FEA Analysis for the Optimization of an Extrusion Die

Abstract

The process of extrusion plays a vital role in the production process of different parts in various environments. Even though there is lot of variations in the production of parts during extrusion with conventional processes to the latest automation in the manufacturing. There is a need to develop different die designs by varying input processes variables for the extrusion process in an optimum manner. The purpose of the present paper is to determine the optimal cold forward extrusion process variables at minimum Extrusion force. The present work deals with the different approaches, one is a statistical method, i.e., Taguchi orthogonal array and the another one is an evolutionary algorithm, i.e., Particle Swarm Optimization in order to determine optimal values of logarithmic strain, die angle and friction coefficient with a purpose to find minimum Extrusion force and the obtained results are compared with those in existing literature. The obtained results lead to the lower energy consumption, better tool life, better formability of the work material, and the better quality of the finished extruded part. With the optimal values obtained in both the techniques, a three dimensional model is developed and analysis is carried out on ANSYS platform. Based on the ANSYS results optimal values or the extrusion process variables are determined.

Keywords: Cold forward extrusion, extrusion force model, die angle, logarithmic strain, frictional coefficient, Taguchi OA, Particle swarm optimization