Development of an integrative plant, process and quality supervisory system at continuous casting by the intelligent combination of sensors, data analysis & decision support techniques (SUPSYSCC) : final report

SUPSYSCC project has been focused on the development of concepts and methods for an integrated plant, process and quality supervisory system for continuous casting by means of the intelligent analysis of results from process and quality measurement devices combined with higher level supervisory tools like decision support systems. The consortium used several innovative approaches to measure and model the process and quality parameters of different casting products. BFI applied methods for checking the plausibility of data, the analysis of relationships between process and plant parameters and product quality features, and the estimation of product features by data-based models. Results were implemented into online applicable tools and validated under operational conditions. ArcelorMittal developed a system for the on-line monitoring of the continuous caster motors paying special attention to the mould oscillators and the line drive system. Lucchini and CSM developed a supervisory system for square billet production of microalloyed resulphurised steels. The system was useful to improve product quality by giving the production staff prompt reporting about process deviations which helped improve plant and process set-up. Aalto developed soft-sensors for predicting the billet surface quality which were integrated into an on-line supervisory system able to control the secondary cooling performance. Tools for secondary cooling status control systems based on PQ curves and solidification process characterisation based on imageprocessing methods were developed by Gerdau. Riva developed new tools for the quality control of the production of blooms and for the calculation of the Jominy profile and the steel hardenability.