Electrode Control and Regulation in Submerged Arc Furnaces
Published on : Tuesday 04-08-2020
Sureshbabu Chigurupalli elaborates upon how challenges of electrode management in submerged arc furnaces are overcome by algorithms developed on resistance measurement.
The evolution of industrial process automation today is progressing at a much faster rate compared to the last decade. As the competition is gearing up and bottom lines are diving, industries are moving towards more data-driven and productivity rather than age-old concepts of labour driven technology. We would soon see IIoT, Cyber-Physical Systems, and lots of industrial automation everywhere making industries much better than of today. The upgradation of technology in SAF (submerged arc furnaces) is even though slow but is making progress as it is inevitable to stay in the competitive market during the era of disruptions. To increase the efficiency over manual labour and to create a quality product at a faster rate many ferroalloys industries are rapidly moving towards the process automation.
A case of implementation of automation in SAF
Operations in SAF revolve around how effectively one is doing smelting by penetration of electrode in the charging burden. The techno-economic impact plays a significant role in electrode management. Automation of electrode operation plays a massive role to reduce the cost and improve the output. Many SAFs are using one or more forms of electrode control to optimise the electrode penetration for better control of smelting inside the furnace. Optimised electrode operation results in better recovery of alloy metal from the raw mix and reduces electricity consumption.
The challenges of electrode management are overcome by algorithms developed on resistance measurement. SAF operations suffer from several complexities due to the nature of the electrical circuit of the electrode system which is interconnected among themselves with burden mix and molten metal bath. The smelting process is working on the Joule heating method where power is
drawn by the electrode based on the resistance of the burden mix and molten metal bath. This leads to an interaction effect where variations in one electrode’s current can cause comparable changes to the currents in the other electrodes. This makes a huge impact on larger size furnaces due to a considerable drop in power factor. This problem is largely overcome by the resistance control method.
In the resistance control method, the resistance encountered by each electrode is predominantly dictated by the length and conductivity of the current path from the electrode’s tip to the molten metal bath, which acts as the three-phase circuit’s floating neutral point. Hence resistance changes due to tip position or conductivity changes beneath one electrode, do not impact the resistances beneath the others, effectively dissociating the control of the individual electrodes. Resistance-based control is therefore considered to be superior to the current control method where the electrodes are operated on the set current. Many SAFs are globally using the resistance-based algorithms logic developed by taking analogue and digital inputs of current, voltage, tap position of the transformer, and holder position of the electrode.
Resistance calculation algorithms require certain input readings from the furnace for sending regulation commands. The primary current, voltage, power monitor, etc., are integrated with PLC for the regulation of electrodes, penetration for better control of the smelting zone. The smelting zone is created by Joule heating principle. Joule heating, also known as resistive, resistance, or Ohmic heating, is the process by which the passage of an electric current through an electrode produces heat. The basic principle of operation is shown in the Fig 1 where resistance is controlled by altering the movement of the electrode.
Resistance set point may vary from type of raw material. Based on the mass balance of the raw material there will be a change in the power requirement. Schematic diagram of the electrode assembly is shown in Fig 2.
The general layout of PLC configuration with algorithm is shown in Fig 3. Feedbacks of voltage, current and tap position are taken from the primary side of the transformer to reduce the errors.
Resistance control algorithm implementations in one of the SAF is shown in Fig 4 and Fig 5. Manual intervention and control of the electrode was inconsistent and the same has been improvised after the implementation of furnace controller. Pictorial representation of the interaction effect is shown in Fig 6. Asymmetrical currents of the electrodes are corrected by using the algorithms controller.
Advantages
Mentioned below are some of the benefits with resistance-based algorithms:
1. Elimination of unnecessary electrode movement caused by the electrical interaction between electrodes (which is common in current based control).
2. Consistent and even power distribution between electrodes.
3. Consistent penetration of electrode to maintain optimised metallurgical condition for better smelting zone.
4. Elimination of manual intervention and to improving the ergonomics and efficiency of manpower.
The resulting trends are seen in Fig 6.
Conclusion
Resistance based algorithm controller is very popular among then SAF operations due to its inherent advantages. However, the result may vary based on the furnace design, application, and mass balance of the burden mix. Different study and analysis reports suggest that there is 4-5% improvement in yield, specific power, power factor, load factor and recovery.
References
1. A B Stewart and I J Barker - A solution to measurement problems and interaction effects in the control of submerged arc furnaces, National Institute for Metallurgy, South Africa.
2. B A Ngwenya, L Mabiza, I J Barker, A De waal, M S Rennie, P Mailer (1995) – The performance of a resistance-based furnace control system on a submerged-arc furnace, Infacon 7, Trondheim, Norway.
3. T E Magnussen (2018) – Basic parameters in the operation and design of submerged arc furnaces, with particular reference to production of high-silicon alloys, The Journal of South African Institute of Mining and Metallurgy, Volume 118, pp 631-636.
4. Michael M Gasik, (2013) Handbook of Ferroalloys, pp 29-83.
Sureshbabu Chigurupalli is Unit Head – Plant Operations, Balasore Alloys Limited, Odisha. Sureshbabu is leading and managing all plant operations with effective utilisation of all resources and implementing industry best practices such as TPM, Six Sigma, Lean Management and other Business Excellence initiatives that contribute to improve productivity and efficiency. He has exhibited leadership in closely collaborating with numerous Japanese Consultants for implementing TPM to enhance overall plant effectiveness.
A B.Tech in Instrumentation from Andhra University, Sureshbabu is an enterprising leader and planner with a strong record of contributions in streamlining operations, invigorating businesses, heightening productivity, systems and procedures. He has achievement-driven professional experience in spearheading entire unit/plant operations to maintain continuity and match organisational goals through supervising Operations, Quality Control, Production Goals, Automation, Maintenance, Process Improvements, Safety Guidelines, Manpower Development, New Policy/Procedure Guidelines, Resource Allocation and Cost Optimisations.
