Indian Journal of Science and Technology
DOI: 10.17485/ijst/2015/v8i22/79097
Year: 2015, Volume: 8, Issue: 22, Pages: 1-4
Original Article
T. Deepan Barathi Kannan1* , G. Rajesh Kannan2 , M. Umar3 and S. Ashok Kumar4
1 Department of Production Engineering, NIT-Trichy, Tiruchirappalli, Tamil Nadu – 620015, India; [email protected]
2 Department of Mechanical Engineering, M.A.M. School of Engineering, Trichy – 621 105, Tamil Nadu, India; raj. [email protected]
3 Department of Mechanical Engineering, C.S.I. College of Engineering-ketti, The Nilgiris, Tamilnadu – 643 215, India; [email protected]
4 Department of Industrial Engineering, PSG College of Technology, Coimbatore – 641004, Tamil Nadu, India; [email protected]
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.
Keywords: ANN, Brass, Drilling, GA, Ovality, Surface Roughness
Subscribe now for latest articles and news.
