SUNSHINE

The SUNSHINE project is aimed at an early detection of defects and to identify, with the support of in-line sensors and models, incorrect process conditions which lead to shape or surface quality problems in the as-cast products, that may also lead to problems during rolling.

Project information

Project duration

-

Project funder

EU Research Fund for Coal and Steel (RFCS)

Funding amount

103 000 EUR

Project coordinator

University of Oulu

Unit and faculty

Process Metallurgy
Faculty of Technology

Contact information

Contact person

Project description

Non-uniform in-mould solidification in long and flat products can lead to rhomboidity, bulging and surface defects affecting the as-cast quality and the continuous production flow up to rolling, especially when aiming at improved energy efficiency by hot direct charging of billets or slabs to reheating furnaces. The occurrence of defects will be predicted by means of machine learning and other AI tools. Appropriate countermeasures and suitable operating conditions for defect avoidance will be defined and provided via alerts and recommendations will be developed and applied in industrial campaigns to evaluate the performance of the developed solutions for defect avoidance.

Total budget

3.7 MEUR

Partners

Rina Consulting CSM, Sidenor I+D, Oulun yliopisto, Feralpi Siderurgica, Acciaierie d’Italia, VDEH-BFI, Dillinger

Additional information

Project homepage: https://sunshine-project.eu/