Pickling is a long-standing process which is of interest for most of the production of steel strips. Nevertheless its control is far from being satisfactory what result in significant productivity losses and sometimes in limited quality.
The reason for those problems is to be found in the quite difficult evaluation of the pickling state. Indeed on one hand it is evident that high strip quality requires complete elimination of the oxide at the strip surface; so the under-pickling cannot be tolerated. What is less obvious on the other hand is that over-pickling i.e. attack of the iron by the pickling solution can also represent a serious problem in terms of quality and productivity losses. However these last problems are well actual and expensive for the steel industry.
The objective of this RFCS project was to identify the conditions where under- and over-pickling take place. So the optimised window wre highest productivity and quality are achieved can be determined.
This objective has been attained in a stepwise approach:
- adaptation or development of sensors as it appears that precise knowledge of the state of pickling surface is the obligatory first step. These sensors have been developed in laboratory and then validated in continuous conditions. They encompass all the important aspects of pickling process: state of pickled surface, pickling process itself as well as aggressiveness of the pickling solution;
- monitoring, detecting and understanding the conditions where under- or over-pickling take place. This has been attained by means of advanced statistical analysis and by modelling works;
- proposing solutions in terms of process parameters and pickling operation. These improvements address both regular grades and the qualities which are reputed critical for over-pickling;
- validating the solution in plant tests and quantifying the benefits of the improved procedure.