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In order to realize energy saving and high-efficiency production in the CNC turning process of parts, a novel hybrid approach for cutting parameters' optimization considering processing energy and efficiency is proposed. Through experimental fitting and orthogonal experiments, the no-load power and cutting power functions of the CNC lathe were obtained, and a multi-objective optimization model of energy saving and high efficiency was established. The model takes the minimum energy consumption and the fastest processing time as the goal, and comprehensively considers the actual constraints under the processing conditions of the lathe. An improved multi-objective teaching-learning-based optimization (TLBO) algorithm is designed to solve the multi-objective model, a self-study method is added in the learning stage to improve the global search ability of the algorithm, and a minimum partial optimization strategy is added in the teaching stage to ensure the balance of multi-objective optimization results. Finally, the proposed model and algorithm are verified via a typical case, the cutting parameter decision model is established by using analytic hierarchical process (AHP), and the Pareto front solution of cutting parameter optimization is obtained, which objectively selects a better combination of turning parameters. The results show that this method can guide the operator to select cutting parameters from qualitative random to quantitative, and provides theoretical guidance for enterprises implementing energy saving and high-efficiency production.

A novel hybrid approach for cutting parameters optimization considering processing energy and efficiency in turning process