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Proceedings of the XXI International Mineral Processing Congress
IMPROVING
CONTROLLABILITY
ON FLOTATION
COLUMNS
L.G. Bergh, J.B. Yianatos Chemical Engineering Department Santa Maria University, Valparaiso, Chile
Abstract
Flotation columns are common devices in cleaning circuits in the mineral processing industry. The operation and control of these columns often have the final responsibility for the quality of the concentrate grade and, to a less extent, for the recovery of the cleaning circuit. The use of basic distributed control has frequently lead to a large variability in concentrate grade and recovery, as can be observed in many concentrators world-wide. The contribution to this variability usually comes from different sources, severely constraining the performance of conventional control systems. In this paper, the industrial experience in developing supervisory control systems is discussed in order to provide procedures for the diagnosis of instrumentation, calibration and maintenance, prior to the implementation of control schemes on top of the distributed control system. Examples based on control systems developed for E1 Teniente and Salvador Concentrators, from Codelco-Chile, are used to illustrate how some of the constraints on the controllability of the process can be relaxed. Keywords: flotation columns, process control, instrumentation, diagnosis Introduction
Flotation columns are now used worldwide as efficient cleaning processes in a large number of sulfide mineral concentrators. Increasing degrees of freedom in their operating variables have led to large variations in metallurgical performance and therefore to increased scope for improving their control. In this process, stable operation and consequent consistent metallurgical benefits can only be obtained if basic distributed control systems are implemented. In general, wash water and air flowrates and froth depth are measured on line, while tailings, air and wash water flowrates are manipulated. On line analyzers, tailings and feed flow-rates and some other measurements are often incorporated into the system when a supervisory control strategy is implemented on top of a distributed control system. The primary objectives, as indices of process productivity and product quality, are the recovery and the concentrate grade. Their on-line estimation, however, usually requires a significant amount of work in maintenance and calibration of on-stream analyzers, in order to maintain good accuracy and high availability. It is therefore common practice to control secondary objectives, such as froth depth, gas flowrate and wash water flowrate (Bergh and Yianatos, 1993). This control is known as a stabilizing strategy. Lack of accurate measurements, non-linear dynamics and high interaction among variables are some of the main problems associated with stabilizing control. These characteristics reduce the effectiveness of conventional PID control without a supervisor to co-ordinate the control loops. The use of basic distributed
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Process Simulation and Control
control has frequently lead to a large variability in concentrate grade and recovery, as can be observed in many concentrators worldwide. This variability is usually due to different factors, such as disturbances entering the process from the column feed, temporal malfunction of water and air distributors, instrumentation problems related to calibration, maintenance and failure, and lack of co-ordination in the use of resources such as froth depth, air flowrate and wash water flowrate. This paper focuses on highlighting a revision of those limiting aspects in order to relax some of these hard constraints enabling the implementation of a supervisory control that may achieve reasonable performance and large availability over time. The discussion is based on the experience of developing, commissioning and evaluating the SINCO-PRO at Salvador (Bergh et al., 1999) and the E1 Teniente (Bergh et al., 1996) concentrators in Codelco-Chile. Plant installation and results El Teniente concentrator
E1 Teniente Division of Codelco-Chile produces over 340,000 t/y of copper and 1,900 t/y of molybdenum. A general scheme of the circuit is shown in Figure 1. Feed [ L, Rougher column 1st cleaner i ~~..~,. column
q ~
-~ Final tailings [ Feed I
d
Rougher sewell 1st cleaner sewell
~ ~
2nd
711
.....]
I [ ~~Final
Scavenger circuit "
Cleaner circuit
[ Mo/Cu ] circuit Cu concentrate
Figure 1" E1 Teniente Concentrator general flotation circuit.
To obtain this output over 97,000 t/d of ore was mined. The ore from sewell (acid circuit) and column (basic circuit) is floated in separate rougher and cleaning stages. Both concentrates are cleaned in a second common stage by four flotation columns in parallel and feeds the molybdenum/copper separation circuit to obtain the final concentrates. The second cleaner circuit consists of four columns, 2• m 2 for the rectangular section and 14 m in height. The first cleaner concentrates, coming from column and sewell, are mixed and split into two streams, each one feeding a group of two columns. The circuit global head, tailings and concentrate are analyzed by an onstream X-ray fluorescence analysis system Courier 300 from Outokumpu. The column 1 concentrate and tailings grades in particular are also measured. The feed flowrate every two columns, the global tailings flowrate and column 1 tailings flowrate are
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Proceedings of the XXI International Mineral Processing Congress
measured by magnetic flow meters. The airflow rate is measured by a combination of orifice plate and dp/cell in each column. The wash water flowrate is measured in each column by magnetic flow meters. Globe type pneumatic control valves are used to regulate the air and wash water flow-rates. Pinch type pneumatic control valves are used to regulate the tailing flowrate in each column. The froth depth is estimated using a pressure measurement under the pulp-froth interface. All sensors and control valves are electrically linked to a TDC-3000 distributed control system from Honeywell. The TDC-3000 system communicates through a CM50S interface to a DEC microVAX 3100/80 computer. Salvador Concentrator The average ore grade was 0.7+0.75% Cu and 0.022+0.026% Mo. The circuit tonnage was 34,000 t/d. Figure 2 shows the flotation circuit.
