Advertisement

Identification and compensation of position-dependent geometric errors of rotary axes on five-axis machine tools by using a touch-trigger probe and three spheres

  • Yu-Ta Chen
  • Pruthvikumar More
  • Chien-Sheng LiuEmail author
  • Chih-Chun Cheng
ORIGINAL ARTICLE

Abstract

For the machining accuracy of five-axis machine tools, it must be emphasized that not only the PIGEs but also the PDGEs of rotary axes influence the machining accuracy. However, until now there is no any commercial measurement system available for identifying the PDGEs in the rotary axes of five-axis machine tools. As a result, this study proposes a robust, efficient, and automatic measurement method to identify and compensate the position-dependent geometric errors (PDGEs) of rotary axes on five-axis machine tools. The proposed measurement method has established an on-machine measurement for the PDGEs of rotary axes by using a touch-trigger probe and three spheres installed on the spindle as well as the tilting rotary table, respectively. For each rotary axis, only a single measuring pattern is implemented to measure the PDGEs with a single setup, which delineates the advantages of efficient and automated identifying procedures in each periodical measurement. By implementing the proposed measurement method, 12 PDGEs can be numerically identified based on the measurement algorithm, which is built through a kinematic error model as well as a least square method. Finally, the proposed measurement method is experimentally conducted on a commercial five-axis machine tool. Moreover, after consequently performing the proposed measurement method, the PDGEs of the rotary axes were quantitatively compensated by the commercial controller to validate its feasibility. The experimental results have clearly delineated that the linear errors and angular errors are reduced from at most 37.81 μm and 10.23 mdeg to 0.9 μm and 0.26 mdeg, respectively. Consequently, the experimental results have demonstrated that the proposed measurement method is efficient and precise.

Keywords

Position-dependent geometric errors Rotary axis Five-axis machine tool Touch-trigger probe Error identification 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Funding information

The authors gratefully acknowledge the financial support provided to this study by the Ministry of Science and Technology of Taiwan under Grant Nos. MOST 106-2218-E-194-011, 106-3114-8-194-001, 106-2628-E-006-010-MY3, and 107-2218-E-194 -002.

