Figure 2: Top view of injectors for oxygen, carbon, fuel gas and flux, in an EAF. Source: Electric Furnace Steelmaking,Treatise on Process Metallurgy, Vol 3, Jorge Madias, Argentina

Operating a furnace like a Formula#1 racing car is exciting, but there’s a downside to it

By Ananda Bhattacharjee


Melting steel in an electric arc furnace (EAF) is a highly energy-intensive process. There are various sources of energy: electricity, natural gas, oxygen; all being pumped in at an enormous rate, in a modern EAF. The only aim is to melt and tap the steel as fast as possible, and consuming energy as less as possible. While the prospect of operating a furnace like a Formula#1 racing car feels exciting, there is a downside to it.

The high rate of pumping energy into the furnace reduces the energy consumption because the process time is reduced, thereby reducing the time-dependent energy losses. However, under such circumstances of high-speed energy transfer, it is very important that the process in the furnace does not deviate from its expected path. Deviations cause loss of energy and consequently loss of money. Hence, the need to have adequate modern, real-time, digital control systems arises.

The purpose of these control systems is to guide the operator as well as the various equipment systems through the process, so that the end of the process is reached with the minimum possible expense of energy and materials, as well as in the minimum possible time. The systems collect process data from the field sensors and instruments that are located at different points in the EAF. The data is evaluated to understand the progress of the process. This is done with reference to advanced process models that have been developed. The evaluation results are fed back for operator or equipment for corrective action or response.

Fundamentally, an EAF process achieves the following:

  • Melts scrap efficiently;
  •  Melts DRI efficiently;
  •  Helps in dissolution of fluxes;
  •  Heats up a flat bath efficiently;
  •  Decarburises and de-phosphorises the bath;
  •  And finally, achieves the target steel chemistry and temperature before tapping

The process starts with scrap melting only with the help of electric power supplied through graphite electrodes. Then the subsequent steps join in at different points of time and proceed to completion before the steel is tapped from the furnace. All the above steps proceed almost concurrently, with remnants of submerged scrap melting away towards the end of the process. The external inputs (other than the metallic charge) into the furnace are in the form of electric power, oxygen injection, flux addition, fuel gas, etc.

The condition inside the furnace is highly dynamic. It changes as the melt temperature increases, slag chemistry evolves, decarburisation rate varies, etc. The supply of energy and other inputs also needs to be altered in tune with the conditions existing inside the furnace at that time. This calls for a dynamic process control.

Dynamic process automation has multiple advanced field-sensors located at various points in the EAF. These sensors collect information continuously regarding off-gas composition, flow rates and temperature, parameters of the arcing system, slag condition, etc. This information is then processed through various updated process models. The state of the process is thus evaluated at any point of time. Suitable parameter/process controls are then executed to guide the process on the pre-determined path. On the other hand, conventional process control is based on periodic measurements of process parameters. The parameter/process controls that are executed under conventional process control are based on simple statistical analysis and are therefore not as reliable as the modern dynamic process automation.

Dynamic process automation has taken giant strides in the steel industry today. It has made the required process control possible even in the hot, dust-prone and hazardous conditions of an EAF. The remarkable progress in the digital world that has facilitated the evolution of the dynamic process automation are:

  • The steep rise in data volume storage capacity, computational power and connectivity.
  • Development of new-age sensors with high accuracy.
  • The emergence of data analytics.
  • New forms of human-machine interaction such as touch interfaces and augmented-reality systems.
  • Improvements in transferring digital instructions to the physical world.

The Present Status

Most of the EAFs in the country are still operator-centric. It means that the operators have established a set of control points and process parameters through which they allow the melting and refining processes to proceed in the furnace. These control points and the specified parameters have been arrived at with the help of their knowledge and also their practical experience of the process and statistical data. Such process optimisation is based on characteristic values per heat: electric energy demand, electric power input rate, metallic yield, tapping temperature, steel sample analysis, tap-to-tap time, etc.

The operator-centric EAF process has evolved with time as EAFs have been modernised by introduction of newer technologies and control systems. This operator-technology collaboration over the years has, of course, led to tremendous improvement in the operations of EAFs.

Figure 1: Evolution of EAF steel making, electric steel making, Treatise on Process Metallurgy, Vol 3, Jorge Madias, Argentina

However, more needs to be done. Benefits from standalone component systems of EAF have reached a plateau. There is a goldmine of benefits that lay untapped because they are beyond the capacity of standalone equipment systems and existing level of operator intervention. Additionally, human interventions are sometimes lax.


Figure 2: Top view of injectors for oxygen, carbon, fuel gas and flux, in an EAF. Source: Electric Furnace Steelmaking,Treatise on Process Metallurgy, Vol 3, Jorge Madias, Argentina

The Way Forward

The need of the time is to have interconnected systems that exchange information about the real-time state of the process and respond to that information by suitably adjusting their performance.

