Objective
Changing technical and economic constraints on blast furnace operation require that flexible blast furnace control methods be adopted in order to ensure stability of the required iron quality and quantity under any conditions. The objectives of this research are to investigate different approaches which are claimed to surpass control methods currently in use: application of model-based control strategies for improved regulation of hot metal qualities, application of automatic knowledge acquisition methods for ensuring that supervising expert systems are kept up to date, and application of artificial neural networks for data compaction and process state classification and prediction.
Topic(s)
Call for proposal
Data not availableFunding Scheme
CSC - Cost-sharing contractsCoordinator
40237 Düsseldorf
Germany