A study on the laser-assisted milling of 13-8 stainless steel for optimal machining. (December 2020)

• Record Type: Journal Article
• Authors: Cao, Xu-Feng; Woo, Wan-Sik; Lee, Choon-Man
• Is Part Of: Optics & laser technology. Volume 132(2020)
• Publication Date: 2020-12
• Subjects: Laser-assisted machining -- Stainless steel -- Design of experiment -- Optimal machining conditions; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2020.106473
• Languages: English
• ISSNs: 0030-3992

Abstract

Highlights: Laser-assisted milling (LAMilling) of stainless steel was performed. Optimal LAMilling conditions were determined using Taguchi method. Influence factor with the greatest effect on cutting force was the depth of cut. Cutting force prediction equation and the experimental data were in good agreement. The machining characteristics were improved by the LAMilling. Abstract: 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.