Fig. 9: User screen of the rule-based system

Fig. 8: Through-heating measurement with trial ingot

Fig. 7: Calculated temperature distribution (left) and tension distribution (right) in heating/austenitisation of forging ingots
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New processes and instruments II

Simulation models for design and optimisation (CFD, Comsol)

It is possible to increase the convective heat influx selectively via the flow control and furnace atmosphere. This mostly occurs by increasing the average flow rate. Installing circulation blowers to this end, which have high material quality requirements, was often not economically feasible. In a newly developed process, the impulse flows of the combustion gases, injected directly into the furnace through the burner, are the single driving force of the atmosphere circulation. To achieve a targeted increase in impulse flows, two new heating processes were developed.

These developments were based on studies of combustion technology, flow conditions and heat transfer with the aid of numerical simulation calculations (Fig. 6) and technical laboratory trials. This new development can help improve the efficiency of several heating processes. It is important to know the details of the properties of the materials used during the heating and heat treatment in order to attain the required product quality and energy efficiency. As a rule, however, these types of measurements cannot be conducted during the process. A newly developed FEM simulation model is able to detail the temperature, the thermal, elastic, plastic, transformation based and transformation induced plastic strain and stress states as well as the diffusion-controlled or non-diffusion phase transformation of the material used throughout all steps of the heating and heat treatment process. The simulation model is currently being used for developing, designing and optimising a new combined plant presently under construction. This plant consists of cooling sections, continuous furnace and hardening basin for heat treatment of seamless rolled rings straight from the rolling heat. The fuel savings per tonne heat treated material is expected to be approx. 18 Nm³ of natural gas, leading to a reduction in CO2 emissions of approx. 33.3 kg. At a planned material throughput of approx. 26,500 tonnes of the material used annually, this corresponds to annual savings of about 477,000 Nm³ of natural gas and a reduction in CO2 emissions of 882 tonnes per year. Another present application utilises the simulation model to optimise the austenitisation of forging ingots in batch furnaces with respect to furnace operation method and furnace loading. This minimises the tension and increases the energy efficiency during heating and transition of the forging ingots (Fig. 7).

Batch furnace model

Based on simulation calculations, the batch furnace model can optimise furnace cycles according to exposure time and energy input. This type of model can be used offline as an educational and/or planning system as well as online for process monitoring and drawing time purposes. This enables the development of optimal heating curves and furnace utilisation. Thus, it is possible to improve the operational planning and increase the throughput. The system is completely implemented within the ORACLE database and has a pleasant graphical user interface.

Model-based furnace operation

The model-based furnace operation has a wide range of applications, even for operators of small-scale plants. The different goals of the optimisation process can be defined, e.g. minimised energy use, equal through-heating or reduction of scale and tension effects. This relieves the operating personnel of carrying out routine tasks and makes possible optimum furnace operation even under irregular process conditions. The most significant improvements compared to “manual” operation are the automated process control adjustment to variations in the process gas supply or different material flows as well as the reaction to interruptions in the production process. The resulting cost savings and quality improvements soon lead to economic advantages. Several system operators have already put this furnace control system to successful use. The process and systems knowledge, which in part has been accumulated over decades, is often entirely in the hands of a few highly qualified employees. Rule-based systems can be a means of saving and finding regular use of this store of knowledge. These systems can be used to control, document and optimise processes. In some applications, rule-based systems are given precedence over model-based systems. This applies in particular if it is difficult to depict process control requirements analytically or if they cannot be depicted at all. At present, this solution is used in furnace operation systems and sintering plants.


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