Surface roughness modeling in Laser-assisted End Milling of Inconel 718

• Published in: Machining science and technology 2019-07, Vol.23 (4), p.650-668
• Main Authors: Feng, Yixuan, Hung, Tsung-Pin, Lu, Yu-Ting, Lin, Yu-Fu, Hsu, Fu-Chuan, Lin, Chiu-Feng, Lu, Ying-Cheng, Lu, Xiaohong, Liang, Steven Y.
• Format: Article
• Language: English
• Subjects: Inconel 718; laser-assisted milling; modeling; surface roughness
• ISSN: 1091-0344; 1532-2483
• DOI: 10.1080/10910344.2019.1575407

Inconel 718 is a difficult-to-machine material while products of this material require good surface finish. Therefore, it is essential for the evaluation and prediction of surface roughness of machined Inconel 718 workpiece to be developed. An analytical model for the prediction of surface roughness under laser-assisted end milling of Inconel 718 is proposed based on kinematics of tool movement and elastic response of workpiece. The actual tool trajectory is first predicted with the consideration of overall tool movement, elastic deformation of tool, and the tool tip profile. The tool movements include the translation in feed direction and the rotation along its axis. The elastic deformation is calculated based on the previously established milling force prediction model. The tool tip profile is predicted based on the tool tip radius and angle. The machined surface profile is simulated based on the tool trajectory with elastic recovery, which is considered through the comparison between the minimum thickness and actual cutting thickness. Experiments are conducted in both conventional and laser-assisted milling under seven different sets of cutting parameters. Through the comparison between the analytical predictions and experimental measurements, the proposed model has high accuracy with the maximum error less than 27%, which is more accurate for lower feed rate with error less than 3%. The proposed analytical model is valuable for providing a fast, credible, and physics-based method for the prediction of surface roughness in milling process.