Title: Multi-objective optimisation method of cutting parameters of CNC machine tools based on improved genetic algorithm

Authors: Zhenzhuo Wang; Yijie Zhu

Addresses: Department of Automation Engineering, Henan Polytechnic Institute, NanYang, 473000, China ' Department of Electronic Information Engineering, Henan Polytechnic Institute, NanYang, 473000, China

Abstract: To improve the energy efficiency level of CNC machine tool processing, reduce production costs and energy consumption, a multi-objective optimisation method for cutting parameters of CNC machine tools based on improved genetic algorithm is proposed. Firstly, a multi-objective optimisation model for cutting parameters of CNC machine tools was constructed with the minimum energy consumption, maximum benefit, and maximum timeliness as objective functions, combined with three constraints of cutting speed, cutting power, and feed rate. Then, the objective function values of the cutting parameters of the CNC machine tool are sorted by non-dominated sorting based on the dominated effect. Finally, an improved Pareto genetic multi-objective optimisation method is designed using the improved niche technique and the vector modulus fitness function as the criterion for outliers, in order to obtain the optimal multi-objective optimisation of the cutting parameters of the CNC machine tool. The experimental results show that the method improves the feed speed, cutting speed and cutting depth, reduces the machining energy consumption, machining cost and machining time, and has good application effect.

Keywords: CNC machine tools; objective function; cutting parameters; constraints; goal optimisation; improved genetic algorithm.

DOI: 10.1504/IJMTM.2025.145933

International Journal of Manufacturing Technology and Management, 2025 Vol.39 No.3/4/5, pp.195 - 215

Received: 31 Oct 2023
Accepted: 03 Jun 2024
Published online: 30 Apr 2025 *

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