MODEL PREDICTIVE CONTROL TO OPTIMIZE MILLING CIRCUITS USING NKOMATI NICKEL MINE AS A CASE STUDY

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1 MODEL PREDICTIVE CONTROL TO OPTIMIZE MILLING CIRCUITS USING NKOMATI NICKEL MINE AS A CASE STUDY King Becerra Product Manager, Advanced Process Control (FLSmidth Inc.) ABSTRACT This paper reviews the installation of an advanced process control solution based on model predictive control technology in a milling circuit, using Nkomati Nickel Mine as case study. Nkomati Nickel Mine in South Africa processes one of the world s hardest ores in a 375k TPM autogenous grinding circuit. The plant employs an unconventional processing circuit, comprising a primary autogenous mill (AG or FAG) and pebble crushing circuit followed by a secondary hybrid pebble/ball mill and classification cyclone cluster. The results conclusively demonstrate operational and economic benefits during circuit operation with the advanced process control system ON. Production performance and circuit stability were significantly better than during manual control. Este artículo revisa la instalación de una solución de control avanzada de procesos en un circuito de molienda, usando la mina de nickel de Nkomati como caso de estudio. La solución implementada se basa en la tecnología de control predictiva basada en modelos. La mina de Nkomati, localizada en Sudáfrica, procesa uno de los minerales más duros del mundo en un circuito autógeno de molienda de 375k TPM. La planta emplea un circuito de procesamiento no convencional, que comprende un molino primario autógeno (AG o FAG) y un circuito de trituración seguido por un molino secundario de bolas y un grupo de ciclones. Los resultados demuestran de forma concluyente los beneficios operativos y económicos durante el funcionamiento del circuito con el sistema de control avanzado de procesos operando. El rendimiento de la producción y la estabilidad del circuito fueron significativamente mejores que durante el control manual. INTRODUCTION The Nkomati Nickel Mine is owned in Joint Venture (JV) by African Rainbow Minerals (ARM) and Norilsk Africa. Each JV partner holds a 50% stake in the mine and jointly manage the mine and processing operations. The circuit is designed to process 4.5MM metric tonnes per annum of Nickel, Copper, Cobalt and Platinum Group Metals ore at a feed rate of approximately 575 TPH. The Nkomati grinding circuit is of unconventional design chosen after an extensive study (Wolmarams & Morgan, 2009) and is based on autogenous primary grinding followed by hybrid pebble/ball mill secondary grinding. 1

2 Primary crushed ore reclaimed from the stockpile is fed at a rate of 575 tonnes/hour via conveyor to an FLS 34 x 17.5 grate discharge, variable speed, gear driven primary autogenous mill installed with dual 5.2MW drives discharging over a 30mm trommel screen. +30mm trommel oversize (pebbles) are deposited on a conveyor that feeds a storage bin. The pebble bin has a dual purpose; to feed pebbles used as grinding media to the secondary grinding mill and to recycle pebbles to the in-circuit FLS Raptor XL600 pebble crushers via an overflow chute on the pebble bin. Pebble crusher product is then fed back to the primary mill. Trommel screen underflow is discharged over a double deck vibrating screen. Screen product +4mm and -16mm from the screen decks is fed onto the pebble bin feed belt and -4mm screen underflow is discharged into the mill sump shared by both primary and secondary mills. Slurry from the mill discharge sump is pumped to a cluster of 16 classifying cyclones via two variable speed cyclone feed pumps. Cyclone overflow is fed to the flotation circuit and cyclone underflow gravitates to the secondary mill feed hopper where it is fed together with -4mm primary mill product and -70mm pebbles into an FLS 23 x 31.5 grate discharge, fixed speed, gear driven hybrid secondary pebble/ball mill installed with dual 5.2 MW drives. The circuit described together with available measurements and actuators is shown in Figure 1. Figure 1 - Available measurements and actuators 2

3 The grinding circuit, photographed shortly after commissioning, is illustrated in Figure 2 below. Figure 2 - Nkomati grinding circuit Advanced Process Control (APC) or Expert Control is currently accepted as an advantage in most modern high capacity concentrator grinding circuits. Several successful case studies reported during the last years, reinforce the operational and economical benefits provided by advanced process control systems (Sims, Lacouture & McKay, 2006; Parker, Thong, Sloan, Pass & Lam, 2006; Rogers, Almond, Maru & Becerra, 2010). Nkomati decided to install an advanced process control system to stabilize the operation, improve the process performance and facilitate ramp up to full production. The selected vendor was FLSmidth who also supplied the grinding mills and pebble crushers for this project. The system implemented was developed based on FLSmidth s ECS/ProcessExpert System (PxP), an advanced process control solution used to stabilize and then optimize key plant processes. SYSTEM OBJECTIVES, IMPLEMENTATION AND CONTROL STRATEGY The application implemented at Nkomati Plant was designed to maintain stable mill operation and material flows while maximizing production and optimizing product particle size. All variables and parameters typical in AG mill operation are managed by the application. 3

