Open Access
MATEC Web of Conferences
Volume 28, 2015
2015 the 4th International Conference on Advances in Mechanics Engineering (ICAME 2015)
Article Number 02001
Number of page(s) 9
Section Mechanical design manufacturing and automation
Published online 28 October 2015
  1. Y. Altintas: Manufacturing automation, principles of metal cutting and machine tool vibrations, Cambribge University (2000), in press. [Google Scholar]
  2. Y. Altintas: Analytical prediction of three dimensional chatter stability in milling, Jpn. Soc. Mech. Eng. Vol. 44(3) (2001), p. 717–723. [Google Scholar]
  3. M. Rahman: In-process detection of chatter by automatic spindle regulation, CIRP Ann Vol. 41(1) (1992), p. 433–436. [CrossRef] [Google Scholar]
  4. I. Inasaki, B. Karpuschewski and H.S. Lee: Grinding Chatter – Origin and Suppression, CIRP Ann. Manuf. Technol. Vol. 50(2) (2001), p. 515–534. [Google Scholar]
  5. Z.C. Li, B. Lin, Y.S. et al XU, et al: Experimental studies on grinding forces and force ratio of the unsteady-state grinding technique, J. Mater. Process. Technol. Vol. 129(1–3) (2002), p. 76–80. [CrossRef] [Google Scholar]
  6. H. Li and Y.C. Shin: A study on chatter boundaries of cylindrical plunge grinding with process condition-dependent dynamics, Int. J. Mach. Tool Manuf. Vol. 47 (2007), p. 1563–1572. [Google Scholar]
  7. N. Subramanya and Y.C. Shin: Automated sensor selection and fusion for monitoring and diagnostics of plunge grinding, Trans. ASME J. Manuf. Sci. Eng. Vol. 130(3) (2008), 031014-1–031014-11. [Google Scholar]
  8. Y. Altintas and P. Lee: Mechanics and dynamics of ball end milling, Trans. ASME J. Manuf. Sci. Vol. 120 (1998), p. 684–692. [CrossRef] [Google Scholar]
  9. Y. Altintas and E. Budek: Analytical prediction of stability lobes in milling, Ann CIRP Vol. 44(1) (1995), p. 357–362. [Google Scholar]
  10. Y. Altintas and S.S. Park: Dynamic Compensation of Spindle- Integrated Force Sensors, Ann CIRP Vol. 53(1) (2004), p. 305–308. [CrossRef] [Google Scholar]
  11. S. Tangjitsitcharoen and T. Moriwaki: Intelligent identification of turning process based on pattern recognition of cutting states, Mater. Proc. Technol. Vol. 192-193 (2007), p. 491–496. [CrossRef] [Google Scholar]
  12. J. Hino, C. Su and T. Yoshimura: A study of chatter prediction in high-speed end milling process by fuzzy neural network, J. Soc. Mech. Eng. Ser.C Vol. 47 (2001), p. 825–831. [Google Scholar]
  13. T. Moriwaki and Y. Mori: Sensor fusion for in- process identification of cutting process based on neural network approach, Proc. IMACS/SICE Int. Symp. on Rob, Mechatron. and Manuf. Syst. Kobe (1992), p. 245–250. [Google Scholar]
  14. S. Tangjitsitcharoen: Advance in detection system to improve the stability and capability of CNC turning process, J. Intell. Manuf. 22 (2011), p. 843–852. [CrossRef] [Google Scholar]
  15. K. Ueda, S. Miyamoto and T. Sugita: An approach to adaptive control based on pattern recognition of cutting states, In: Proceedings of 6th International Conference Production Engineering, Osaka (1987), p. 212–217. [Google Scholar]
  16. S. Tangjitsitcharoen and N. Pongsathornwiwat: Development of chatter detection in milling process, Int. J. Adv. Manuf. Technol. 65 (2013), p. 919–927. [CrossRef] [Google Scholar]
  17. T. Sata, K. Matsushima, T. et al Nakamura, et al: Learning and recognition of the cutting states by spectrum analysis, Ann CIRP 22 (1973), p. 41–42. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.