Machining characteristics and process parameter optimization of Near-dry electrical discharge milling of titanium alloy

被引:0
|
作者
Kang, Shaopeng [1 ,2 ]
Zhuo, Xianghua [1 ]
Kong, Linglei [1 ]
Li, Yanxin [1 ]
He, Yafeng [3 ]
机构
[1] Jiangsu Univ Technol, Sch Mech Engn, Changzhou 213001, Peoples R China
[2] Jiangsu Prov Engn Res Ctr Adv Fluid Power & Equipm, Changzhou 213001, Peoples R China
[3] Changzhou Inst Technol, Dept Aeronaut & Mech, Changzhou 213002, Peoples R China
来源
SCIENTIFIC REPORTS | 2025年 / 15卷 / 01期
基金
中国国家自然科学基金;
关键词
Ti-6Al-4V; Near-dry EDM; Fluid simulation; Orthogonal experiment; Grey relational analysis (GRA); HIGH-SPEED; ELECTRODE; TI-6AL-4V; FLUID; GAS; GRA;
D O I
10.1038/s41598-025-92830-y
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Titanium alloy (Ti-6Al-4V) is a difficult-to-machine material, known for its excellent physical and chemical properties. However, traditional machining methods incur high tool wear costs when processing this material. The near-dry electrical discharge milling (N-EDM) method, which removes excess material via electroerosion, mitigates the impact of titanium alloy's hardness and strength, enabling effective material cutting. To enhance machining efficiency and surface quality, this study employs a simulation model of the inter-electrode flow field, combined with experimental data, to investigate the effect of milling thickness on key machining parameters and determine the optimal thickness. Subsequently, a four-factor, three-level (L27(43)) orthogonal experiment was designed, with current, duty cycle, gas pressure, and atomization rate as input parameters. Material removal rate (MRR), relative electrode wear ratio (REWR), width of cut (WOC), and roughness average (Ra) were selected as primary optimization indicators. Based on the orthogonal experiment results, analysis of variance (ANOVA) was conducted to examine the influence of the input parameters on the various process indicators and determine the optimal single-objective processing parameters. Using Grey Relational Analysis (GRA), the multi-objective optimal machining parameters were identified as: 2 A current, 40% duty cycle, 0.2 MPa gas pressure, and 20 ml/min atomization rate. These parameters significantly enhance both processing efficiency and surface quality.
引用
收藏
页数:19
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