OPTIMIZATION OF CUTTING PARAMETER USING NEURAL NETWORK

Abstract

Neural networks are now of major interest as when it is connected to computer it mimics the brain and bombard people, with much more informations. These have shown promise for solving many combinatorial optimization problems. Neural network have become increasingly popular because of their speedy computation and also provide close optimal solution which are sometimes not possible by other computation methods. Neural networks offer several advantages over the more, conventional procedure and symbolic approaches to computing. The most frequently cited of these are their ability to develop a generalized solution to a problem from a set of examples and to continue development and adopt to changing circumstances with exposure of new variation of problem. Problems where the time required to generate solution is critical, mark another important area. Optiration of cutting parameters represents a key component in machining process penning. Neural network produces solution in a fraction of second irrespective of the complexity of the problem. In this dissertation, a neural network model has been developed optimizing machining parameters in case of turning operation.