The effect of surface roughness on ultrasonic assisted milling of Inconel 718

被引：0
|
作者：
All-Hafiz, Ohammad Shah [1 ]
Kasim, Mohd Shahir [1 ]
Mohamad, W. Noor Fatihah [1 ]
Izamshah, Raja [1 ]
Sundi, Syahrul Azwan [1 ]
Akmal, Muhammad [1 ]
机构：
[1] Univ Tek Malaysia Melaka, Fak Kejuruteraan Pembuatan, Durian Tunggal 76100, Melaka, Malaysia
来源：
PROCEEDINGS OF INNOVATIVE RESEARCH AND INDUSTRIAL DIALOGUE 2018 (IRID'18) | 2019年
关键词：
Ultrasonic assisted machining; Ultrasonic vibration machining; Surface roughness;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Ultrasonic assisted machining is a combination of precision machining with a small-amplitude vibration tool to improve machining capabilities. Recently, ultrasonic assisted machining has been the main focus of research particularly on ultrasonic vibration effects on machining processes. However, the characteristic of ultrasonic vibration has a potential to influence workpiece surface roughness. Therefore, the main objective of this study was to evaluate the performance of the ultrasonic assisted machining on the surface machined roughness in comparison with the conventional way. The result showed that the ultrasonic vibration improved the surface roughness up to 27% on flooded machining condition.
引用
收藏
页码：23 / 24
页数：2
相关论文
共 50 条
  • [41] Development of an artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy
    Hossain, Mohammad Ishtiyaq
    Amin, A. K. M. Nurul
    Patwari, Anayet U.
    2008 INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION ENGINEERING, VOLS 1-3, 2008, : 1321 - 1324
  • [42] Optimum surface roughness in end milling Inconel 718 by coupling neural network model and genetic algorithm
    Ozcelik, B. (ozcelik@penta.gyte.edu.tr), 1600, Springer-Verlag London Ltd (27): : 3 - 4
  • [43] Optimum surface roughness in end milling Inconel 718 by coupling neural network model and genetic algorithm
    Ozcelik, B
    Oktem, H
    Kurtaran, H
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2005, 27 (3-4): : 234 - 241
  • [44] Optimum surface roughness in end milling Inconel 718 by coupling neural network model and genetic algorithm
    Babur Ozcelik
    Hasan Oktem
    Hasan Kurtaran
    The International Journal of Advanced Manufacturing Technology, 2005, 27 : 234 - 241
  • [45] Effect of electropulsing-assisted ultrasonic nanocrystal surface modification on microstructures and hardness of additive manufactured Inconel 718
    Ye, Yixuan
    Zhang, Chaoyi
    Gao, Le
    Peng, Lan
    Liu, Gang
    Zhang, Yu
    Tang, Chao
    Huang, Tao
    Ye, Chang
    ENGINEERING FAILURE ANALYSIS, 2023, 153
  • [46] Influence of cutting tool wear when milling Inconel 718 on resulting roughness
    Mrkvica I.
    Špalek F.
    Szotkowski T.
    2018, Jan-Evangelista-Purkyne-University (18): : 457 - 461
  • [47] Tool wear and its effect on the surface integrity and fatigue behavior in high-speed ultrasonic peening milling of Inconel 718
    Yin, Xiaoming
    Liu, Yihang
    Zhao, Shicai
    Li, Xun
    Geng, Daxi
    Zhang, Deyuan
    TRIBOLOGY INTERNATIONAL, 2023, 178
  • [48] Ultrasonic-assisted on the turning of Inconel 718 by Taguchi method
    Chen, Ding-Yeng
    Tsao, Chung-Chen
    Lin, Mao-Yong
    Tsai, Che-Hsiung
    Hsu, Chun-Yao
    ADVANCED MANUFACTURING FOCUSING ON MULTI-DISCIPLINARY TECHNOLOGIES, 2012, 579 : 160 - 173
  • [49] An Initial Study of the Effect of Using Liquid Nitrogen Coolant on the Surface Roughness of Inconel 718 Nickel-Based Alloy in CNC Milling
    Shokrani, A.
    Dhokia, V.
    Newman, S. T.
    Imani-Asrai, R.
    45TH CIRP CONFERENCE ON MANUFACTURING SYSTEMS 2012, 2012, 3 : 121 - 125
  • [50] Studies on the effect of SiC nanopowder concentration and discharge energy on surface roughness and recast layer in micro ED milling of Inconel 718 alloy
    Boominathan, Elumalai
    Krishnan, Giridharan
    Gurijala, Chakravarthi
    Jothiprakash, V. M.
    PHYSICA SCRIPTA, 2025, 100 (01)
12345