource by privileging their migration to their normal band, that is using the availability principle. For example, the procedure to increase the concentrate grade is illustrated in Figure 6.
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Supervisory control at Salvador flotation columns
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approaches, such as the use of fuzzy logic, to the decision problem have been studied by simulation [6] and more recently by pilot plant experimentation. Even though preliminary results have been shown to improve the overall performance of the process, and to adequately handle the specific problem of oscillations around band limits, it was decided to evaluate first the expert control strategy and then include, if necessary, other techniques. The expert control strategy supervises the system every ten minutes. In this particular case the control time interval is not restricted by the on-line analysers, which provide continuous information, but it is for the response time of the process. If the control interval is changed then the parameters defining the magnitude of the maximum changes in each setpoint must also be modified accordingly.
EVALUATION A circuit performance comparison was made for a period of two months of operation under supervisory control (November and December 1997) and almost a year before that (August and September 1996) under DCS control. The main results are shown in Figure 7. In this Figure, one can observe the feed grade to the flotation circuit, the feed grade to the columns and the concentrate grade. The feed grade to the plant remained almost constant, between 0.7% and 0.8%, during both periods of evaluation. An important change can be seen in the copper feed grade to the columns. As a result of a stabilisation of the whole cleaning circuit by the supervisor the feed grade was increased on average from 8.6% to 10.1% and the standard deviation was reduced from 1.3% to 0.4%. This stabilisation decreased the circulating load on the circuit and helped to significantly decrease the consumption of chemical reagents used to control pH. The concentrate copper grade increased by an average of 1.2% without loss in process recovery. The circuit stability was improved, reducing the standard deviation of the concentrate grade from 0.9 to 0.7%. 1
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CONCLUSIONS The development and implementation of the new control strategy leads to the following general conclusions: The cleaning circuit controllability is usually constrained, due to of instrumentation malfunctions, mainly due to inappropriate calibration and maintenance methodologies. Thus a complete diagnostic programme should be carried out before implementing any control strategy. Once the major problems detected are solved, there is great opportunity for appropriate use of the information available. Distributed control systems are not sufficient to achieve tight metallurgical objectives, a supervisor with different attributes being needed. Supervisory control systems should be adaptable to different computation platforms, and should consider at least modules for: validation and reconciliation of process data, detection of operation and instrumentation problems and co-ordination of local control loops under an overall strategy. Other important aspects in the success of a supervisory control system are the operator involvement in the project and the ability of the system to be running even when some information is not temporarily available. In our experience, the joint training programme for control room and field operators, instrumental and maintenance personnel, on all the aspects related to the project, has been extremely helpful in co-ordinating all the efforts in relaxing different constraints on the process controllability. In particular the economical benefits of the project exceeded the company expectations, and the payoff period of the project was reduced to two months.
ACKNOWLEDGEMENTS
The financial support of Conicyt (Fondef D96T- 1022) and the Santa Maria University (Project 972723), and the invaluable contribution of Salvador Concentrator personnel at different stages of this work and its permission to present these results are greatly acknowledged.
REFERENCES l,
2.
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4.
5.
6.
Bergh, L.G. & Yianatos, J.B., Control Alternatives for Flotation Columns, Minerals Engineering, 6, N ° 6, 631-642 (1993). Kosics, G.A., Dobby, G.S. & Young, P.D., ColumnEx: a Powerful and affordable Control System for Column Flotation, Proceedings International Conference on Column Flotation, Sudbury, Canada, 359-373 (1991). Hirajima, T., Takamori, T., Tsunekawa, M., Masubara, T., Oshima, K., Imai, T., Sawaki, K. & Kubo, S., The Application of Fuzzy Logic Control Concentrate Grade in Column Flotation at Toyaha Mines, Proceedings International Conference on Column Flotation, Sudbury, Canada, 375-389 (1991). Bergh, L.G., Yianatos, J-B., Acufia, C.P. & Cartes, F., SINCO-COL Application to Flotation Columns in El Teniente Concentrator, Proceedings International Conference Column "96, Montreal, Canada, August, 583-591 (1996). Bergh, L.G., Yianatos, J.B. & Acufia, C.P., Hierarchical Control Strategy for Flotation Columns, Minerals Engineering, 8, N°12, 1583-1591 (1995). Bergh, L.G., Yianatos, J.B. & Leiva, C.A., Fuzzy Supervisory Control for Flotation Columns, Minerals Engineering, 11, N°8, (1998).
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 in M i n e r a l s Engineering is i n v i t e d , p r e f e r a b l y b y em a i l to b w i l l s @ m i n - e n g . c o m , or b y F a x to + 4 4 - ( 0 ) 1 3 2 6 - 3 1 8 3 5 2