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Final report on Contract No. 7210-EA/152, 424, 330, 902; 1 July 1996 to 30 June 1999

The aim of the project was to acquire further knowledge to improve strip flatness control particularly by making better use of actuator control ranges. The research activities were concentrated mainly upon:

- The application of artificial neural network techniques in strip flatness prediction during cold rolling.
- The development and validation of a new mathematical model for determining strip flatness in cold rolling.
- The calculation of strip profile and flatness in different types of cluster mills.
- The investigation of the effect of different control actuators upon strip flatness.

An artificial neural network strip flatness simulator has been developed by CSM. Good results have been obtained in terms of capability to predict the strip flatness properties at the exit of the roll gap, as a function of strip geometry and rolling parameters. IRSID developed a reference numerical model for flatness of cold rolled strips, which can be used to preset cold rolling mills and also to control strip flatness during rolling. The new model brings a significant gain of accuracy compared to models in current industrial use. The calculations of strip flatness for different types of cold rolling mills, particularly for cluster mills, were carried out with MEFOS's program CLUSTER. For 12-high mills, a comparison between measured flatness and the flatness calculated with CLUSTER shows that the shape of the flatness is correct but that the values for the calculated flatness are exaggerated. gerated.

Additional information

Authors: No authors specified, BFI, Düssseldorf (DE)
Bibliographic Reference: EUR 20102 EN (2002), pp.126. Euro:19:00
Availability: EUR-OP reference: KI-NA-20102-EN-S. Available from EUR-OP sales agents. URL:
ISBN: ISBN: 92-894-3153-9
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