On-position Measurement Method for Position-error Compensation in Machining

Abstract

Due to requirements of high-precision geometric tolerances for some high precision products, forming errors and clamping errors are unavoidable in the machining process. In this paper, an on-position measurement method is proposed for position error compensation based on the combination datum theory. Firstly, the mathematical representation model of the coaxiality of parts with the shallow holes is constructed based on the combination datum theory. Secondly, an on-position measurement method is proposed with constructing the mathematical model of the profiles of the surfaces based on laser displacement sensors (LDSs) to calculate the coaxiality error of parts on-position based on the combination datum theory. Based on it, the position of the spindle of the machine are adjusted to present the clutter again to compensate for position errors of the holes. Finally, the experimental results demonstrate the effectiveness and correctness of the proposed position error compensation method based on the on-position measurement device.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

References

  1. 1.

    Anselmetti, B., & Louati, H. (2005). Generation of manufacturing tolerancing with ISO standards. International Journal of Machine Tools and Manufacture, 45(10), 1124–1131

    Article  Google Scholar 

  2. 2.

    Krulikowski, A. (1998). Fundamentals of geometric dimensioning and tolerancing. Nantwich: Delmar Publishers.

    Google Scholar 

  3. 3.

    Chen, W., Xue, J., Tang, D., Chen, H., & Qu, S. (2009). Deformation prediction and error compensation in multilayer milling processes for thin-walled parts. International Journal of Machine Tools and Manufacture, 49(11), 859–864

    Article  Google Scholar 

  4. 4.

    Badar, M. A., Raman, S., & Pulat, P. S. (2005). Experimental verification of manufacturing error pattern and its utilization in form tolerance sampling. International Journal of Machine Tools and Manufacture, 45(1), 63–73

    Article  Google Scholar 

  5. 5.

    Ngoi, B. K. A., Lim, L. E. N., Ong, A. S., & Lim, B. H. (1999). Applying the coordinate tolerance system to tolerance stack analysis involving position tolerance. International Journal of Advanced Manufacturing Technology, 15(6), 404–408

    Article  Google Scholar 

  6. 6.

    Li, Z.-L., Tuysuz, O., Zhu, L.-M., & Altintas, Y. (2018). Surface form error prediction in five-axis flank milling of thin-walled parts. International Journal of Machine Tools and Manufacture, 128, 21–32

    Article  Google Scholar 

  7. 7.

    Zhou, P., Zhao, X., Tao, B., & Ding, H. (2020). Time-varying isobaric surface reconstruction and path planning for robotic grinding of weak-stiffness workpieces. Robotics and Computer-Integrated Manufacturing, 64, 101945

    Article  Google Scholar 

  8. 8.

    Wang, L., & Hao, S. (2018). Machining deformation prediction of thin-walled workpieces in five-axis flank milling. International Journal of Advanced Manufacturing Technology, 97(9–12), 4179–4193

    Article  Google Scholar 

  9. 9.

    Pechard, P.-Y., Tournier, C., Lartigue, C., & Lugarini, J.-P. (2009). Geometrical deviations versus smoothness in 5-axis high-speed flank milling. International Journal of Machine Tools and Manufacture, 49(6), 454–461

    Article  Google Scholar 

  10. 10.

    Xie, F., Chen, L., Li, Z., & Tang, K. (2020). Path smoothing and feed rate planning for robotic curved layer additive manufacturing. Robotics and Computer-Integrated Manufacturing, 65, 101967

    Article  Google Scholar 

  11. 11.

    Fu, G., Fu, J., Xu, Y., Chen, Z., & Lai, J. (2015). Accuracy enhancement of five-axis machine tool based on differential motion matrix: Geometric error modeling, identification and compensation. International Journal of Machine Tools and Manufacture, 89, 170–181

    Article  Google Scholar 

  12. 12.

    Xiang, S., & Altintas, Y. (2016). Modeling and compensation of volumetric errors for five-axis machine tools. International Journal of Machine Tools and Manufacture, 101, 65–78

    Article  Google Scholar 

  13. 13.

    Ding, S., Huang, X., Yu, C., & Liu, X. (2016). Novel method for position-independent geometric error compensation of five-axis orthogonal machine tool based on error motion. International Journal of Advanced Manufacturing Technology, 83(5), 1069–1078

    Article  Google Scholar 

  14. 14.

    Habibi, M., Arezoo, B., & Vahebi Nojedeh, M. (2011). Tool deflection and geometrical error compensation by tool path modification. International Journal of Machine Tools and Manufacture, 51(6), 439–449

    Article  Google Scholar 

  15. 15.

