Title: Prediction of optimal stability states in inward-turning operation using genetic algorithms

Authors: K. Rama Kotaiah, J. Srinivas, K.J. Babu

Addresses: Department of Industrial and Production Engineering, K.L. University, Vaddeswaram, Guntur (Dist), Andhra Pradesh, 522502, India. ' Department of Mechanical Engineering, Chaitanya Engineering College, Visakhapatnam, Andhra Pradesh, India. ' K.L. University, Vaddeswaram, Guntur (Dist), Andhra Pradesh, 522502, India

Abstract: This paper proposes a neural network-based optimisation scheme for predicting localised stable cutting states in inward turning operation. A set of cutting experiments are performed in inward orthogonal turning operation. The cutting forces and critical chatter locations are predicted as a function of operating variables including tool overhang length. Radial basis function neural network are employed to develop the generalisation models. Optimum cutting parameters are predicted from the model using binary-coded genetic algorithms. Results are illustrated with the data corresponding to four work materials operated over a HSS tool.

Keywords: critical chatter length; tool overhang; RBF neural networks; optimum parameters; orthogonal turning; optimisation; stable cutting states; cutting forces; genetic algorithms; HSS tooling; high speed steel.

DOI: 10.1504/IJMMM.2010.033066

International Journal of Machining and Machinability of Materials, 2010 Vol.7 No.3/4, pp.193 - 207

Published online: 07 May 2010 *

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