Optimization of End Milling Process Parameters on Mild Steel Grade EN3B using Genetic Algorithm

Abstract

This project aims to reduce the surface roughness and improve the MRR rate of taken mild steel
material. Now a day’s quality and productivity plays main roles in the market. Optimization should be required for all types of
machining process to improve the desired quality of the product. The Main aim of this project is to reduce tool wear, increase
tool life, MRR rate and improve surface finish of the product. In the end milling process, it is considered to be three main
cutting parameters cutting speed, feed and depth of cut. The optimization of cutting parameters according to the raw material
and cutting tool to get higher surface finish. There are various optimization techniques are available in this project Genetic
Algorithm is used. Minitab is used for forming regression equations for L27 arrays table values and optimizing the input
parameters values by using GA. Mild Steel BS 970 Grade EN3B is the raw material used and the appropriate cutting tool is
TIN coated tungsten carbide. The MCV 650 Vertical Machining Centre is used to making end milling process on the work piece and the obtained results shows that the optimized parameters are efficient to machining and give better surface finish.