Optimization and Modelling of Machining Parameters in End Milling Operation Using Box-Behnken Technique

Machining is a costly process; it includes the cost of workpiece material, tool, energy consumption (by machine), labour cost, etc. so, it should be done very carefully because an error in a single parameter may cause the rejection of the product. To overcome this problem, optimization and prediction of the parameter are the necessities of the process. This paper deals with the optimization and prediction of the milling forces of aluminium alloy 7075, which have been done through the RSM technique. The three process parameters—feed rate, depth of cut, and velocity—were considered during this experiment. The experiments have been done to establish an empirical relationship between process parameters and response parameters. The prediction of forces has been made through an empirical model or regression model in the X, Y, and Z directions. Further, a comparison has been made between the experimental and predicted force values. The average error in prediction and experimental forces is approximately 6%.