IJAT Vol.6 No.6 pp. 704-709
doi: 10.20965/ijat.2012.p0704


High-Efficiency Machining Strategy for Non-Uniformly Shaped Workpiece Using On-Machine Measurement

Keiji Ogawa, Heisaburo Nakagawa, and Toshihiro Iwao

Department of Mechanical Systems Engineering, School of Engineering, The University of Shiga Prefecture, 2500 Hassaka-cho, Hikone-shi, Shiga 522-8533, Japan

April 19, 2012
July 12, 2012
November 5, 2012
high-efficiency machining, on-machine measurement, large-size products, force monitoring, adaptive control
Non-uniformly shaped workpieces made of such materials as ceramic and cast metal can prevent higherefficiency machining from being achieved in the conventional process due to large deviation of removal stock. Therefore, this paper proposes a novel method to achieve a high-efficiency machining strategy for non-uniformly shaped workpieces using on-machine measurement. This method utilizes on-machine measurement of a workpiece placed at an arbitrary position on a machine table as a machining pre-process. The product shape is arranged in the workpiece shape, and NC program for machining is generated based on the on-machine measurement data. The proposed method can be expected to be reasonable for a largesize product that requires long machining time because of long initial setup time and air-cutting in machining. A case study using numerical experiment was carried out. The results showed that our proposed method reduced total manufacturing time including on-machine measurement.
Cite this article as:
K. Ogawa, H. Nakagawa, and T. Iwao, “High-Efficiency Machining Strategy for Non-Uniformly Shaped Workpiece Using On-Machine Measurement,” Int. J. Automation Technol., Vol.6 No.6, pp. 704-709, 2012.
Data files:
  1. [1] A. Matsubara and S. Ibaraki, “Monitoring and Control of Cutting Forces in Machining Processes: A Review,” Int. J. of Automation Technology, Vol.3, No.4, pp. 445-456, 2009.
  2. [2] F. Klocke, S. Kratz, T. Auerbach, S. Gierlings, G. Wirtz, and D. Veselovac, “ProcessMonitoring and Control ofMachining Operations,” Int. J. of Automation Technology, Vol.5, No.3, pp. 403-411, 2011.
  3. [3] M. Takei, D. Kurihara, S. Katsura, and Y. Kakinuma, “Hybrid Control for Machine Tool Table Applying Sensorless Cutting Force Monitoring,” Int. J. of Automation Technology, Vol.5, No.4, pp. 587-593, 2011.
  4. [4] D. Kim and D. Jeon, “Fuzzy-logiccontrol of Cutting Forces in CNC Milling Processes Using Motor Currents as Indirect Force Sensors,” Precision Engineering, Vol.35, Issue 1, pp. 143-152, 2011.
  5. [5] S. Ibaraki, M. Sakahira, H. Saraie, A. Matsubara, and Y. Kakino, “On theMonitoring of Cutting Forces in EndMilling Processes: An Estimation Method by Geometrically Combining Force Vectors of ServoMotors and a SpindleMotor,” J. of the Japan Society of Precision Engineering, Vol.70, No.8, pp. 1091-1095, 2004. (in Japanese)
  6. [6] T. Moriwaki and K. Shirase, “Intelligent Machine Tools: Current Status and Evolutional Architecture,” Int. J. ofManufacturing Technology and Management, Vol.9, Nos.3-4, pp. 204-218, 2006.
  7. [7] T. Sato, Y. Kakino, and A. Matsubara, “A Study on Drilling Process Control by Intelligent Machine Tools (2nd Report): Minimization of Total Machining Time of Drilling Multiple Holes Considering the Tool Life,” J. of the Japan Society of Precision Engineering, Vol.69, No.5, pp. 731-735, 2003. (in Japanese)
  8. [8] A. Matsubara, M. Sugihara, A. A. D. Sarhan, H. Saraie, S. Ibaraki, and Y. Kakino, “Research on Spindle and Machining Process Monitoring for Intelligent Machine Tools,” Proc. of 3rd Int. Conf. on Leading Edge Manufacturing in 21st Century, pp. 469-474, 2005.
  9. [9] K. Ogawa, H. Nakagawa, Y. Oda, and Y. Kakino, “Monitoring of Cutting Force in End-milling Processes Using Internal Sensors in a Linear Motor Driven Machining Center,” Proc. of 3rd Int. Conf. of Asian Society for Precision Engineering and Nanotechnology, 1D-7, pp. 1-5, 2009.
  10. [10] Y. Nakagawa, H. Nakagawa, and K. Ogawa, “High Efficiency Machining Using Force Control with Intelligent Machine Tools,” The Japan Society of Mechanical Engineers, Kansai branch, No.104-1, pp. 4-3, 2010. (in Japanese)
  11. [11] M. Cho, G. Kim, T. Seo, Y. Hong, and H. H. Cheng, “Integrated machining error compensation method using OMM data and modified PNN algorithm,” Int. J. of Machine Tools and Manufacture, Vol.46, Nos.12-13, pp. 1417-1427, 2006.
  12. [12] J. P. Choi, B. K. Min, and S. J. Lee, “Reduction of machining errors of a three-axis machine tool by on-machine measurement and error compensation system,” J. of Materials Processing Technology, Vols.155-156, pp. 2056-2064, 2004.
  13. [13] M. S. Rahman, T. Saleh, H. S. Lim, S. M. Son, and M. Rahman, “Development of an on-machine profile measurement system in ELID grinding for machining aspheric surface with software compensation,” Int. J. of Machine Tools and Manufacture, Vol.48, Nos.7-8, pp. 887-895, 2008.

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