Interactive Multiobjective Optimization for the Hot Rolling Process

In this paper, multi-objective optimization is applied to the hot rolling process. It is modeled mostly using first principle models considering, for instance, the mass balance (or mass flow rate), the tensions in the material, the power requirements, the thermal field, and the microstructure of the material. Two optimization formulations are considered. In the first case, both the grain size and the power consumption in the rolling process are minimized. It is shown that the result from a single-objective optimization formulation, i.e., where only one of the two objectives are considered, yields control schedules with poor performance for the other objective. Furthermore, the differences between optimal control schedules for different objectives are compared and analyzed. The second case is a design optimization problem where the optimal positioning of cooling pipes is considered. This study shows how the MOO framework can be used to systematically choose a good cooling pipe setup. The two studies shows that MOO can be a helpful tool when designing and running hot rolling processes. Furthermore, navigation among the Pareto optimal solutions is very useful when the user wants to learn how the control variables interact with the process.