4 The objectives are: Stabilize AG mill operation and prevent over filling of the AG mill. Minimize circuit stoppages and allow controlled operation at maximum capacity Optimize control and balance loads between the AG and ball mills. Avoid sump spillage and maintain cyclone inlet pressure to set points. Maintain constant flow to the flotation plant. Keep particle size analysis (manual value) on target. Improve grind and energy efficiency. The system was implemented using an eight-step methodology to assure the success of the PxP Grinding Circuit application: 1. Project planning 2. Kick-off and process interviews 3. Application Design 4. Primary commissioning 5. ECS/ProcessExpert training 6. Remote monitoring and tuning 7. Follow-up visit 8. Long-term support The system was installed at the plant early During the first on-site visit, checking of signals and tags was completed within 5 working days. After that, the system was left gathering data and under remote monitoring and process observation for a period of 12 weeks. Commissioning of the system was completed after a further 6 weeks on site. Final tuning of the system was completed via a remote connection using the connection established during installation. A variety of APC techniques were used to develop the advanced process control solution. As this application has sparse number of measurements and actuators and involves a multi-time scale delayed process, model predictive control was identified as the best technique for this application complemented by fuzzy logic rules. The model predictive control technology uses a mathematical model of the process to predict future process behaviour and pre-plan actions in the future to attain desired targets. The key process measurements required for control were identified between Nkomati and FLSmidth. It was decided to split the application into two main modules or components: the primary grinding circuit comprising the AG mill and pebble crushers, and the secondary grinding circuit comprising the ball mill, sump and cyclones. The user interface was designed to easily identify the actions being performed by the application and enable the operator to partially enable/disable the control strategy whenever an instrumentation or process problem occurs. The PxP graphical operator interfaces for the primary and secondary grinding circuits are shown in Figures 3 and 4 below. 4

5 Figure 3 - ECS/ProcessExpert graphical interface primary grinding circuit Figure 4 - ECS/ProcessExpert graphical interface secondary grinding circuit 5

6 PERFORMANCE EVALUATION RESULTS An evaluation test protocol was defined to identify and formally record benefits realized through the implementation of the PxP at the Nkomati grinding circuit. Both parties agreed to conduct a series of tests to reasonably compare performance data with the PxP System ON and OFF. In summary, eight (8) tests, each of twenty-four (24) hours duration were executed. 8 days in total, 4 days with the PxP switched to OFF and 4 days with PxP switched to ON. The sequence alternated 1 day with PxP and 1 day without until 8 days were reached. Six (6) periods were identified as valid for analysis and measurements of operational benefits. A joint comparison between Nkomati and FLSmidth confirmed the following main achievements at Nkomati: Production: 4.3% increase Energy Consumption: 6.70% decrease in the whole circuit AG Mill Weight: 36% process variability reduction Density: 15% process variability reduction CycloPack Pressure: 44% process variability reduction Pump Speed: 28% process variability reduction P80: 28% quality variability reduction Cyclone Overflow % passing 75µm: 24% quality variability reduction Better representations of the production results by period with and without the PxP are illustrated in Figures 5 and 6. As it can be seen in the figures, the production results were very consistent throughout the whole test protocol. The production results clearly indicate that the performance of the grinding circuit in both operational and economic terms was highly improved when the PxP was ON. Fresh Feed tn / hr Figure 5 - Fresh feed by period with and without PxP 6

7 Circuit Specific Power Consumption Kwh / Ton Figure 6 - Circuit specific power consumption by period with and without PxP The process stability was also improved when the PxP was running. On average, the process variability of the AG mill weight level, ball mill weight level, cyclopack pressure, pump speed and density was 36%, 43%, 44%, 28% and 15% lower when the PxP was ON. Figures 7 to 10 illustrate a better representation of the process stability results by period with and without the PxP. As it can be seen in the graphs, the process stability results were very consistent along the whole test protocol. 3.0 Standard Deviation of AG Mill Weigth Figure 7 - AG mill weight standard deviation by period with and without PxP 7

8 Standard Deviation of Ball Mill Weight Figure 8 - Ball mill weight standard deviation by period with and without PxP Standard Deviation of Cyclopack Pressure Figure 9 - Cyclopack pressure standard deviation by period with and without PxP The mill stability was significantly improved when the PxP was running, as process results clearly indicate. Benefits in terms of ultimate circuit capacity and overall circuit power efficiency will arise, as consequence of the improvement in consistency and stability of the grinding circuit control. The payback time of the PxP System, at Nkomati Plant, is less than two months, as a result of increasing the production by 4.3% and decreasing the energy consumption by 6.7%. Both operational and economical results make this a very successful project. The economic benefits go directly to the bottom line once the return on relatively modest investment is reached. 8

