Open Access
Volume 36, Number 1, February 2018
Page(s) 124 - 131
Published online 18 May 2018
  1. Hu Yushen, Yuan Yulan, Zhou Liang. Experiment of Temperature in Milling Material ZM5 Based on Cutting Parameter[J]. Machine Building & Automation, 2010, 39(5) : 44-45 (in Chinese) [Google Scholar]
  2. Ruslan M S, Othman K, Ghani J A, et al. Surface Roughness of Magnesium Alloy AZ91D in High Speed Milling[J]. Journal Technologies, 2016, 78(6/9) : 115-119[Article] [Google Scholar]
  3. Lu L, Hu S, Liu L, et al. High Speed Cutting of AZ31 Magnesium Alloy[J]. Journal of Magnesium and Alloys, 2016, 4(2) : 128-134 10.1016/j.jma.2016.04.004 [NASA ADS] [CrossRef] [Google Scholar]
  4. Pu Z, Umbrello D, Dillon O W, et al. Finite Element Modeling of Microstructural Changes in Dry and Cryogenic Machining of AZ31B Magnesium Alloy[J]. Journal of Manufacturing Processes, 2014, 16(2) : 335-343 10.1016/j.jmapro.2014.02.002 [CrossRef] [Google Scholar]
  5. Salahshoor M, Guo Y B. Cutting Mechanics in High Speed Dry Machining of Biomedical Magnesium-Calcium Alloy Using Internal State Variable Plasticity Model[J]. International Journal of Machine Tools and Manufacture, 2011, 51(7) : 579-590[Article] [CrossRef] [Google Scholar]
  6. Liu Longfei, Hu Shaohua, Lu Liwei. Sawtooth Chip of AZ31 Magnesium Alloy under High-Speed Cutting and Different Cutting Velocities[J]. Chinese Journal of Rare Metals, 2016(7) : 654-659 (in Chinese) [Google Scholar]
  7. Fu Hongya, Zhang Xiang, Han Zhenyu, et al. Modeling and Simulation of Micro-Ball-End Milling Forces[J]. Computer Integrated Manufacturing Systems, 2011, 17(7) : 1448-1453 (in Chinese) [Google Scholar]
  8. Guo M, Wang R, Zhu X. High Speed Machining of Magnesium Alloy[J]. Ordnance Material Science and Engineering, 2009(6) : 92-96[Article] [Google Scholar]
  9. Bhowmick S, Lukitsch M J, Alpas A T. Dry and Minimum Quantity Lubrication Drilling of Cast Magnesium Alloy(AM60)[J]. International Journal of Machine Tools and Manufacture, 2010, 50(5) : 444-457 10.1016/j.ijmachtools.2010.02.001 [CrossRef] [Google Scholar]
  10. Mandal N, Doloi B, Mondal B. Force Prediction Model of Zirconia Toughened Alumina(ZTA) Inserts in Hard Turning of AISI 4340 Steel Using Response Surface Methodology[J]. International Journal of Precision Engineering and Manufacturing, 2012, 13(9) : 1589-1599 10.1007/s12541-012-0209-x [CrossRef] [Google Scholar]
  11. Lim B S. Fuzzy Regression Modeling for Tool Performance Prediction and Degradation Detection[J]. International Journal of Neural Systems, 2010, 20(5) : 405-419 10.1142/S0129065710002498 [CrossRef] [Google Scholar]

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