single-au.php

IJAT Vol.10 No.3 pp. 429-437
doi: 10.20965/ijat.2016.p0429
(2016)

Paper:

Accurate Estimation of Cutting Time Based on Control Principle of Machine Tool

Kosuke Saito*, Hideki Aoyama*,†, and Noriaki Sano**

*Keio University
3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan

Corresponding author, E-mail: haoyama@sd.keio.ac.jp

**UEL Corporation, Tokyo, Japan

Received:
November 2, 2015
Accepted:
March 1, 2016
Published:
May 2, 2016
Keywords:
CAM, machine tool, numerical control, machining speed, sampling time
Abstract

The accurate estimation of cutting time before beginning a cutting process is necessary to improve the productivity of machining. Commercial computer-aided machining (CAM) systems estimate the cutting time by dividing the tool path length by the designated feed rate in a numerical control (NC) program. However, the actual cutting time generally exceeds the estimated cutting time for curved surfaces because of the acceleration and deceleration of the NC machine tool. There are systems that estimate cutting time while considering acceleration and deceleration along the controlled axes, but these are applicable only to particular machine tools. In this study, a flexible system for the accurate estimation of cutting time, based on the control principle of a machine tool, is developed. Experiments to estimate cutting time are conducted for the machining of complex shapes using two different NC machine tools. The actual cutting time is compared with the cutting time estimated by the developed system and that by a commercial CAM system. The estimation error of the proposed system is only 7%, while that of the commercial CAM system is 51%.

Cite this article as:
K. Saito, H. Aoyama, and N. Sano, “Accurate Estimation of Cutting Time Based on Control Principle of Machine Tool,” Int. J. Automation Technol., Vol.10, No.3, pp. 429-437, 2016.
Data files:
References
  1. [1] P. G. Maropoulos, R. Baker, and K. Paramor, “Integration of tool selection with design Part 2: Aggregate machining time estimation,” J. of Materials Processing Technology, Vol.107, Nos.1-3, pp. 135-142, 2000.
  2. [2] M. Monreal and C. Rodriguez, “Influence of tool path strategy on the cycle time of high-speed milling,” Computer-Aided Design, Vol.35, No.4, pp. 395-401, 2003.
  3. [3] X. Yan, K. Shirase, M. Hirano, and T. Yasui, “NC program evaluator for higher machining productivity,” Int. J. of Machine Tools & Manufacture, Vol.39, No.10, pp. 1563-1573, 1999.
  4. [4] E. Heo, D. Kim, B. Kim, and F. Chen, “Estimation of NC machining time using NC block distribution for sculptured surface machining,” Robotics and Computer-Integrated Manufacturing, Vol.22, Nos.5-6, pp. 437-446, 2006.
  5. [5] H. Siller, C. Rodriguez, and H. Ahuett, “Cycle time prediction in high-speed milling operations for sculptured surface finishing,” J. of Materials Processing Technology, Vol.174, Nos.1-3, pp. 355-362, 2006.
  6. [6] A. Matsubara, “Design and control of precision positioning and feed drive systems,” pp. 71-107, Morikita Publishing Co., Ltd., 2008 (in Japanese).
  7. [7] Y. Altintas and S. Tulsyan, “Prediction of part machining cycle times via virtual CNC,” CIRP Annals – Manufacturing Technology, Vol.64, pp. 361-364, 2015.
  8. [8] H. Siller, C. A. Rodriguez, and H. Ahuett, “Cycle time prediction in high-speed milling operations for sculptured surface finishing,” J. of Materials Processing Technology, Vol.174, pp. 355-362, 2006.
  9. [9] E.-Y. Heoa, D.-W. Kima, B.-H. Kimb, and F. F. Chen, “Estimation of NC machining time using NC block distribution for sculptured surface machining,” Robotics and Computer-Integrated Manufacturing, Vol.22, pp. 437-446, 2006.
  10. [10] B. Sencer, “Trajectory Generation for CNC Machine Tools,” J. of JSPE, Vol.79, No.7, pp. 631-638, 2013.
  11. [11] C. A. Rodríguez, T. Harnau, Y. Wang, N. Akgerman, and T. Altan, “Estimation of Machining Time in High-Speed Millingof Prismatic Parts,” Society of Manufacturing Engineers, Technical Paper No.MS99-142, 1999.
  12. [12] M. Monreal and C. A. Rodríguez, “Influence of tool path strategy on the cycle time of high-speed milling,” Computer Aided Design, Vol.395, Issue 4, pp. 395-401, 2003.
  13. [13] B. H. Kim and B. K. Choi, “Machining efficiency comparison direction-parallel tool path with contour-parallel tool path,” Computer Aided Design, Vol.34, pp. 89-95, 2002.
  14. [14] T. Unno, Y. Morimoto, Y. Ichida, and R. Sato, “Real-Time Synthesis and Control by Corrected Inverse Transfer Function of NC Tables – Effects of Compensation at Quadrant Motion for Circular Interpolation –,” J. of JSPE, Vol.74, No.1, pp. 72-76, 2008 (in Japanese).
  15. [15] P. G. Maropoulos, R. P. Baker, and K. Y. G. Paramor, “Integration of tool selection with design Part 2: Aggregate machining time estimation,” J. Material Process Technology, Vol.107, Issues 1-3, pp. 135-142, 2000.
  16. [16] E. Y. Heo, B. H. Kim, and D. W. Kim, “Estimation of sculptured surface NC machining time,” Trans. of the Society of CAD/CAM Engineers, Vol.8, Issue 4, pp. 254-261, 2003.
  17. [17] B. S. Soa, Y. H. Jungb, J. W. Parkc, and D. W. Leed, “Five-axis machining time estimation algorithm based on machine characteristics,” J. of Materials Processing Technology, Vol.187-188, pp. 37-40, 2007.
  18. [18] R. T. Coelho, A. F. de Souza, A. R. Roger, A. M. Y. Rigatti, and A. A. de Lima Ribeiro, “Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate,” Int. J. of Advanced Manufacturing Technology, Vol.46, Issue 9, pp. 1103-1111, 2010.
  19. [19] E. M Shehab and H. S Abdalla, “Manufacturing cost modelling for concurrent product development,” Robotics and Computer-Integrated Manufacturing, Vol.17, Issue 4, pp. 341-353, 2001.
  20. [20] E. Shehab and H. Abdalla, “An Intelligent Knowledge-Based System for Product Cost Modelling,” Int. J. of Advanced Manufacturing Technology, Vol.19, Issue 1, pp. 49-65, 2002.
  21. [21] K. Saito, H. Aoyama, and N. Sano, “Toolpath Generation Method Based on Control Characteristics of Machine Tool for High-Speed and High-Accuracy Machining,” Int. J. of Automation Technology, Vol.6, No.6, pp. 697-703, 2012.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Aug. 19, 2019