Fast Cutter Accessibility Analysis Using Ray Tracing Cores of GPU
Masatomo Inui, Kohei Kaba, and Nobuyuki Umezu
Department of Mechanical Systems Engineering, Ibaraki University
4-12-1 Nakanarusawa, Hitachi, Ibaraki 316-8511, Japan
In the cutter path computation for the five-axis machining, it takes much time to determine proper cutter postures in machining. We propose a novel method for calculating all possible cutter postures that can be used in machining mold’s surface without collisions in a short time. In determining the cutter postures for each cutting point, intersection detection between a line segment and a set of polygons is frequently carried out. Latest graphics processing units (GPUs) are equipped with a hardware called ray tracing (RT) cores dedicated to image processing in the 3D computer graphics. We use this RT core technology for accelerating the intersection detection and consequently reducing the time and cost necessary in the cutter posture determination. We also present the numerical experiments conducted to verify the effectiveness of the proposed method.
-  M. Inui, K. Nishimiya, and N. Umezu, “Accessibility map for assisting cutter posture determination in five-axis mold machining,” Proc. 2020 IEEE 16th Int. Conf. on Automation Science and Engineering (CASE), pp. 432-437, doi: 10.1109/CASE48305.2020.9216975, 2020.
-  B. K. Choi and R. B. Jerard, “Sculptured surface machining, theory and applications,” Kluwer Academic Publishers, Dordrecht, 1998.
-  M. Rao, F. Ismail, and S. Bedi, “Tool path planning for five-axis machining using the princial axis method,” Int. J. Mach. Tools Manuf., Vol.37, Issue 7, pp. 1025-1040, doi: 10.1016/S0890-6955(96)00046-6, 1997.
-  S. S. Makhanov, “Adaptable geometric patterns for five-axis machining: a survey,” Int. J. Adv. Manuf. Technol., Vol.47, pp. 1167-1208, doi: 10.1007/s00170-009-2244-z, 2010.
-  R. T. Farouki and S. Li, “Optimal tool orientation control for 5-axis CNC milling with ball-end cutters,” Comput. Aided Geom. Des., Vol.30, pp. 226-239, doi: 10.1016/j.cagd.2012.11.003, 2013.
-  E. L. J. Bohez, S. D. R. Senadhera, K. Pole, J. R. Duflou, and T. Tar, “A geometric modeling and five-axis machining algorithm for centrifugal impellers,” J. Manuf. Syst., Vol.16, Issue 6, pp. 422-436, doi: 10.1016/S0278-6125(97)81700-1, 1997.
-  Y. Takeuchi, T. Idemura, and T. Sata, “5-axis control machining and grinding based on solid model,” CIRP Annals – Manufacturing Technology, Vol.40, No.1, pp. 455-458, doi: 10.1016/S0007-8506(07)62028-9, 1991.
-  Y. Takeuchi and T. Watanabe, “Generation of 5-axis control collision-free tool path and postprocessing for NC data,” CIRP Annals – Manuf. Tech., Vol.41, No.1, pp. 539-542, doi: 10.1016/S0007-8506(07)61263-3, 1992.
-  K. Morishige and Y. Takeuchi, “5-axis control rough cutting of an impeller with efficiency and accuracy,” Proc. 1997 IEEE Int. Conf. Robot. Autom., pp. 1241-1247, doi: 10.1109/ROBOT.1997.614307, 1997.
-  K. Morishige, Y. Takeuchi, and K. Kase, “Tool path generation using C-space for 5-axis control machining,” J. Manuf. Sci. Eng., Vol.121, No.1, pp. 144-149, doi: 10.2493/jjspe.62.1783, 1999.
-  J. Kaneko and K. Horio, “Fast determination method of tool posture for 5-axis control machining using graphics hardware,” J. Japn. Soc. Precis. Eng., Vol.72, No.8, pp. 1012-1017, doi: 10.2493/jspe.72.1012, 2006 (in Japanese).
-  J.-K. Kang and S.-H. Suh, “Machinability and set-up orientation for five-axis numerically controlled machining of free surfaces,” Int. J. Adv. Manuf. Tech., Vol.13, No.5, pp. 311-325, doi: 10.1007/BF01178251, 1997.
-  S. N. Spitz, A. J. Spyridi, and A. A. G. Requicha, “Accessibility analysis for planning of dimensional inspection with coordinate measuring machines,” IEEE Trans. Robot. Autom., Vol.15, No.4, pp. 714-727, doi: 10.1109/70.782025, 1999.
-  K. Morimoto and M. Inui, “A GPU based algorithm for determining the optimal cutting direction in deep mold machining,” Proc. of IEEE Int. Symp. Assembly Manuf., doi: 10.1109/ISAM.2007.4288473, 2007.
-  M. Inui, “Fast inverse offset computation using polygon rendering hardware,” Comput. Aided Des., Vol.35, pp. 191-201, doi: 10.1016/S0010-4485(02)00052-0, 2003.
-  M. Inui, N. Umezu, and Y. Kitamura, “Visualizing sphere-contacting areas on automobile parts for ECE inspection,” J. Comput. Des. Eng., Vol.2, Issue 1, pp. 55-66, doi: 10.1016/j.jcde.2014.11.006, 2015.
-  W. Li and S. McMains, “Voxelized Minkowski sum computation on the GPU with robust culling,” Comput. Aided Des., Vol.43, No.10, pp. 1270-1283, doi: 10.1016/j.cad.2011.06.022, 2011.
-  M. Inui and A. Ohta, “Using a GPU to accelerate die and mold fabrication,” IEEE Comput. Graph. Appl., Vol.27, pp. 82-88, doi: 10.1109/MCG.2007.23, 2007.
-  M. Jachym, S. Lavernhe, C. Euzenat, and C. Tournier, “Effective NC machining simulation with OptiX ray tracing engine,” Vis. Comput., Vol.35, pp. 281-288, doi: 10.1007/s00371-018-1497-7, 2019.
-  M. Inui, K. Kaba, and N. Umezu, “Fast dexelization of polyhedral models using ray-tracing cores of GPU,” Comput. Aided Des. & Appl., Vol.18, No.4, pp. 786-798, doi: 10.14733/cadaps.2021.786-798, 2021.
-  M. Inui, N. Umezu, and M. Tsukahara, “Simple offset algorithm for generating workpiece solid model for milling simulation,” J. Adv. Mech. Des. Syst. Manuf., Vol.11, No.4, doi: 10.1299/jamdsm.2017jamdsm0042, 2017.
-  NVIDIA, OptiX™ ray tracing engine. https://developer.nvidia.com/optix [Accessed October 18, 2021]
-  NVIDIA, CUDA C Programming Guide, 2018.
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