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IJAT Vol.15 No.2 pp. 215-223
doi: 10.20965/ijat.2021.p0215
(2021)

Paper:

Forward Kinematics Model for Evaluation of Machining Performance of Robot Type Machine Tool

Akio Hayashi*,†, Hiroto Tanaka*, Masato Ueki**, Hidetaka Yamaoka*, Nobuaki Fujiki*, and Yoshitaka Morimoto*

*Kanazawa Institute of Technology
7-1 Ohgigaoka, Nonoichi, Ishikawa 924-8501, Japan

Corresponding author

**Sumitomo Wiring Systems, Ltd., Yokkaichi, Japan

Received:
August 31, 2020
Accepted:
December 1, 2020
Published:
March 5, 2021
Keywords:
robot-type machine tools, parallel link mechanism, forward kinematics model, positioning accuracy, machining performance
Abstract

Robot-type machine tools are characterized by the ability to change the tool posture and machine itself with a wider motion range than conventional machine tools. The motion of the robot machine tool is realized by simultaneous multi-axis control of link mechanisms. However, when the robot machine tool performs a general milling process, some problems that affect the machining accuracy occur. Moreover, it is difficult to identify the motion errors of each axis, which influence machining accuracy. Thus, it is difficult to adjust the servo gain and alignment error. In addition, the machining performance is unidentified because of the rigidity differences when the posture changes. In this study, the focus was on robot-type machine tools consisting of a serial and a parallel link mechanism. A geometric model is described, and the forward kinematics model is derived based on the geometric model. Machining tests were then carried out to evaluate the machining accuracy by measuring the machined surfaces and the simulated motion of the tool posture based on the proposed forward kinematics model to identify the mechanism that affects the machined surface roughness and surface waviness. As a result, it was shown that the proposed model can separate and reproduce the behavior of each axis of the machine. Finally, it was clarified that the behavior of the second axis has a great influence on the tool posture and machined surface.

