Optimization of hot rolling parameters

Hot deformation parameters such as pass reduction and final rolling temperature strongly affect the final microstructure and consequently the mechanical properties of the final product. Most hot rolling models predict microstructure and properties for a given hot rolling schedule and on their own could be used to redesign or improve the deformation schedules. Here, an optimization algorithm which is based in the gradient method is used to design thermomechanical sequences when a specific grain sized is desired. The optimization module is coupled to a metallurgical model which predicts the microstructural evolution during the hot rolling process and the austenite/ferrite transformation during subsequent cooling. In previous work, the metallurgical model was described and validated for a plain carbon and a Nb microalloyed steel. Moreover, it was shown that the ensemble of the metallurgical model and the optimization module is able to generate 'optimized' rolling schedules which lead to the predefined mechanical properties in terms of grain size. In this work, the software has been used to optimize the strain and the number of rolling passes in order to obtain the minimum austenite grain size prior to transformation for a plain carbon steel. The applicability of classical optimization models, based on the gradient method, to hot rolling operations, is discussed.