A Desirability-Based Solution Search Method for Sequential Optimization of the Hot Rolling Process

Abstract

Although it is an old technique, research on the hot rolling process maintains its importance because of its widespread usage in steel production and its requirement for a vast amount of resources, especially energy. The roll pass design of the hot rolling process considerably affects many operational parameters such as energy requirement, wear of the rolls, working forces, and torques. Furthermore, due to the sequential nature of the rolling process, a design of any number of passes is strictly interrelated with all other passes in the process. This makes it very involved to find optimum design solutions that allow for the compromise between conflicting goals and restrictions. In this paper, a new optimized solution search strategy based on a desirability function is offered to deal with the sequential characteristics of the roll pass design. A novel optimization method utilizing response surfaces and the proposed solution search strategy is presented to reduce the shaping energy of the overall process while minimizing turning moments and radial forces on rolls during the rough rolling process. The method and solution search strategy developed are illustrated and validated via a case study. Comparing the case study's findings to three distinct pass designs used in industrial power plants, it was discovered that significant energy savings, low turning moments, and reduced radial forces had been made compared to the reference designs.