Optimization of the high-speed CNC milling process using two-phase parameter design strategy by the Taguchi methods

High speed, high quality and short delivery are the development trend of the manufacturing industry. In this paper, the Taguchi dynamic characteristic theory was used coupled with proposed ideal function models under a two-phase optimization strategy. The main objective of this work is to develop optimized machining parameters in the high-speed milling process with the characteristics of high machining efficiency and geometrical accuracy, and wide applications. The experimental results showed that the machining time can be effectively reduced using the designed optimal parameters obtained from the first phase of the strategy. The process variance was only 63.96% of the initial conditions, and the robustness of the process was increased 1.56 times. The control factors having the most influences on the machining time and the robustness of the CNC milling process in order of importance were identified as cutting speed, number of teeth, and feed per tooth. The dimensional relationship between the input and output of the milling process under the first-phase optimized conditions was derived as Y = 1.001 090M. Therefore, according to this model, final adjustment to the input programmed dimension can be made in phase two to obtain the ideal machining accuracy.