Lirong Zhou

One way to manage the modern challenges of global resource depletion and climate change is to reduce energy consumption. The use stage of machines in manufacturing operations consumes the majority of energy and brings serious emissions over a machine's life cycle. With this in mind, a multi-objective cutting parameter optimization model is proposed, focusing on minimizing the process time and energy consumption per unit of removed material. Constraint conditions, such as the processing capacity of the machine tool, the tool life, the surface roughness of the part, and wasted ploughing energy are considered. A genetic algorithm is used to solve the optimization model and the effects of the parameters on the energy consumption of the machine are discussed. To verify the proposed method, experiments were designed for an end milling operation, using Taguchi design principles.