Multi-objective Optimization Method of CFRP Drilling Process Parameters for Power and Drilling Quality

被引：0
作者：
Ma F. [1 ,2 ]
Huang S. [2 ,3 ]
Liu P. [4 ]
Zhang H. [1 ,3 ]
机构：
[1] Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan
[2] Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan
[3] Precision Manufacturing Institute, Wuhan University of Science and Technology, Wuhan
[4] Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University
来源：
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2023年 / 59卷 / 11期
关键词：
carbon fiber reinforced composite; CNC machining system; high-efficiency and low-carbon machining; multi-objective optimization;
D O I：
10.3901/JME.2023.11.290
中图分类号：
学科分类号：
摘要：
The proportion of carbon fiber reinforced composites (CFRP) used in high-end manufacturing fields such as aviation and aerospace has increased significantly. The large-scale production of CFRP components has been launched. Although the cost of CFRP can be reduced, problems such as consumption reduction, emission reduction and quality improvement will become increasingly prominent. In order to improve the quality of CFRP components and reduce the energy consumption and carbon emissions during the machining process, a multi-objective optimization study on the machining parameters of the drilling process for CFRP components is carried out. First, a multi-objective optimization model with spindle speed, feed rate and layer laying sequence of composite materials as optimization variables, drilling power during drilling and delamination factor at the orifice of CFRP components as objectives is determined; then, through full factor experiments, using the instrument to collect drilling power and delamination factor data; Furthermore, based on the response surface method, the influence of each machining parameter on the drilling power and delamination factor is analyzed; finally, the multi-objective model is optimized by using polynomial fitting and NSGA-II algorithm. The research results show that the constructed multi-objective optimization model and the proposed optimization method can obtain the optimal parameter combination, and the optimization results can significantly improve the machining quality and drilling power. © 2023 Editorial Office of Chinese Journal of Mechanical Engineering. All rights reserved.
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页码：290 / 299
页数：9
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