Skip to main content
Log in

Wireless communication influence on CNC machine tool probe metrological parameters

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The influence of the wireless communication on CNC machine tools touch-trigger probe inaccuracy of probing is investigated. Factors such as time of processing and wireless transmission of trigger signal from the probe to the CNC machine tool controller including position and orientation of the interface receiver are taken into consideration. A new method allowing to obtain 3D probe error characteristics with several times more accuracy than the procedure used on a CNC machine tools has been applied. The analyses have been performed for several wireless interfaces of two types: an optical and a radio type. The influence of the abovementioned parameters has been analysed theoretically and verified experimentally. Good agreement between the proposed theoretical model and experimental data has been obtained.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Guiassa R, Mayer JRR, Balazinski M, Engin S, Delorme F-E (2014) Closed door machining error compensation of complex surfaces using the cutting compliance coefficient and on-machine measurement for a milling process. Int J Comput Integr Manuf 27(11):1022–1030

    Article  Google Scholar 

  2. Mayer JRR (2012) Five-axis machine tool calibration by probing a scale enriched reconfigurable uncalibrated master balls artifact. CIRP Ann Manuf Technol 61:515–518

    Article  Google Scholar 

  3. 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 68:21–29

    Article  Google Scholar 

  4. Ibaraki S, Ota Y (2013) Error calibration for five-axis machine tools by on-the-machine measurement using a touch-trigger probe. Int J Autom Technol 8(1):20–27

    Google Scholar 

  5. Alami Mchichi N, Mayer JRR (2014) Axis location errors and error motions calibration for a five-axis machine tool using the SAMBA method. Procedia CIRP 14:305–310

    Article  Google Scholar 

  6. Jiang Z, Bao S, Zhou X, Tang X, Zheng S (2015) Identification of location errors by a touch-trigger probe on five-axis machine tools with a tilting head. Int J Adv Manuf Technol. doi: 10.1007/s00170-015-7189-9

  7. Zhang Z, Hu H (2013) A general strategy for geometric error identification of multi-axis machine tools based on point measurement. Int J Adv Manuf Technol 69(5–8):1483–1497

    Article  Google Scholar 

  8. 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(9–12):2071–2082

    Article  Google Scholar 

  9. ISO 230-10:2011 standard: Test code for machine tools -- Part 10: Determination of the measuring performance of probing systems of numerically controlled machine tools. Geneva: International Organization for Standardization

  10. Cho MW, Seo TI (2002) Inspection planning strategy for the on-machine measurement process based on CAD/CAM/CAI integration. Int J Adv Manuf Technol 19(8):607–617

    Article  Google Scholar 

  11. Cho MW, Seo TI (2002) Machining error compensation using radial basis function network based on CAD/CAM/CAI integration concept. Int J Prod Res 40(9):2159–2174

    Article  MATH  Google Scholar 

  12. Cho MW, Seo TI, Kwon HD (2003) Integrated error compensation method using OMM system for profile milling operation. J Mater Process Technol 136(1–3):88–99

    Article  Google Scholar 

  13. Choi JP, Min BK, Lee SJ (2004) Reduction of machining errors of a three-axis machine tool by on-machine measurement and error compensation system. J Mater Process Technol 155–156:2056–2064

    Article  Google Scholar 

  14. Zeleny J, Janda M (2009) Automatic on-machine measurement of complex parts. Mod Mach Sci J (1):92–95

  15. Jankowski M, Woźniak A, Byszewski M (2014) Machine tool probes testing using a moving inner hemispherical master artifact. Precis Eng 38(2):421–427

    Article  Google Scholar 

  16. Estler WT, Phillips SD, Borchardt B, Hopp T, Levenson M, Eberhardt K, McClain M, Shen Y, Zhang X (1997) Practical aspects of touch-trigger probe error compensation. Precis Eng 21(1):1–17

    Article  Google Scholar 

  17. Estler WT, Phillips SD, Borchardt B, Hopp T, Witzgall C, Levenson M, Eberhardt K, McClain M, Shen Y, Zhang X (1996) Error compensation for CMM touch trigger probes. Precis Eng 19(2–3):84–96

    Google Scholar 

  18. Woźniak A, Dobosz M (2003) Metrological feasibilities of CMM touch trigger probes. Part I: 3D theoretical model of probe pretravel. Measurement 34(4):273–286

    Article  Google Scholar 

  19. Woźniak A, Dobosz M (2005) Influence of measured objects parameters on CMM touch trigger probe accuracy of probing. Precis Eng 29(3):290–297

    Article  Google Scholar 

  20. Sładek J, Gąska A (2012) Evaluation of coordinate measurement uncertainty with use of virtual machine model based on Monte Carlo method. Measurement 45(6):1564–1575

    Article  Google Scholar 

  21. Woźniak A, Byszewski M, Jankowski M (2013) Setup for triggering force testing of touch probes for CNC machine tools and CMMs. Meas Sci Rev 13(1):29–33

    Google Scholar 

  22. Lian F-L, Moyne JR, Tilbury DM (2000) Implementation of networked machine tools in reconfigurable manufacturing systems. In: 2000 Japan-USA Symposium on Flexible Automation, Ann Arbor, MI, USA, 23–26 July 2000

  23. Zhang H, Shi Y, Wang J (2014) On energy-to-peak filtering for nonuniformly sampled nonlinear systems: a Markovian jump system approach. IEEE Trans Fuzzy Syst 22(1):212–222

    Article  MathSciNet  Google Scholar 

  24. Zhang H, Wang J (2014) State estimation of discrete-time Takagi–Sugeno fuzzy systems in a network environment. IEEE Trans Cybern (epub ahead of print)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adam Wozniak.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wozniak, A., Jankowski, M. Wireless communication influence on CNC machine tool probe metrological parameters. Int J Adv Manuf Technol 82, 535–542 (2016). https://doi.org/10.1007/s00170-015-7374-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-015-7374-x

Keywords

Navigation