Preset generation for a steel tandem cold mill by means of a neural network tool

This paper traces the development of a software tool, based on a combination of artificial neural networks (ANN) and a few process equations, aiming to serve as a backup operation instrument in the reference generation for the real-time controllers of a steel tandem cold mill. By emulating the mathematical model responsible for generating the presets under normal operational conditions, the system works as an option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based on a lookup table), which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that, by this instrument, it is possible to achieve virtually all the presets needed by this kind of process. The text characterizes the problem, relates the investigated options to solve it, justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results.