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Neural Network Modeling for Face Milling Operation

Milling operation is one of the important manufacturing processes in production industry. Study and analysis of milling process parameters such as spindle speed, feed rate and depth of cut are important for process planning engineers. The responses are temperature, surface roughness, machining time, feed force, thrust force and cutting force. The main aim of this study is to find out the effects of these parameters in face milling operation on Monel k 400 work piece materials with tungsten carbide insert. The theoretical investigation is carried out with neural network modelling and the 3-1-6 structure neural network models are considered. Developed neural network models show best agreement with experimental values. For same type of operation, result of these experiments shall be useful for future research purpose.