Cite this article as:
Akio Hayashi, Hiroto Tanaka, Masato Ueki, Hidetaka Yamaoka, Nobuaki Fujiki, and Yoshitaka Morimoto, “Forward Kinematics Model for Evaluation of Machining Performance of Robot Type Machine Tool,” Int. J. Automation Technol., Vol.15, No.2, pp. 215-223, 2021.
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References
  1. [1] K. Thoben, S. Wiesner, and T. Wuest, ““Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples,” Int. J. Automation Technol., Vol.11, No.1, pp. 4-16, 2017.
  2. [2] Y. Domae, “Recent Trends in the Research of Industrial Robots and Future Outlook,” J. Robot. Mechatron., Vol.31, No.1, pp. 57-62, 2019.
  3. [3] M. Weck and D. Staimer, “Parallel Kinematic Machine Tools – Current State and Future Potentials,” CIRP Annals, Vol.51, No.2, pp. 671-683, 2002.
  4. [4] K. Neumann, “The key to aerospace automation,” SAE Aerospace Manufacturing and Automated Fastening Conf. and Exhibition, 2006-01-3144, 2006.
  5. [5] K. Neumann, “Practical and Portable Automated Machining,” SAE Aerospace Manufacturing and Automated Fastening, 2014-01-2275, 2014.
  6. [6] S. Matsuoka, K. Shimizu, N. Yamazaki, and Y. Oki, “High-speed End Milling of an Articulated Robot and Its Characteristics,” J. of Materials Processing Technology, Vol.95, Issues 1-3, pp. 83-89, 1999.
  7. [7] T. Oiwa, “Precision Mechanism Based on Parallel Kinematics,” J. of the Robotics Society of Japan, Vol.4, No.4, pp. 326-336, 2010.
  8. [8] L. B. da Silva, H. Yoshioka, H. Shinno, and J. Zhu, “Tool Orientation Angle Optimization for a Multi-Axis Robotic Milling System,” Int. J. Automation Technol., Vol.13, No.5, pp. 574-582, doi: 10.20965/ijat.2019.p0574, 2019.
  9. [9] W. Guo, R. Li, C. Cao, and Y. Gao, “Kinematics Analysis of a Novel 5-DOF Hybrid Manipulator,” Int. J. Automation Technol., Vol.9, No.6, pp. 765-774, doi: 10.20965/ijat.2015.p0765, 2015.
  10. [10] G. Ma, Y. Chen, Y. Yao, and J. Gao, “Kinematics and Singularity Analysis of a Four-Degree-of-Freedom Serial-Parallel Hybrid Manipulator,” J. Robot. Mechatron., Vol.29, No.3, pp. 520-527, 2017.
  11. [11] T. Harada and K. Dong, “Mechanical Design and Control of 3-DOF Active Scanning Probe Using Parallel Link Mechanism,” Int. J. Automation Technol., Vol.5, No.2, pp. 86-90, doi: 10.20965/ijat.2011.p0086, 2011.
  12. [12] Y. Takeda, K. Kamiyama, Y. Maki, M. Higuchi, and K. Sugimoto, “Development of Position-Orientation Decoupled Spatial In-Parallel Actuated Mechanisms with Six Degrees of Freedom,” J. Robot. Mechatron., Vol.17, No.1, pp. 59-68, 2005.
  13. [13] K. Xing, J. Mayer, and S. Achiche, “Impact of Model Complexity in the Monitoring of Machine Tools Condition Using Volumetric Errors,” Int. J. Automation Technol., Vol.14, No.3, pp. 369-379, 2020.
  14. [14] B. Montavon, P. Dahlem, M. Peterek, and R. Schmitt, “A Digital Perspective on Machine Tool Calibration,” Int. J. Automation Technol., Vol.14, No.3, pp. 360-368, 2020.
  15. [15] S. Ibaraki, S. Goto, K. Tsuboi, N. Saito, and N. Kojima, “Kinematic modeling and error sensitivity analysis for on-machine five-axis laser scanning measurement under machine geometric errors and workpiece setup errors,” Int. J. of Advanced Manufacturing Technology, Vol.96, pp. 4051-4062, 2018.
  16. [16] S. Ibaraki and I. Yoshida, “A five-axis machining error simulator for rotary-axis geometric errors using commercial machining simulation software,” Int. J. Automation Technol., Vol.11, No.2, pp. 179-187, doi: 10.20965/ijat.2017.p0179, 2017.
  17. [17] R. Sato, S. Hasegawa, K. Shirase, M. Hasegawa, A. Saito, and T. Iwasaki, “Motion Accuracy Enhancement of Five-Axis Machine Tools by Modified CL-Data,” Int. J. Automation Technol., Vol.12, No.5, pp. 699-706, 2018.
  18. [18] R. Sato, K. Morishita, I. Nishida, K. Shirase, M. Hasegawa, A. Saito, and T. Iwasaki, “Improvement of Simultaneous 5-Axis Controlled Machining Accuracy by CL-Data Modification,” Int. J. Automation Technol., Vol.13, No.5, pp. 583-592, 2019.
  19. [19] R. Sato, M. Maegawa, G. Tashiro, and K. Shirase, “Influence of Servo Characteristics on Motion Accuracy of Parallel Kinematic Mechanism,” Key Engineering Materials, Vols.523-524, pp. 762-767, 2012.
  20. [20] Y. Oba and Y. Kakinuma, “Simultaneous tool posture and polishing force control of unknown curved surface using serial-parallel mechanism polishing machine,” Precision Engineering, Vol.49, pp. 24-32, 2017.
  21. [21] H. Yachi and H. Tachiya, “Calibration Method for a Parallel Mechanism Type Machine Tool by Response Surface Methodology – Consideration via Simulation on a Stewart Platform Mechanism –,” Int. J. Automation Technol., Vol.4, No.4, pp. 355-363, 2010.
  22. [22] N. Zimmermann and S. Ibaraki, “Self-calibration of rotary axis and linear axes error motions by an automated on-machine probing test cycle,” The Int. J. of Advanced Manufacturing Technology, Vol.107, pp. 2107-2120, 2020.
  23. [23] S. Aoyagi, M. Suzuki, T. Takahashi, J. Fujioka, and Y. Kamiya, “Calibration of Kinematic Parameters of Robot Arm Using Laser Tracking System: Compensation for Non-Geometric Errors by Neural Networks and Selection of Optimal Measuring Points by Genetic Algorithm,” Int. J. Automation Technol., Vol.6, No.1, pp. 29-37, doi: 10.20965/ijat.2012, 2012.
  24. [24] S. Ibaraki, T. Yokawa et al., “A Study on the Improvement of Motion Accuracy of Hexapod-type Parallel Mechanism Machine Tool (3rd Report) – A Kinematic Calibration Method Considering Gravity Errors –,” J. of JSPE, Vol.72, No.3, pp. 355-359, doi: 10.2493/jspe.72.355, 2004 (in Japanese).
  25. [25] K. Nagao, N. Fujiki, Y. Morimoto, and A. Hayashi, “Calibration Method of Parallel Mechanism Type Machine Tools,” Int. J. Automation Technol., Vol.14, No.3, pp. 429-437, doi: 10.20965/ijat.2020.p0429, 2020.
  26. [26] I. Inasaki, “Theory of Generating Motion for Machine Tools: Formulation and Application,” JSME Int J., Series C, Vol.60, No.574, pp. 1891-1895, 1994 (in Japanese).

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Last updated on Jul. 20, 2021