A fast optimization approach for multipass wire drawing processes based on the analytical model

Abstract

A fast optimization approach is described for design optimization of the multipass wire drawing process with genetic algorithm. The analytical models for calculation of the drawing force, power consumption, and the temperature rise are addressed by considering the real steel wire drawing condition, and a new die wear factor indicating die wear and life is established based on the slab method. The genetic algorithm has been implemented to build up a single objective optimizer for minimizing the total power consumption and a multiobjective optimizer for minimizing both the total power consumption and temperature rise under several deliberate design constraints. The numerical examples show that the multiobjective optimizer presents better performance in finding the optimal solution, compared with the single objective optimizer. Different types of optimization methods especially designed for real demands are demonstrated under multiobjective optimization set. Compared with a reference design, it indicates that significant improvements in the total power consumption and the control of maximum temperature, delta factor, and die life have been achieved by the optimization. It has been proved that the optimizer for the multipass wire drawing processes is highly effective and efficient.