Composition-Processing-Property Correlation of Cold-Rolled IF Steel Sheets Using Neural Network

Artificial neural network (ANN) models have been developed to establish relationships between the mechanical properties of the cold-rolled sheets of interstitial free (IF) as a function of the chemical composition of the steel, the rolling and the batch annealing parameters. The mechanical properties studied include yield and [image omitted]. The technology of rolling mill automation necessarily embraces a broad spectrum of interests, ranging from fundamental process analysis to the solution of special control-theoretic problems. Determining the relationship between various compositional and processing parameters and the mechanical properties of cold-rolled sheets is important but not easy to establish. The complex and highly nonlinear interactions between the variables make the system difficult to assess from the prediction point of view. ANN model is found to be capable of developing the inherent relationship between the variables and could be successfully used to develop better understanding on the metallurgical principles of cold rolled IF steel.