Objective The project objective is to improve end-point analysis and temperature control in the BOS process through the application of neural networks to current computer models for primary charge balancing, sub-lance end-blow control and end-point analysis prediction. Conventional statistical process models based on thermal or physical logic are limited in their ability to account for interrelated variables whose influence is not well understood. Neural networks with their self-learning capabilities are expected to be more accurate, faster and more precise. Programme(s) ECSC-STEEL C - Medium-term guidelines for the ECSC steel RTD programme of research and pilot/demonstration projects, 1996-2002 Topic(s) C1 - Primary steelmaking Call for proposal Data not available Funding Scheme CSC - Cost-sharing contracts Coordinator British Steel plc EU contribution No data Address Moorgate S60 3AR Rotherham United Kingdom See on map Total cost No data Participants (2) Sort alphabetically Sort by EU Contribution Expand all Collapse all INSTITUT FÜR BERGWERKS- UND HÜTTENMASCHINENKUNDE DER RWTH AACHEN Germany EU contribution No data Address Wüllnerstrasse, 2 52056 AACHEN See on map Total cost No data KONINKLIJKE HOOGOVENS Netherlands EU contribution No data Address 1970 CA IJMUIDEN See on map Total cost No data