Regrinding
w . ~ C1
Figure 2: Instrumentation and distributed control system at the Salvador Concentrator.
The flotation feed comes from the hydrocyclone overflow of the grinding circuit. The feed pulp was distributed in four parallel rougher flotation banks. The rougher concentrate is reground and sent to a single cleaning stage or can be partially diverted to a thickener, allowing the control of the feed flowrate to the column circuit. The rougher tailings go to general tails. The single cleaning stage consists of two columns in parallel and produces the Cu-Mo bulk concentrate. The columns are rectangular in cross-section, 2• m 2, and 13 m in height. Column tailings are distributed in two parallel scavenger banks. The scavenger concentrate was 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 first to a thickener and then on to the molybdenum plant.
Process Simulation and Control
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The feed flowrate to the columns is regulated using a variable speed pump, and the feed tank is provided with an overflow connected to a thickener allowing for an extra surge capacity. The columns operate with three control loops to regulate the air, wash water and froth depth, as shown in Figure 2. Moreover, four in-line AMDEL analyzers are used to monitor the process. Thus, column feed, concentrate grades, rougher and scavenger tails are continuously monitored. Another control alternative is the addition of reagents, such as frother, to increase column froth recovery, and the addition of lime to regulate pH for iron control. The supervisor SINCO-PRO was developed in Control Language in the Application Module of a TDC-3000 Honeywell system. All process data is collected and displayed on screen in a TDC-3000 system and sent through a PCNM software interface 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, set point values and messages to operators are returned to the system to implement the control actions and to display consistent process variable values, performance indices and messages. SINCO-PRO evaluation Figure 3 shows a sequence of concentrate grade and column recovery differences between column 1 and global circuit at E1 Teniente Concentrator. 4
..........................................
15 10 5 0 -5
~
2 -3 -4
i,lfdi ......
.........................................
-10 -15 -20 Time (d) (a) Concentrate
Time (d) (b) Recovery
Figure 3: Performance difference b e t w e e n c o l u m n 1 and global circuit at E1 Teniente.
At the Salvador Concentrator, 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 4. The feed grade of the plant remained almost constant, between 0.7% and 0.8%, during both periods of evaluation. The stabilization of the whole cleaning circuit by the supervisor resulted in an average increase of the column feed grade from 8.6% to 10.1% and the standard deviation was reduced from 1.3% to 0.4%. This stabilization decreases the circulating load on the cleaning circuit and help in significantly decreasing the consumption of chemical reagents for pH control. The concentrate copper grade experimented an average increment 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%.
Proceedings of the XXI International Mineral Processing Congress
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33 ~" 32 ~ 31
,~ 33 32 '~ 31 ,1= 30 o = 29 o
~ 30 o
~ 29 o
r~ 28
28 27
'
0
10
20
'
30 Time (d)
(a) Period N o v e ~ - D e c e ~
'
'
40
50
27
10
0
60
1997 after SINCO-PRO
20
30 Time (d)
40
50
60
(b) Period August-Septerrlx~1996 usingDCS
Figure 4: Evaluation at the Salvador Concentrator.
Figure 5 shows the column operation with SINCO-PRO at the Salvador Concentrator, from January 1998 to June 1999. During the first six months the columns operate at conditions similar to those during the evaluation period. Following this period, the temporary shut-down of a large mill, the higher content of oxide copper minerals in the feed and a late decrease in the copper price have contributed to a change in the concentrator grade-recovery policy in order to maintain the copper production. Thus, the mill throughput was increased, the rougher concentrate and the column feed grades decreased (10% to 6%), and the new final concentrate grade was maintained around 30% Cu, also improving the column recovery by 10%. The SINCO-PRO system has been able to manage this operation without any trouble during the last 18 months as shown in Figure 5. ,q.u
o Feed o Conc. 35 O
30
25 0.,I
20 O
etO
=
15 O
10
0
100
r
i
i
i
200
300
400
500
600
Time (d) Figure 5: Colunm operation at the Salvador Concentrator, January 1998 - June 1999.
Improving controllability In practice, the extension of the success of any control approach may be severely limited by different constraints, as it is schematically shown in Figure 6. As can be noted, many aspects can affect the performance of a process under control. There are
Process Simulation and Control
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constraints related to process design, layout, specifications, installation and maintenance of equipment integrating the process. There are also constraints on the quality (accuracy, repeatability) and availability of the information gathered from the field instrumentation and communicated to a computer interface. In the supervisory control implementation some constraints appear to be related to computer hardware and programming languages, control algorithms, and perhaps the most important of all, lack of process knowledge (Bergh and Yianatos, 1999). Constraints: Constraints: 9 availability 9 9
accuracy
repeatibility
Constraints: 9
I 'nstrumentat'~I "~~~u~t'rS;ry
design
9
layout
9
specification
9
installation
9
maintenance
........
