Abstrato

Neural Networks Based Approach for Machining and Geometric Parameters optimization of a CNC End Milling

Nilesh Pohokar , Lalit Bhuyar

To select the optimum parameters it is necessary to determine them at first for the given machining situation. There are several techniques available to determine the optimum values of these parameters, in this paper machining parameters, cutting speed, feed, depth of cut, and one geometric parameter rake angle are considered for optimization. The neural networks were developed for predicting the results theoretically. To validate the results experimentally trials are then carried out a CNC milling using HSS tool by continuous running condition under dry run on the AISI 1040 MS plate of 140 X 120 X 10 mm workpiece. The predicted results match 90 % including the residuals. Thus proves the neural network is used for optimization of geometric and machining parameters.