Prediction of optimal stability states in inward-turning operation using genetic algorithms
by K. Rama Kotaiah, J. Srinivas, K.J. Babu
International Journal of Machining and Machinability of Materials (IJMMM), Vol. 7, No. 3/4, 2010

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.

Online publication date: Fri, 07-May-2010

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