A cutting parameter energy-saving optimization method considering tool wear for multi-feature parts batch processing

Cutting parameters and tool wear both have significant influence on energy consumption in the processing. In a multi-feature parts batch processing, tool wear values are continuously increasing with the proceeding of processing, leading to a higher energy consumption. To reduce the wear speed, cutting parameters should be continuously adjusted according to different states of tool wear during batch processing. However, current cutting parameter optimization studies only focus on one specific workpiece and the tool wear is seldom considered in the batch processing. To fill this research gap, a cutting parameter energy-saving optimization method considering tool wear for multi-feature parts batch processing was proposed in this paper. First, the synergistic effect mechanism of cutting parameters and tool wear on energy consumption in the batch processing was analyzed. On this basis, a multi-objective cutting parameter optimization model for multi-feature parts batch processing was established. Then, the multi-objective cuckoo search (MOCS) algorithm was used to solve the optimization model. Finally, an experimental case was carried out to verify the effectiveness and practicability of the proposed method. Results show that energy consumption and machining time can be, respectively, decreased by 22.9% and 4.1%. Meanwhile, a conflict relationship exists between the energy consumption and machining time in the processing and the trade-off of them is analyzed in this paper.