Process
Figure 6: Constraints on supervisorycontrol. The successful implementation of the SINCO-PRO hierarchical control strategy was made possible by carrying out a complete program before implementing the new control strategy, thus relaxing some of the strict constraints mainly found in the process and instrumentation. Examples of frequently found constraints are: Process constraints
-
Internal launder design, limiting the carrying capacity and disturbing the froth transport pattern. Tailings discharge piping layout and cavitation of pinch valves, limiting froth depth control and feed flowrate distribution to both columns. Concentrate spill in the discharging channel, limiting the checking and maintenance of local instrumentation. Wash water distributor plugging, limiting proper distribution of water. Lack of appropriate maintenance programs. Installed air spargers came from different suppliers and previous comparison studies showed confuse results. Lack of appropriate maintenance programs.
Instrumentation constraints
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Significant noise on feed flowrate measurement (magnetic flowmeter) leading to loose feed flowrate control and distribution to both columns. Pulp level measurement problems in the feeding tank leading to excessive control actions and pulse feed flow and thus creating instability in the operation of both columns.
Proceedings of the XXI International Mineral Processing Congress
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-
Frequent discalibration of froth depth measurement (pressure in an inverted tube) leading to poor froth depth control. Control bypass valve opened as a policy to remedial problems on air supply system. Plugged pipelines and stacked valves limiting water flowrate supply. Calibration problems of magnetic flowmeters. Low availability of on stream analyzers. Frequent discalibration of on stream analyzers. Lack of instrumentation to monitor air pressure in manifolds. Pressure regulator malfunction due to poor condition of instrumental air.
-
-
-
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Supervisory Control constraints Computer hardware and programming languages. - Inappropriate computer-operator interface. Lack of process knowledge in developing the control strategy and maintaining the system benefits over time. Lack of training of field operators, instrumentalist and maintenance personnel. Managing problems between operators, instrumentalist and maintenance supervisors. Appropriate instrument and device calibration and maintenance programs can easily relax some of these constraints. Others may be partially removed by changing and unifying operating practices through extensive training programs. Those still remaining and limiting the process control require to be considered in the supervisory control strategy. Usually this is accomplished by developing special software modules to detect instrumental and operating problems, leading to automatic remediation or messages suggesting actions to operators. -
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-
C
o
n
c
l
u
s
i
o
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s
Hierarchical control is truly an alternative solution to the problem in an integral form, able to manage information obtained on-line (measured directly or by inference) subject to failure and error calibrations, to detect, alarm and sometimes correct operating problems, and to co-ordinate local conventional control loops by using logical rules. In this way, it has been shown as a powerful tool in increasing the operatingavailability and the product quality of complex processes, such as flotation columns. The flotation circuit controllability is usually limited because of instrumentation malfunctioning mainly due to inappropriate calibration and maintenance methodologies. Furthermore, constraints on process design, piping layout, equipment specification, installation and maintenance contribute to limit the achievements of any control system. Hence a complete diagnostic program should be carried out before implementing any control strategy. Once the major detected problems are solved, there is a greater opportunity for an appropriate use of the available information. Distributed control systems are not sufficient in achieving strict metallurgic objectives. In this case a supervisor with different attributes is needed. Supervisory control systems should be adaptable to different computation platforms, and should consider, at very least, modules for: validation and reconciliation of process data,
Process Simulation and Control
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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 operator involvement in the project and the ability of the system to continue running even when some of the information is not temporarily available. In our experience, the joint training program for control room and field operators, instrumentalist and maintenance personnel, related to the project on all the aspects, has been extremely helpful in coordinating all the efforts in relaxing different constraints on the process controllability. Acknowledgements
This work has been possible thanks to the financial support of Conicyt (Project Fondecyt 1990859) and the Santa Maria University (Project 992723). References
Bergh, L.G. and Yianatos, J.B., 1993. Control Alternatives for Flotation Columns. Minerals Engineering, Vol 6, N~ 6, 631-642. Bergh, L.G. and Yianatos, J.B., 1999. Supervisory Control Experience on Large Industrial Flotation Columns. Proceedings Control and Optimization in Minerals, Metals and Material Processing Symposium. Quebec, Canada, August 22-26. Bergh, L.G., Yianatos, J.B., Acufia, C.P. and Cartes, F., 1996. SINCO-COL Application to Flotation Columns in E1 Teniente Concentrator. Proceedings International Conference Column'96. Montreal, Canada, August, 583-591. Bergh, L.G., Yianatos, J.B., Acufia, C.P., Prrez, H. and Lrpez, F., 1999. Supervisory Control at Salvador Flotation Columns. Minerals Engineering, Vol 12, N ~ 7, 733-744.