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

Abstract

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, roll wear, working forces, and torques. Furthermore, due to the sequential nature of the rolling process, a design of any number of passes is closely interrelated with all other passes in the process. This complexity makes it challenging to find optimal design solutions that strike a balance between conflicting goals and constraints. In this article, a new optimized solution search strategy based on a desirability function is offered to address 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 proposed method provides integrated optimization of the process by ensuring information flow between the passes and can also be applied to other sequential processes with some modifications. The developed method and solution search strategy are illustrated and validated through a case study. The findings of the case study are compared to three distinct pass designs used in industrial power plants. The results show significant energy savings, lower turning moments, and reduced radial forces compared to the reference designs.