Year 2007
Suvi Rannantie

Implementation, Analysis and GUI Design of Statistical Batch Model for Peirce Smith Converters

Modelling of copper converting process has usually been based on static models in which the mathematical description of the process is built on mass and energy balances and thermodynamic equilibrium calculations. However these models require reliable empirical information and trial-and-error calculations. Difficult conditions, such as high temperature, dust and exhaust gases perturb measurements. Furthermore, it is difficult to evaluate model-related state variables, because the precise composition of batch materials is not analysed continuously.

The aim of the work was to examine the statistical batch model developed for the Peirce Smith converters in the Boliden Harjavalta copper smelter, and to design a graphical user interface for the model. The model gives the amount and the composition of matte and slag as well as blowing times, and controls the operations towards the optimal iron-silica ratio and smooth temperature trend. Calculation is based on interrelation of various components and mass balance in the system. The logic of the model has been embedded into macros which read and update data in the database and perform calculations automatically.

The theory part deals with PS converter models in general with some application examples. The experimental part presents the copper production process and the automation system at Harjavalta site and describes the converter measurements. Then the operating principle of the calculation model and its GUI are introduced. Finally, validity and usability of the model are evaluated with quantitative and qualitative methods by comparing model suggestions with measured data before and after taking the model into use.

The results confirm that, on average, less silica flux is fed into the converter at present and that the model works correctly, giving reliable results in slag blow. The converting capacity has increased in slag blow steps but also during the copper blow. The financial calculations have shown that the model produces considerable savings.

This info last modified 27 Apr 2024 by Jerri Kämpe-Hellenius