An improved wolf pack algorithm for sustainable machining parameter optimization

Machining parameter is one of the influence factors of energy consumption in numerical control machining process. In this paper, spindle speed, feedrate, cutting depth and cutting width are selected as the machining parameters to be optimized. The artificial neural network is used to establish an energy consumption model to characterize the relationship between energy consumption and the machining parameters. Based on the energy consumption model, an improved wolf pack algorithm is presented to search for optimal machining parameters to minimize the energy consumed in machining process. The method has been tested and verified based on experimental data. The experimental results show that this optimization method is very effective for the sustainable machining parameter optimization.