Minimization of Springback in Seamless Tube Cold Drawing Process Using Advanced Optimization Algorithms

Abstract

Seamless tube manufacturing is mostly done using cold drawing process. Apart from scores on tube, chattering, eccentricity, springback is also one of the severe problems induced in seamless tube drawing process. It is because of the elastic energy stored in the tubes during forming process. This paper uses Taguchi method of experimentation for optimizing process parameters viz. die semi angle, land width and drawing speed to minimize springback. The regression model of Taguchi method using Minitab 17 is employed in Matlab as an input for further advanced optimization algorithms viz. particle swarm optimization (PSO), simulated annealing (SA) and genetic algorithm (GA). The results of these algorithms show that the process parameter values of 15° die semi angle, 10 mm land width and 8 m/min drawing speed give least springback with almost 10.5% improvement over Taguchi results.