Speaker
Description
Given the sheer volume of resources and energy used in smelters around the world, the optimization potential of simulation and modeling-based efficiency measures is huge.
However, simulations require representative input data in order to work properly. In other words: simulations can only be as good as the data they are built on. In addition to the detailed model the best possible measurement data from the up- and downstream material flows are essential. For this reason, new sensors and analysis techniques are constantly being established to improve the data basis. But despite all efforts, there are still a few blind spots.
As the expression "make the slag and the steel makes itself" suggests, the slag has a considerable influence on the quality of the steel produced. But the chemical composition of the slags could only be included post-mortem into the models since the analysis time was too long due to sample preparation times. Various quite limited workarounds have been established to include some kind of slag data into the model in real time. But e.g. the smell or the color appearance of the slag bath is quite unprecise.
The alternative is Laser OES technology which works analogously to Spark OES is capable of measuring the chemical composition on up to 1000 surface spots per second. That allows homogenization of data instead of physical samples. Thus, even hot slag can be chemically analyzed in 1-2 minutes and the precise values can be incorporated into the simulation.
With the precise slag analyses available in real time, the models and simulations can be optimized further and raised to a completely new level. The positive impact of simulations can also be increased even further. This not only makes economic sense, but is also smart in regards of Industry 4.0.