The research reported in this paper proposes an Advanced Process Control system, denoted "i.Process | Steel -RHF", oriented to energy efficiency improvement in a pusher type billets reheating furnace located in an Italian steel plant. A tailored control method based on a two-layer Model Predictive Control strategy has been created that involves cooperating modules. Different types of linear models have been combined and an overall furnace global linear model has been developed and included in the controller formulation. The developed controller allows handling all furnace conditions, guaranteeing the fulfillment of the defined specifications. The reliability of the proposed approach has been tested through significant simulation scenarios. The controller has been installed on the considered real plant, replacing local standalone controllers manually conducted by plant operators. Very satisfactory field results have been achieved, both on process control and energy efficiency improvement. Optimized trade-offs between energy saving, environmental impact decreasing, product quality improvement and production maximization have been guaranteed. Consequently, Italian energy efficiency certificates have been obtained. The formulated steel industry reheating furnaces control method has been patented.

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This study proposes a data analysis and modelization method for the rolling mill process of billets in steel plants. By exploiting rolling mill signals and advanced data processing algorithms, a reliable billet tracking system is designed, which tracks each workpiece from the furnace entrance to the rolling mill stands’ exit area. Based on the stored information, two problems are addressed: the data analysis of the temperature sensors (a thermal imaging camera and pyrometers) and the current that is related to the rolling mill stands’ absorption, and subsequently, a mathematical modelization of the billets’ temperature along their path in the rolling mill is produced. The data analysis suggested that we should perform hardware modifications: the thermal imaging camera was repositioned to avoid the effect of scale formation on the temperature measurements. The modelization phase provided the basis for future control and/or diagnosis applications that will exploit a temperature decay model.

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