EAFs usually operate with the following systems:

  •  Electrode regulation system for arcing;
  •  Oxygen blowing system;
  •  Carbon and flux injection system;
  •  DRI and flux feeding system;
  •  Fuel gas burner system;
  •  Refractory system;
  •  Water cooling system; and
  •  Process gas suction and cleaning system.

Each of the above systems plays a vital role in carrying out the job of melting and refining of steel. The refractory system and the water-cooling system can be considered as static, since there is practically no change in input as the process progresses. The inputs from the other systems change and adjust according to the demands of process.The key to the improved performance of “intelligent systems” is that they deliver inputs into the process viz, electric power, injected carbon, injected flux, oxygen, etc, according to the requirement of the process. The coordinated effort raises the performance of EAFs as a whole.

The Power Input To EAF

The electrode regulation system facilitates feeding of melting electric power into the furnace. In a “smart” furnace an artificial intelligence tool optimises the electric power input into the furnace by setting the optimum setpoints for the electrode arc regulation and current control loop based on the dynamic conditions of the furnace.

The arc length is kept long when scrap is all around the electrode, thereby enhancing heat transfer by radiation. When flat bath has been achieved, the power input and the arc length adjust to an optimum level so that the arc is covered by a foamy slag, thereby keeping refractory erosion in control. If the slag foaming is not adequate, the oxygen, carbon and flux injection is suitably altered to achieve adequate slag foaming.

The DRI and flux feeding rate is adjusted according to the power input rate in the furnace. This ensures smooth melting of DRI and prevents formation of “ferroberg”- a floating lump of un-melted DRI.

Thus, multiple systems operate in close coordination, adjusting inputs to the furnace in accordance to the demands of the conditions existing in the furnace at that point of time. There are “intelligent” electrode regulation systems, including oxygen, DRI and flux modules that fill this requirement. AMIGE is one of the makers of such systems.

Operator intervention with the help of isolated systems have limitations in understanding, timely and accurately, the conditions that exist inside the furnace and therefore input parameter adjustment may be delayed, inadequate or faulty – here lies the utility of new age sensors, computational power, connectivity, analytics and digital instructions to hardwired equipment.

Furnace Off-gas Measurements

Continuous online analysis of off-gas composition and flow rate provide very useful insight into the decarburisation process. Assessment of carbon oxidised from the bath, the carbon remaining in the bath and the balance oxygen blow required to be blown, can all be done on a continuous basis by analysing the measured data and correlating it with the total carbon content in the charge-mix. Without off-gas analysis, operators have to rely on static process information (steel sample analysis, celox analysis) and highly simplified process models to operate and control their EAFs.

Carbon in the liquid steel is oxidised and removed by blowing oxygen into the liquid steel. Carbon escapes the steel bath in the gaseous form of carbon monoxide. This process of carbon removal continues throughout the EAF process and the rate of decarburisation varies and is dependent on many factors, including the steel temperature and its carbon content at that point of time. A scenario can be imagined where an EAF is in refining stage of steel making. The operator has an estimation of the amount of oxygen that will be required to be blown before he extracts a steel sample to ascertain the carbon content. He interrupts the oxygen blow on the basis of his experience of oxygen usage needs and visual observation of the steel bath. Since he has no real-time information of the carbon remaining in the bath, there is a possibility that he might blow excess oxygen, or he might have under-blown. In both the cases of under-blow and excess-blow, there are losses: loss of productivity, loss of metal yield, loss of heat, etc. Any loss costs money.

There is an innovative automation system developed for the dynamic control and optimisation of the EAF that is based on the real-time measurement of furnace off-gas composition, dynamic process inputs and online process models. Tenova is manufacturing one such product. It is an approach to EAF control and optimisation that builds on the EFSOP real-time off-gas analysis system. The benefits of furnace control and optimisation based on off-gas measurement using the EFSOP system have been reported.

Figure 4: EAF layout at DEWG Siegn, probe at point A, Source: Improved EAF Process, European Commission Research Fund for Coal and Steel

The adoption of real-time off-gas analysis has provided many steel makers with a tool for understanding the dynamics of their process. A lot of information, previously unknown, especially related to rates of oxidation and decarburisation, are now available. The process insights generated lay the foundation for future innovations.

Figure 5: General arrangement of dynamic automation and systems in EAF, Source: Author’s depiction

The Advantages

EAFs around the world have attempted to use these process automation modules and have drawn benefits from the same. Dynamic process control modules provide the following advantages:

  • Improve process reliability;
  •  Improve productivity;
  •  Facilitate deeper insights into the process to make future innovation easier,
  •  Reduce consumption of energy and material, and
  • Reduce cost of production

It is important that more EAFs adopt modern dynamic process automation systems, to improve process stability, which in turn leads to product reliability, not to mention the cost reduction potential.



(The author is a freelance steel technology consultant based out of Kolkata, India. He may be contacted at or +919763777846)

This article is a compilation of information drawn from various sources and the author’s personal views on them.


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