ANN approach for modelling parameters in drilling operation

Abstract

Drilling is one of the most widely used machining operations in industries. The general problems that occur in drilling are poor surface roughness and ovality. In this article efforts are made to reduce the above said problems while drilling 6mm hole in brass plate with the help of Artificial Neural Network (ANN) modelling technique and Genetic Algorithm (GA) optimization technique. It was found that proper parameters selection plays a vital role in reducing the surface roughness and ovality errors. Brass plates are widely used in manufacturing of couplings, while manufacturing it, there is need to make holes of diameter 6mm. Thus the results found in this work will be helpful for coupling manufacturing industries to improve the quality of drilled holes.