Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-08T10:32:00.356Z Has data issue: false hasContentIssue false

Investigation of sinter plant production rate and RDI by neural networks

Published online by Cambridge University Press:  06 June 2005

Get access

Abstract

Data from the Rautaruukki Raahe sinter plant were analyzed with feed-forward neural networks. The resulting models were used to investigate and optimize the sinter plant production rate and the reduction degradation index (RDI) that is an important sinter quality indicator for small blast furnaces. Especially, the effects of controllable parameters such as the chemical composition of sinter, physical conditions of raw materials and factors reflecting the sintering event were studied.

Type
Research Article
Copyright
© La Revue de Métallurgie, 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)