References

  1. 1.
    Xiang S, Yang J (2014) Using a double ball bar to measure 10 position-dependent geometric errors for rotary axes on five-axis machine tools. Int J Adv Manuf Technol 75:559–572CrossRefGoogle Scholar
  2. 2.
    Chen YL, Shimizu Y, Cai Y, Wang S, Ito S, Ju BF, Gao W (2015) Self-evaluation of the cutting edge contour of a microdiamond tool with a force sensor integrated fast tool servo on an ultra-precision lathe. Int J Adv Manuf Technol 77:2257–2267CrossRefGoogle Scholar
  3. 3.
    Liu CS, Li YA (2018) Evaluation of grinding wheel loading phenomena by using acoustic emission signals. Int J Adv Manuf Technol 99:1109–1117Google Scholar
  4. 4.
    Li Y, Wei W, Su D, Zhao W, Zhang J, Wu W (2018) Thermal error modeling of spindle based on the principal component analysis considering temperature-changing process. Int J Adv Manuf Technol 99:1341–1349CrossRefGoogle Scholar
  5. 5.
    Wiessner M, Blaser P, Böhl S, Mayr J, Knapp W, Wegener K (2018) Thermal test piece for 5-axis machine tools. Precis Eng J Int Soc Precis Eng Nanotechnol 52:407–417Google Scholar
  6. 6.
    Wu SK, Tsai MS, Lin MT, Huang HW (2018) Development of novel tool center point velocity planning algorithm for five axis machine tool. Int J Precis Eng Manuf 19(8):1187–1199CrossRefGoogle Scholar
  7. 7.
    Blaser P, Pavliček F, Mori K, Mayr J, Weikert S, Wegener K (2017) Adaptive learning control for thermal error compensation of 5-axis machine tools. J Manuf Syst 44:302–309CrossRefGoogle Scholar
  8. 8.
    Olarra A, Axinte D, Kortaberria G (2018) Geometrical calibration and uncertainty estimation methodology for a novel self-propelled miniature robotic machine tool. Robot Comput Integr Manuf 49:204–214CrossRefGoogle Scholar
  9. 9.
    Szipka K, Laspas T, Archenti A (2018) Measurement and analysis of machine tool errors under quasi-staticand loaded conditions. Precis Eng J Int Soc Precis Eng Nanotechnol 51:59–67Google Scholar
  10. 10.
    Sun G, He G, Zhang D, Sang Y, Zhang X, Ding B (2018) Effects of geometrical errors of guideways on the repeatability of positioning of linear axes of machine tools. Int J Adv Manuf Technol 98:2319–2333CrossRefGoogle Scholar
  11. 11.
    Zha J, Xue F, Chen Y (2017) Straightness error modeling and compensation for gantry type open hydrostatic guideways in grinding machine. Int J Mach Tools Manuf 112:1–6CrossRefGoogle Scholar
  12. 12.
    Chen YT, Lin WC, Liu CS (2017) Design and experimental verification of novel six-degree-of freedom geometric error measurement system for linear stage. Opt Lasers Eng 92:94–104CrossRefGoogle Scholar
  13. 13.
    Liu W, Li X, Jia Z, Li H, Ma X, Yan H, Ma J (2018) Binocular-vision-based error detection system and identification method for PIGEs of rotary axis in five-axis machine tool. Precis Eng J Int Soc Precis Eng Nanotechnol 51:208–222Google Scholar
  14. 14.
    Lee KI, Yang SH (2013) Robust measurement method and uncertainty analysis for position-independent geometric errors of a rotary axis using a double ball-bar. Int J Precis Eng Manuf 14(2):231–239CrossRefGoogle Scholar
  15. 15.
    ISO 230-7 (2015) Test code for machine tools-part 7: geometric accuracy of axes of rotation, ISOGoogle Scholar
  16. 16.
    ISO 10791-1 (2015) Test conditions for machining centres –part1: geometric tests for machines with horizontal spindle (horizontal z-axis), ISOGoogle Scholar
  17. 17.
    ISO 10791-6 (2014) Test conditions for machining centres –part6: accuracy of speeds and interpolations, ISOGoogle Scholar
  18. 18.
    Flynn JM, Shokrani A, Vichare P, Dhokia V, Newman ST (2018) A new methodology for identifying location errors in 5-axis machine tools using a single ballbar set-up. Int J Adv Manuf Technol 99:53–71CrossRefGoogle Scholar
  19. 19.
    Xiang S, Yang J, Zhang Y (2014) Using a double ball bar to identify position-independent geometric errors on the rotary axes of five-axis machine tools. Int J Adv Manuf Technol 70:2071–2082CrossRefGoogle Scholar
  20. 20.
    Weikert S (2004) R-test, a new device for accuracy measurements on five axis machine tools. CIRP Ann Manuf Technol 53(1):429–432CrossRefGoogle Scholar
  21. 21.
    Ibaraki S, Knapp W (2012) Indirect measurement of volumetric accuracy for three-axis and five-axis machine tools: a review. Int J Autom Technol 6(2):110–124CrossRefGoogle Scholar
  22. 22.
    Bi Q, Huang N, Sun C, Wang Y, Zhu L, Ding H (2015) Identification and compensation of geometric errors of rotary axes on five-axis machine by on-machine measurement. Int J Mach Tools Manuf 89:182–191CrossRefGoogle Scholar
  23. 23.
    Ibaraki S, Iritani T, Matsushita T (2012) Calibration of location errors of rotary axes on five-axis machine tools by on-the-machine measurement using a touch-trigger probe. Int J Mach Tools Manuf 58:44–53CrossRefGoogle Scholar
  24. 24.
    Ibaraki S, Iritani T, Matsushita T (2013) Error map construction for rotary axes on five-axis machine tools by on-the-machine measurement using a touch-trigger probe. Int J Mach Tools Manuf 68:21–29CrossRefGoogle Scholar
  25. 25.
    Ibaraki S, Oyama C, Otsubo H (2011) Construction of an error map of rotary axes on a five-axis machining center by static R-test. Int J Mach Tools Manuf 51:190–200CrossRefGoogle Scholar
  26. 26.
    Zargarbashi SHH, Mayer JRR (2006) Assessment of machine tool trunnion axis motion error, using magnetic double ball bar. Int J Mach Tools Manuf 46:1823–1834CrossRefGoogle Scholar
  27. 27.
    Lee KI, Lee DM, Yang SH (2012) Parametric modeling and estimation of geometric errors for a rotary axis using double ball-bar. Int J Adv Manuf Technol 62:741–750CrossRefGoogle Scholar
  28. 28.
    Zhu S, Ding G, Qin S, Lei J, Zhuang L, Yan K (2012) Integrated geometric error modeling, identification and compensation of CNC machine tools. Int J Mach Tools Manuf 52(1):24–29CrossRefGoogle Scholar
  29. 29.
    Zhang Y, Yang J, Zhang K (2013) Geometric error measurement and compensation for the rotary table of five-axis machine tool with double ballbar. Int J Adv Manuf Technol 65:275–281CrossRefGoogle Scholar
  30. 30.
    Peng W, Xia H, Chen X, Lin Z, Wang Z, Li H (2018) Position-dependent geometric errors measurement and identification for rotary axis of multi-axis machine tools based on optimization method using double ball bar. Int J Adv Manuf Technol 99:2295–2307CrossRefGoogle Scholar
  31. 31.
    Chen YT, More P, Liu CS (2018) Identification and verification of location errors of rotary axes on five-axis machine tools by using a touch-trigger probe and a sphere. Int J Adv Manuf Technol. Online 1–15Google Scholar
  32. 32.
    Tsutsumi M, Saito A (2004) Identification of angular and positional deviations inherent to 5-axis machining centers with a tilting-rotary table by simultaneous four-axis control movements. Int J Mach Tools Manuf 44:1333–1342CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringNational Chung Cheng UniversityChiayi CountyTaiwan
  2. 2.Department of Mechanical EngineeringNational Cheng Kung UniversityTainan CityTaiwan

Personalised recommendations