Reducing energy consumption during the melting of metals in induction furnaces through the application of best practice and the analysis of digital melting process data

In a crucible-less induction furnace, there is a ceramic crucible situated within a cylindrical copper coil. The material in the crucible is situated within an electromagnetic field generated by the current flowing through the copper coil. This induces eddy currents in the metal. The ohmic losses from these eddy currents heat the metal and eventually cause it to melt. 

Such induction crucible furnaces achieve efficiencies of over 80 per cent for ferrous materials and over 70 per cent for highly conductive materials such as copper or aluminium, provided the copper in the coil is highly conductive and the electromagnetic field is returned with minimal leakage via yokes made of transformer sheet. 

Alternatively, an induction furnace can also be constructed according to the channel furnace principle.

In this case, a so-called channel inductor (or several of them) is flanged onto an upper furnace vessel. The liquid melt is heated according to the principle of a short-circuited transformer. A copper coil forms the primary winding and a channel of liquid metal forms the short-circuited secondary winding. The short-circuit current of the transformer then flows through this channel, and its ohmic losses in turn heat the metal. This electrical principle achieves efficiency levels that are 10–15 percentage points higher than those of the crucible furnace principle. However, it has the disadvantage that the furnace must not be completely emptied, which imposes restrictions on alloying and operational flexibility. 

The crucible furnace also has the advantage that significantly higher capacities can be achieved. For instance, crucible furnaces for iron and steel with capacities exceeding 20 MW and melting rates of more than 40 t/h are successfully in use. 

Even though the induction furnace can be operated CO₂-free using electricity from renewable energy sources, the foundries using them strive to run the furnaces with the lowest possible electricity consumption. This is done for reasons of sustainable resource conservation and also to ensure the economic viability of foundries and semi-finished product plants, particularly in the face of rising energy costs. The melting of iron or aluminium materials requires approximately 500–560 kWh/t; consequently, energy costs often become a significant factor in the production of castings and semi-finished products. 

Three main factors influencing how a foundry can save energy during the melting process:  

• Plant sizing and the structure of the electricity supply contract

• Practical operation of melting furnaces

• Analysis of digital melting process data

Assessment and sizing of the plant and compliance with the terms of electricity supply contracts

Today’s electricity supply contracts usually specify a power charge, a unit price and a reactive power charge. The costs associated with the capacity charge can be reduced by ensuring that the plant draws power from the grid as evenly as possible. The energy supplier charges accordingly for the provision of peak capacity, which it must supply from the generation and transmission network sides. It therefore makes sense to size a melting furnace system so that the planned liquid metal demand is met, whilst the temporary peak demand is met – where possible – through additional production times.

Maximum monitoring systems are also helpful here, as they ensure that predefined loads are throttled when the power limit is reached. Induction furnace systems with pulse-width-modulated IGBT inverters offer an advantage for this mode of operation, as they maintain a constant power factor (cos phi) even in the partial-load range, whilst still achieving very good electrical efficiency with the parallel resonant circuit inverter. Series resonant circuit inverters also achieve a constant power factor.

With these, however, the high uncompensated furnace current must pass through the entire inverter, leading to additional losses and greater stress on the components. 

The unit price in the electricity supply contract determines the cost per kWh consumed, which is payable by the smelting plant. If this is, for example, 20 cents per kWh and the furnace system consumes 550 kWh/t of liquid metal, the electricity cost per tonne of castings or semi-finished products would be 110 euros. 

In some grids, the electricity tariff costs may also vary depending on the time of day or day of the week. In such cases, it may be advisable to install a holding furnace or a furnace system with two or three crucibles to store molten metal produced during off-peak hours. 

Whether additional costs are payable for the reactive power consumed depends, on the one hand, on the level of reactive power consumption permitted by the energy supplier and, on the other hand, on whether the induction furnace system maintains a constant cos phi of, for example, 0.99 at the inverter input, even under partial load.

If the unit price does not include a low-tariff rate and the demand for molten metal is relatively continuous, it is advisable to avoid installing additional holding furnaces where possible. For example, a 60-metric-tonne holding furnace for iron, designed as a trough induction furnace, has an annual energy requirement of approx. 2 million kWh. Based on the example, at 20 cents per kWh, the energy costs therefore amount to 400,000 euros per year. 

Operating modes of melting furnaces in practice

Just as with driving a car, a significant proportion of the energy consumption when operating an induction melting furnace can be saved simply by skilful operation. This begins with the selection and processing of the feedstock. 

The cost-saving measures can therefore be divided into two categories: optimising the type and quality of the feedstock, and optimising the process sequence. 

Often, little attention is paid to surface impurities, as no difference can be detected by visual inspection alone. The material melts just as well as pure metal. After the melting process, the non-metallic impurities are removed in the form of slag. 

