A study on the laser-assisted milling of 13-8 stainless steel for optimal machining

被引:14
|
作者
Cao, Xu-Feng [1 ]
Woo, Wan-Sik [2 ]
Lee, Choon-Man [3 ]
机构
[1] Jiangsu Hyundai Wia Co Ltd, 6 Fenghuang Rd, Zhangjiagang 215614, Peoples R China
[2] Adv Mfg Res Ctr AMRC Korea, 25,Gongdan 9 Ro 12 Gil, Gyongsan, Gyeongsangbuk D, South Korea
[3] Changwon Natl Univ, Coll Mechatron, Dept Mech Engn, 20 Changwondaehak Ro, Changwon Si 51140, Gyeongsangnam D, South Korea
来源
OPTICS AND LASER TECHNOLOGY | 2020年 / 132卷 / 132期
基金
新加坡国家研究基金会;
关键词
Laser-assisted machining; Stainless steel; Design of experiment; Optimal machining conditions; ENERGY EFFICIENCY; CUTTING FORCE; TEMPERATURE; OPTIMIZATION; WORKPIECE;
D O I
10.1016/j.optlastec.2020.106473
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Difficult-to-cut materials are being increasingly used. Precipitation hardened martensitic stainless steel, for example, has an excellent combination of strength and toughness, and is used in a large number of applications in the oil industry, the aviation industry, and the nuclear industry. But the same characteristics make it difficult to machine. Processing it with conventional machining (CM) methods requires a high cutting force, resulting in poor surface quality and short tool lives. Thermally-assisted machining (TAM) is considered an economic way of processing these difficult-to-cut materials. TAM uses external heat sources to locally heat and soften the workpiece in front of the cutting tool, enabling difficult-to-cut materials to be processed more easily. Representative heat sources for TAM are laser, plasma, and induction. The advantages of laser-assisted machining (LAM) are its high energy density and easily controlled heat source. The purpose of this study was to optimize the machining conditions of 13-8 stainless steel processed by LAM. Three factors have a significant effect on the machining characteristic, feed rate, spindle speed and depth of cut (DOC). In order to quantitatively understand the impact of these factors on processing characteristics, the Taguchi method was applied in this study. S/N ratio, ANOVA and response optimization were employed to analyze the experiment results for cutting force and surface roughness, to find the optimal machining conditions for LAM. The maximum error between the prediction equations and verification experiments for cutting force was 10.5%. Then the cutting force and the surface roughness of the LAM were reduced by 20.1% and 34.4%, respectively, compared to CM.
引用
收藏
页数:9
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