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


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

February 13, 2013
June 29, 2013
July 5, 2013
multi-axis controlled machining, instantaneous cutting force, engagement, estimation, GPGPU
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.
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