The fact is, however, that these impurities collectively result in poorer coupling of the scrap to the induction field. In the case of oxides, these do not couple at all, which leads to poorer overall efficiency. 

In practice, such insights usually only emerge through the analysis of production data. If irregularities are detected in the process or in product quality, action becomes necessary and the process is systematically investigated. 

Below are some illustrative process scenarios and associated indicative figures for potential energy savings during the melting of a batch, as determined in various iron foundries. 

1 Sand in the ‘ ’ (recycled moulding sand) Filling material

After shaking out the moulds, varying amounts of moulding sand residue remain adhering to the recycled material. If this is not sufficiently blasted off, sand consequently enters the melt. Energy is also required for the formation of slag from the sand. Based on a realistic figure of 25 kg of sand per tonne of iron, this results in an increased energy requirement of 25 kWh/t. 

2 Rusted charge material

Depending on the storage conditions of the scrap used, this may introduce rust (iron oxides) into the crucible. The poor thermal coupling leads to lower power consumption. The iron oxide must be heated to the melting temperature, which is energy-intensive. For the example furnace shown in the table (see Figure 4), this results in additional energy consumption of 30 kWh/t. 

3 Low Dichte der Packung

The packing density of the feedstock also influences energy consumption: the higher the packing density, the lower the energy consumption. 

Measurements taken during actual operation showed an extension of the melting process by approx. 8 % and an increase in energy consumption of approx. 25 kWh/t when the packing density was reduced from 2.0 t/m³ to 1.3 t/m³. 

4) Carbonisation following the melting process

If the carbonising agent is not added at the start of the melting process together with the metallic charge, but is instead introduced into the molten bath only after melting, this results in a significantly higher energy requirement. Practical experience has shown that, when stirred in subsequently, approximately 1 to 2 kWh/kg of carburising agent is required in addition. Assuming a realistic value of 1 % carburising agent per batch, a higher energy requirement of up to 5 to 10 kWh/t of iron is therefore to be expected. 

5) Melting at reduced power density

According to theoretical considerations, operating the furnace at maximum available electrical power – and thus at a high power density – is the most energy-efficient approach. Systematic tests carried out also clearly confirm this. The batch time is shortened, thermal losses are reduced and, as a result, electricity consumption is lowered. If the example furnace from the table below is operated at only 50 % of maximum power, this results in a total additional consumption of 20 kWh/t. 

6) Melting with a sump

The use of medium-frequency technology enables melting without a sump

and the melting of small material in small pieces. Due to the improved

electromagnetic coupling of the solid feedstock (applies only to iron casting materials), 5 % less energy is required in pure batch operation,

as a significantly higher coil efficiency is achieved up to the Curie point. 

7) Store with the lid open

If a furnace is operated with the lid open for longer than necessary, a considerable proportion of the heat escapes into the surrounding environment. This energy must be replenished. The low thermal loss, originally only around 275 kW (for a 15-tonne furnace), then rises to around 600 kW. If we consider a period of 20 minutes, this results in an increased energy requirement of 15 kWh/t.

8) Unrestricted extraction

The extraction rate of the flue gas cleaning system should be adjusted to the furnace’s process stages. If no flue gases need to be extracted, or only a small quantity is produced, the extraction rate can be reduced. 

If the filter system is always operated at full capacity, energy is unnecessarily ‘extracted’ from the furnace. In unfavourable cases, the additional energy consumption can be in the region of 2 %. In the example in the table, this is quantified as 8 kWh/t. 

9) Overheating is not necessary

If, during the final phase of melting in manual mode, the iron is not checked in good time for overheating, the desired or sufficient casting temperature may be exceeded unnecessarily. By avoiding an excessive temperature rise of 50 K, savings of approximately 20 kWh/t can be achieved here. 

When using a digital furnace control system, the final temperature can be maintained with an accuracy of up to 5 K in automatic mode. This prevents unnecessary overheating. 

The table below illustrates the energy figures for the examples listed above, based on a furnace with a capacity of 8,000 kg of cast iron, operated at a maximum power of 7,000 kW. Of course, these individual scenarios never all occur simultaneously. However, the total figure shows that, in the worst-case scenario, the required energy consumption could be exceeded by as much as 35 %. 

If we take the electricity costs initially assumed – 20 cents per kWh – as a basis, the cost of producing one tonne increases by 30 EUR. With an annual production of 50,000 tonnes, this therefore amounts to a total of approximately 1,500,000 EUR in avoidable additional costs. 

As the causes are well understood, energy wastage can be easily avoided by establishing standardised procedures and an optimised system, supported by quality monitoring and process control. 

The same software used to operate the furnace can be expanded to include useful modules such as recipe management or process step confirmation. Depending on the foundry process and melting task, individual targets can be set. 

