Experimental investigation and parameters optimization on jet electrochemical machining to improve the surface performance of additive-manufactured 316L stainless steel parts

被引:3
|
作者
Cheng, Haixia [1 ]
Lou, Guibin [1 ]
Shen, Lida [1 ]
Zhang, Ming [1 ]
Yang, Youwen [2 ]
Xie, Deqiao [1 ]
Chen, Ya [1 ]
Bai, Huawen [1 ]
Tian, Zongjun [1 ,2 ]
Zhao, Jianfeng [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, State Key Lab Helicopter Transmiss, Nanjing 210016, Peoples R China
[2] Jiangxi Univ Sci & Technol, HongQi St, Ganzhou 341000, Peoples R China
基金
中国国家自然科学基金;
关键词
selective laser melting (SLM); jet electrochemical machining(JECM); signal-to-noise (S; N); response surface methodology(RSM); surface roughness; LASER; MICROSTRUCTURE; ALLOY;
D O I
10.1088/2051-672X/ac3808
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
For metal parts, selective laser melting (SLM) technology has obvious advantages over traditional forming methods. Parts manufactured by selective laser melting are abbreviated as SLMed Parts. However, the surfaces of SLMed parts have many defects such as adhered particles and pores. These defects lead to poor surface quality of the parts, thus restricting the promotion of SLM technology. Therefore, the paper uses jet electrochemical machining (JECM) to remove the surface defects of SLMed sample. Optimization is technique used in manufacturing sectors to generate the best manufacturing conditions. There are many process variables involved in the JECM process, and it is difficult to select an appropriate parameters combination to maximize the removal of surface defects while minimizing material removal thickness and surface roughness. The purpose of this work is to study the influence of process parameters such as electrolyte temperature, processing time, and current density on material removal thickness, surface roughness and material removal rate in the JECM process. In Minitab19, the L25 made by Taguchi orthogonal array was used in the experiment. Each experiment is carried out under different input parameters, and the data were analyzed through analysis of variance (ANOVA). The optimized processing parameters associated with performance parameters are given and ultimately the experimental results were verified.
引用
收藏
页数:16
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