Application of genetic algorithms to optimization of rolling schedules based on damage mechanics

Abstract

It is well known that tandem cold rolling is one of the most widely used processes in the manufacture of various sheet products with high accuracy and production rate. This paper deals with an optimization problem for tandem cold rolling. A genetic algorithm is developed to optimize the reduction schedules from the power consumption and damage evolution points of view. Damage-coupled finite element simulations are employed to determine the damage objective function. The dominant parameters of the rolling process are calculated using an experimental–analytical model, obtained from an industrial tandem rolling mill. Generally, in rolling process damage and power have conflicting natures and none of them can be improved without degrading the other. In this paper, in the first step, power and damage are optimized independently and some reduction schedules are introduced to minimize power consumption or damage evolution during the process and the results are compared with the experimental observations. Afterwards power and damage are optimized simultaneously by defining a multi-objective function and employing the Pareto optimality; a set of optimized reduction schedules are provided to optimize the power and damage based on the preference ordering of the decision makers in tandem mill. This multi-objective optimization enables the mill operators to select the most appropriate optimized schedule according to the mill necessities. Finally the optimal schedules are numerically simulated to investigate the efficiency of the damage optimized schedule.