Retrieval and analysis of digital melting process data

Modern induction furnace systems are equipped with a PLC and a process computer, which stores all key melting process data and assigns it to a specific batch. Complete batch documentation contains the following information/data

Optionally, data such as lid opening times, periods of high and reduced extraction, optimal or delayed material feeding, and optimal or delayed material discharge can also be recorded. 

A batch diagram provides an overview of material feed, temperature and power consumption plotted against the batch duration. For comparison purposes, an ‘ideal batch’ can be stored as an option, which the operator can then aim to achieve by optimising the charging process as much as possible. For an operating mode aimed at continuous improvement in throughput and energy consumption, it is advisable to install a separate computer with its own clear dashboard, thereby separating the optimisation of the operating mode from the visualisation of the furnace system’s sensor data. 

This provides the furnace operator with transparent, real-time information on whether they have operated the furnace in an energy-efficient manner. This also has a motivating effect on the operator, as they can directly recognise the economic impact of their working methods or that of different scrap qualities. 

Furthermore, the analysis of this melting process data can be supported by artificial intelligence to identify patterns of ‘good or poor’ batch results depending on the numerous parameters, and to develop optimisation proposals for charge materials and furnace operation. 

Greater efficiency through data-driven processes

In the foundry sector, the efficient operation of melting furnaces depends heavily on ‘streamlining’ through data analysis. The successful implementation of standard operating procedures (SOPs) plays a crucial role in optimising energy consumption. 

Implementing the ideal melting process:

An ideal melting process is characterised by a continuously rising cumulative energy consumption curve. Longer ‘flat periods’ on this curve indicate sub-optimal melting conditions. However, due to a lack of data transparency, melting furnaces are often operated based on individual operators’ experience and subjective ‘best practices’. The challenge is exacerbated when operators manage multiple furnaces in vast factory halls, making it difficult to gain timely insights. 

Nudging dashboards for operators

Take, for example, a large foundry in Northern Europe that consumes 100 GWh annually. In the search for optimal conditions, studies revealed that, ideally, around 560 kWh should be required to melt one tonne of scrap into liquid iron. However, until recently, the actual average stood at 640 kWh per tonne of melt. To change this, the foundry collaborated with a Danish company that offers IoT-based energy optimisation services specifically for foundries. 

The experts analysed data from several melt batches to determine the ideal operating procedures and organised the information into real-time dashboards for the operators. These dashboards, which are mounted in the operators’ workspace (see Figures 8a and 8b), display the temperature, energy consumption and weight of the furnace. They also provide clear, visual guidance on the ideal times for loading and unloading the furnaces. Thanks to this initiative, average energy consumption was reduced to 570 kWh/t, representing an annual saving of almost 1 million euros for the melting process alone. 

Achieving energy balance

Building on this experience, the iron foundry integrated existing furnace data with MES and ERP systems to time production to coincide with periods of low energy prices. Whilst this may appear to be a cost-cutting strategy, it also serves the broader aim of supporting the stability of the electricity grid through the increased use of renewable energy sources. 

By strategically adjusting the output of electrically powered equipment for short intervals (5–15 minutes), foundries can receive substantial rebates from transmission system operators (TSOs) by participating in the energy balancing process without significantly disrupting production. For foundries using induction furnaces, this presents a great opportunity to utilise readily available data from furnaces, MES and ERP systems to achieve sustainability, efficiency and a lower carbon footprint.

Bibliography:

1. Trauzeddel, D. (2018) Special Applications of Inductive Melting and Casting Technology. Areas of Application | Plant Engineering | Process Technology. Vulkan Verlag.
2. Dötsch, E. (2019) Inductive Melting and Holding. Fundamentals | Plant Design | Process Engineering. Vulkan Verlag.
3. Donsbach, F.; Schmitz, W.; Trauzeddel, D. (2018) OTTO JUNKER Handbook: Safe and Energy-Efficient Melting in MF Crucible Furnaces. Self-published.
4. Donsbach, F.; Renftle, G.; Niklaus, S. (2021) The melting of scrap with low packing density in a medium-frequency induction crucible furnace. Technical article.
5. OTTO JUNKER Academy
6. Photos: OTTO JUNKER Archive
7. Photos: INDUGA Archive
8. Init Group

Authors:  

Frank Donsbach – OTTO JUNKER GmbH, D-52152 Simmerath-Lammersdorf
Matias Mohedano Rodriguez – OTTO JUNKER GmbH, D-52152 Simmerath-Lammersdorf
Ulrich Nordt – OTTO JUNKER GmbH, D-52152 Simmerath-Lammersdorf
Peter Koldig Hansen, Init Inuatek A/S, DK-1432 Copenhagen