9 Standard Deviation of Cyclone Density Figure 10 Cyclone density standard deviation by period with and without PxP KEY FACTORS FOR A SUCCESSFUL IMPLEMENTATION For an advanced process control project to be successful, several factors are required. To deliver the expected results, the supplier must combine experience in advanced process control techniques and process know-how. The following factors were critical for the success of the Nkomati PxP project, and in general, represent the formula for success for any advanced process control project: Methodology As explained above, an eight-step methodology was followed to assure the success of the ECS/ProcessExpert Grinding Circuit application. This methodology comprises all the activities that are required for an efficient development of advanced process control solution, aligning customer expectations with the application goals for the successful commissioning of the system. Techniques A variety of APC techniques were used to develop the advanced process control solution at Nkomati Plant. As this application has sparse number of measurements and actuators and involves a multi-time scale delayed process, model predictive control was identified as the best technique for this application complemented by fuzzy logic rules. System Implementation Process interviews were a critical success factor to properly design the control strategy. Process observation and analysis followed the process interviews and provided additional evidence to confirm and suggest modifications to the initial control strategy. The system was prepared based on those agreed upon control strategies. 9

10 The interaction with the customer was the most relevant success factor during the system implementation. Through daily meetings, the system performance was analyzed, opportunity areas were identified and the required activities towards completion of the project were agreed between both parties. Robustness The PxP is based on the FLSmidth s proven industrial platform, ECS (Expert Control & Supervision) specially developed for supervisory control, monitoring and reporting functions. Native I/O drivers were used to communicate the PxP directly with the PLC. The Nkomati PxP required no third-party systems to be installed. Further contributors to the robustness of the controller are the selection of the right technology for each specific goal and the measurement reliability-check algorithms in the PxP. At the time of preparing this paper, on average, the utilization factor is 96%. System utilization is an indirect measure of success of advanced process control projects Remote Monitoring Remote monitoring services for troubleshooting and tuning are available through a secure internet connection which enables the supplier s technical experts to effectively support the system remotely. These remote monitoring services are used by the supplier to constantly improve the system performance, and assure the longevity of the system. Process and Technology Know-How The combined know-how of the APC supplier and the plant owner was the foundation for the success of the project. The process interviews were the starting point to gather and consolidate the know how into the application design. CONCLUSIONS The PxP has been successfully implemented on the grinding circuit at Nkomati Plant. The recorded results demonstrate benefits during circuit operation with the. Production performance and circuit stability were significantly better than during manual control. On average, the production was 4.3% higher and the whole grinding circuit energy consumption was 6.7% lower when the PxP was ON; the process variability of the AG mill weight level, ball mill weight level, cyclopack pressure, pump speed and density was 36%, 43%, 44%, 28% and 15% lower when the PxP was ON. 10

11 A PxP model predictive control module has been used as the main process control technique. The application has proven its ability to effectively control the grinding circuit. At the time of preparing this paper the system utilization was 96%, an indirect measure of the success of the project. This utilization is very high and is attributed to a high degree of operator confidence together with the robust nature of the installed system platform. ACKNOWLEDGEMENTS The author would like to acknowledge and express thanks to the following: The Management and Operational Staff of the Nkomati Nickel Mine, for their support in gathering, analyzing and approving data for publication. Henri van der Ryst (Nkomati), Dave Almond and Tejas Maru (FLSmidth Automation Division) for their attention to detail during data analysis. Their joint valuable experience ensured that data was interpreted appropriately and without bias. The Management of FLSmidth, for their approval of this case study for presentation at Mining International Convention XXIX. This case study was based on the article named Model Predictive Control as a Tool for Production Ramp-Up and Optimization at the Nkomati Nickel Mine, first published and presented in the SAG 2011 Proceedings (Vancouver, British Columbia, Canada; September 25 to 28, 2011). REFERENCES Parker, S., Thong, S., Sloan, R., Pass, D. & Lam, M. (2006). Comparative study of grinding expert control on two SABC circuits at Barrick Gold Corporation, International Autogenous and Semiautogenous Grinding Technology 2006 (vol. III, pp ). Vancouver, B.C.: Department of Mining Engineering University of British Columbia. Rogers, M., Almond, D.G., Maru, T.D., Becerra, K (2010). Model Predictive Control Application at Lumwana Copper Concentrator, 2 nd International Congress on Automation in the Mining Industry. Santiago, Chile: Automining2010. Sims, S., Lacouture, B., McKay, J (2006). Grinding Expert System Operation at Red Dog Mine, International Autogenous and Semiautogenous Grinding Technology 2006 (vol. III, pp ). Vancouver, B.C.: Department of Mining Engineering University of British Columbia. Wolmarans, E., Morgan, P. (2009). Milling Circuit Selection for Nkomati 375ktpm Concentrator, Base Metals Conference 2009 (vol. 109, pp ). Kasane, Botswana: The Journal of the Southern African Institute of Mining and Metallurgy. 11