    Chen, W. K., Kuriyagawa, T., Huang, H., & Yosihara, N. (2005). Machining of micro aspherical mould inserts. Precision Engineering, 29(3), 315–323

    Article  Google Scholar 

  16. 16.

    Chen, F. J., Yin, S. H., Huang, H., Ohmori, H., Wang, Y., Fan, Y. F., et al. (2010). Profile error compensation in ultra-precision grinding of aspheric surfaces with on-machine measurement. International Journal of Machine Tools and Manufacture, 50(5), 480–486

    Article  Google Scholar 

  17. 17.

    Landon, Y., Segonds, S., Lascoumes, P., & Lagarrigue, P. (2004). Tool positioning error (TPE) characterisation in milling. International Journal of Machine Tools and Manufacture, 44(5), 457–464

    Article  Google Scholar 

  18. 18.

    Chiou, J. C. J. (2004). Accurate tool position for five-axis ruled surface machining by swept envelope approach. Computer-Aided Design, 36(10), 967–974

    Article  Google Scholar 

  19. 19.

    Lamikiz, A., López de Lacalle, L. N., Ocerin, O., Díez, D., & Maidagan, E. (2008). The Denavit and Hartenberg approach applied to evaluate the consequences in the tool tip position of geometrical errors in five-axis milling centres. International Journal of Advanced Manufacturing Technology, 37(1), 122–139

    Article  Google Scholar 

  20. 20.

    Ong, T. S., & Hinds, B. K. (2003). The application of tool deflection knowledge in process planning to meet geometric tolerances. International Journal of Machine Tools and Manufacture, 43(7), 731–737

    Article  Google Scholar 

  21. 21.

    Li, Y., Surisetti, N. P., & Chen, J. C. (2013). Measuring external profiles of porous objects using CMM. International Journal of Advanced Manufacturing Technology, 64(5), 875–887

    Article  Google Scholar 

  22. 22.

    Ascione, R., & Polini, W. (2010). Measurement of nonrigid freeform surfaces by coordinate measuring machine. International Journal of Advanced Manufacturing Technology, 51(9), 1055–1067

    Article  Google Scholar 

  23. 23.

    Tian, Q., Yang, Y., Zhang, X., & Ge, B. (2014). An experimental evaluation method for the performance of a laser line scanning system with multiple sensors. Optics and Lasers in Engineering, 52, 241–249

    Article  Google Scholar 

  24. 24.

    Mahmud, M., Joannic, D., Roy, M., Isheil, A., & Fontaine, J.-F. (2011). 3D part inspection path planning of a laser scanner with control on the uncertainty. Computer-Aided Design, 43(4), 345–355

    Article  Google Scholar 

  25. 25.

    Wan, A., Song, L., Xu, J., Liu, S., & Chen, K. (2018). Calibration and compensation of machine tool volumetric error using a laser tracker. International Journal of Machine Tools and Manufacture, 124, 126–133

    Article  Google Scholar 

  26. 26.

    Bradley, C., & Chan, V. (2000). A complementary sensor approach to reverse engineering. Journal of Manufacturing Science and Engineering, 123(1), 74–82

    Article  Google Scholar 

  27. 27.

    Huang, N., Bi, Q., Wang, Y., & Sun, C. (2014). 5-Axis adaptive flank milling of flexible thin-walled parts based on the on-machine measurement. International Journal of Machine Tools and Manufacture, 84, 1–8

    Article  Google Scholar 

  28. 28.

    Song, T., Xi, F., Guo, S., Ming, Z., & Lin, Y. (2015). A comparison study of algorithms for surface normal determination based on point cloud data. Precision Engineering, 39, 47–55

    Article  Google Scholar 

  29. 29.

    Bi, Q., Huang, N., Zhang, S., Shuai, C., & Wang, Y. (2019). Adaptive machining for curved contour on deformed large skin based on on-machine measurement and isometric mapping. International Journal of Machine Tools and Manufacture, 136, 34–44

    Article  Google Scholar 

  30. 30.

    Zeng, W., Rao, Y., Wang, P., & Yi, W. (2017). A solution of worst-case tolerance analysis for partial parallel chains based on the Unified Jacobian-Torsor model. Precision Engineering, 47, 276–291

    Article  Google Scholar 

  31. 31.

    Miller, S. J. (2006). The method of least squares. Mathematics Department Brown University, 8, 1–7

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Wenhui Zeng.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zeng, W., Fang, F. & Ma, X. On-position Measurement Method for Position-error Compensation in Machining. Int. J. Precis. Eng. Manuf. 22, 1179–1189 (2021). https://doi.org/10.1007/s12541-021-00528-8

Download citation

Keywords

  • On-position measurement method
  • Position-error compensation
  • Combination datum theory
  • Laser displacement sensor