Process Optimization for Milling Operation - A Review | Original Article
Milling is the machining process which improves dimensional accuracy and surface quality. In this present review work input parameters are cutting speed, feed rate, depth of cut, coolant flow, tool size, width of cut, nose radius, tool diameter, and radial rake angle. Techniques used to optimize process parameters are Taguchi optimization technique with orthogonal array used for design of experiment, response surface methodology and artificial neural network. Response surface methodology (RSM) approach is the procedure for determining the relationship between various process parameters with the various machining criteria and exploring the effect of these process parameters on the coupled responses. An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain processes information. This study provides a review on optimization of machine parameters by different techniques.