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ORGANIZER;CN=ESTAD 2023:mailto:info@metec-estad.com
LOCATION:Room 18a
SUMMARY:Development of prediction models for steelmaking process and their on-line applications with through process approach
DESCRIPTION:In modern steel productions the necessity to improve process performances became more and more a relevant target for both improvement of single product production in terms of quality and costs and also to enable variation in production scheduling thanks a flexible assessment of operating practices adopted.
To enable the improvement on this approach a deeper understanding of the process phenomena occurring during the production is necessary to be able to understand which actions are necessary to improve the effectiveness of the reactions and heat transfer.
For this reason the approach followed in Feralpi included different steps passing through development of modeling for the different process phases, implementing these modelling in off-line prediction model and online process control and including capability to describe process guidelines as support to the operators during the production.
In particular these have been realized for the three main process steps EAF, LF and Continuous casting in order to be able to modify operating practices thanks to prediction model and to support the on-line process control thanks to derived trends KPI’s, in particular for both sites of Feralpi Siderurgica and Acciaierie di Calvisano.
Furthermore a through process view is necessary to respect the process/quality constraints aiming at improvement of performances and productivity.
Acciaierie di Calvisano and Feralpi Siderurgica strongly address its productions developments with adoption of new technologies and solutions Industry 4.0 for data analysis and process control also supported by RFCS funding scheme in the funding R&D projects.
With the contribution of the R&D department, process technology, production areas and research partners, in Feralpi predictive mathematical models have been created for production phases and whole steelmaking process. 
This has been done internally in order to be able to better setup the optimal operating practices for each process phases.
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DTSTART:20230615T090000
DTEND:20230615T092000
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