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IJAT Vol.7 No.4 pp. 391-400
doi: 10.20965/ijat.2013.p0391
(2013)

Paper:

Fast Cutter Workpiece Engagement Estimation Method for Prediction of Instantaneous Cutting Force in Continuous Multi-Axis Controlled Machining

Jun’ichi Kaneko and Kenichiro Horio

Department of Mechanical Engineering, Graduate School of Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama, Saitama 338-8570, Japan

Received:
February 13, 2013
Accepted:
June 29, 2013
Published:
July 5, 2013
Keywords:
multi-axis controlled machining, instantaneous cutting force, engagement, estimation, GPGPU
Abstract

In order to realize high productivity in rough machining processes, a fast simulation system is needed for multi axis controlled machining to predict instantaneous cutting force. The new efficient algorithm to estimate an engagement between the end mill cutter and the machined workpiece in continuous multi axis controlled machining processes is proposed. In order to shorten calculation time for the engagement area, and to improve the real-time prediction of instantaneous cutting force, a new concept is introduced for adapting ultra-parallel processing technology. The proposed method assumes the engagement as a large number of divisions located on the locus of cutting edges. The inclusion estimation process between an estimation point in each division and the machined workpiece volume is resolved into two kinds of simple inclusion estimation – and between the estimation point and tool swept volume and the other between the estimation point and initial workpiece shape. In this paper, a new prototype system based on parallel processing technology known as the general purposed graphic processing unit (GPGPU) is developed and the proposed algorithm is verified with the prototype system. The system shows good performance for complicated NC programs generated by commercial CAM system and realizes real-time simulation of instantaneous cutting force.

Cite this article as:
J. Kaneko and K. Horio, “Fast Cutter Workpiece Engagement Estimation Method for Prediction of Instantaneous Cutting Force in Continuous Multi-Axis Controlled Machining,” Int. J. Automation Technol., Vol.7, No.4, pp. 391-400, 2013.
Data files:
References
  1. [1] Y. Altintas and A. Spence, “End Milling Force Algorithm for CAD Systems,” Annal of the CIRP, Vol.40, No.1, pp. 31-34, 1991.
  2. [2] S. Smith and J. Tlusty, “An Over View of Modeling and Simulation of Milling Process,” Trans of ASME J. of Eng. for Ind., Vol.113, No.2, pp. 169-175, 1991.
  3. [3] H. Narita, K. Shirase, H. Wakamatsu, and E. Arai, “Pre-process Evaluation of Machining Accuracy using Virtual Machining Simulator,” JSME Int. J. Series C, Vol.43, No.2, pp. 492-497, 2000.
  4. [4] S. Ehsan Layegh K., H. Erdim, and I. Lazoglu, “Offline Force Control and Feedrate Scheduling for Complex Free Form Surface in 5-Axis Milling,” Procedia CIRP, Vol.1, pp. 96-101, 2012.
  5. [5] S. Takata, M. Tsai, M. Inui, and T. Sata, “Cutting Simulation System for Machinability Evaluation Using a Workpiece Model,” Annals of the CIRP, Vol.38, No.1, pp. 417-420, 1989.
  6. [6] Y. Takeuchi, M. Sakamoto, Y. Abe, and R. Orita, “Development of a Personal CAD/CAM System for Mold Manufacture Based on Solid Modeling Techniques,” Annal of the CIRP, Vol.38, No.1, pp. 429-432, 1989.
  7. [7] T. Kishinami, S. Kanai, H. Shinjyo, H. Nakahara, and K. Saito, “An Application of Voxel Reperesentation to Machining Simulator,” Journal of the Japan Society for Precision Engineering, Vol.55, No.1, pp. 105-110, 1989 (in Japanese).
  8. [8] K. Nakamoto, T. Kouno, T. Koyama, T. Sakaguchi, and Y. Shirase, “Development of VirtualMachining Simulator by Using Voxel Model,” Journal of the Japan Society of Precision Engineering, Vol.74, No.12, pp. 1308-1312, 2008 (in Japanese).
  9. [9] S. Alan, E. Huseyin, N. P. Ronald, and F. F. Sarah, “High accuracy NCmilling simulation using composite adaptively sampled distance fields,” J. of Computer-Aided Design, Vol.44, pp. 522-536, 2012.
  10. [10] M. Inui and R. Kakio, “Fast Visualization of the NC Milling Result Using Graphics Acceleration Hardware,” Journal of the Japan Society of Precision Engineering, Vol.65, No.10, pp. 1466-1470, 1999 (in Japanese).
  11. [11] J. Kaneko, K. Teramoto, K. Horio, and Y. Takeuchi, “Direct Prediction of Cutting Error in Finish Endmilling Based on Sequence-Free Algorithm,” Mechatronics for Safety, Security and Dependability in a New Era, Elsevier, pp. 153-156, 2006.
  12. [12] J. Kaneko, K. Teramoto, K. Horio, and Y. Takeuchi, “Fast Estimation Method of Workpiece Shape in NC Machining Process for Prediction of Instantaneous Cutting Force,” Service Robotics and Mechatronics, Springer, pp. 373-378, 2010.
  13. [13] W.Wang and K.Wang, “Geometric Modeling for Swept Volume of Moving Solids,” IEEE Computer Graphics and Applications, Vol.6, No.12, pp. 8-12, 1986.
  14. [14] J. Kaneko and K. Horio, “Tool posture planning method for continuous multi axis control machining with consideration of shortening shank length of end mill,” Int. J. of Automation Technology, Vol.6, No.5, pp. 648-653, 2012.

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Last updated on Dec. 05, 2019