Skip to main content

Advertisement

Log in

A method for tracing key geometric errors of vertical machining center based on global sensitivity analysis

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

Abstract

This paper proposes a method for tracing key geometric errors of vertical machining centers based on global sensitivity analysis in order to address inconsistent dimensions associated with sensitivity coefficients, random analytical variables, and geometric errors across different positions. The kinematic chain forward solution and the volumetric error model of vertical machining centers based on a global coordinate system is constructed by means of screw theory; the identification model is constructed based on the double bar ball measurement principle. The identification model is transformed into an optimization-design problem, which is solved by a simulated annealing–genetic algorithm. The idea of orthogonal experimental design is used for reference, and 25 test points are selected for the machine tool workspace. By taking the volumetric error model as a sensitivity calculation model, and by taking geometric errors as analytical factors, multi-factor orthogonal experiments and single-factor parametric tests are designed, respectively. The F-values of the significance test results of the orthogonal experiments and the Euclidean norms, ∆P and ∆O, of the parametric test results are used as global sensitivity coefficients. The analysis results suggest that the traceability results of the key geometric errors are essentially the same across the two tests and the 13 key geometric errors of the J1VMC400B vertical machining center are traced.

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.

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

Similar content being viewed by others

References

  1. Vahebi M, Arezoo B (2018) Accuracy improvement of volumetric error modeling in CNC machine tools. Int J Adv Manuf Technol 95:2243–2257

    Article  Google Scholar 

  2. Wang L, Tian W, Yang G, Yin F, Gao W (2018) The application of a regularization method to the estimation of geometric errors of a three-axis machine tool using a double ball bar. J Mech Sci Technol 32:4871–4881

    Article  Google Scholar 

  3. Cheng Q, Sun B, Liu Z, Li J, Dong X (2017) Key geometric error extraction of machine tool based on extended Fourier amplitude sensitivity test method. Int J Adv Manuf Technol 90:3369–3385

    Article  Google Scholar 

  4. Yang J, Altintas Y (2015) A generalized on-line estimation and control of five-axis contouring errors of CNC machine tools. Int J Mach Tool Manu 88:9–23

    Article  Google Scholar 

  5. Zhang Z, Liu Z, Cai L, Cheng Q, Qi Y (2017) An accuracy design approach for a multi-axis NC machine tool based on reliability theory. Int J Adv Manuf Technol 91:1547–1566

    Article  Google Scholar 

  6. Xiang S (2016) Volumetric error measuring and compensation technique for five-axis machine tools. Shanghai Jiao Tong University, Dissertation

    Google Scholar 

  7. Tian W (2014) Investigation into accuracy design and error compensation of high-precision horizontal machining centers. Tianjin University, Dissertation

    Google Scholar 

  8. Gu P, Lasemi A, Xue D (2016) Accurate identification and compensation of geometric errors of 5-axis CNC machine tools using double ball bar. Meas Sci Technol 27:55001–55004

  9. Cheng Q, Zhao H, Zhang G, Gu P, Cai L (2014) An analytical approach for crucial geometric errors identification of multi-axis machine tool based on global sensitivity analysis. Int J Adv Manuf Technol 75:107–121

    Article  Google Scholar 

  10. Wu J, Gu C, Du Z, Yang J (2018) Identification of key component errors in vertical machine center. J Mach Des Res 34(2018):81–84

  11. Aguilar JJ, Velazquez J, Aguado S, Santolaria J, Samper D (2016) Improving a real milling machine accuracy through an indirect measurement of its geometric errors. J Manuf Syst 40:26–36

    Article  Google Scholar 

  12. Wang WQ, Wu HQ (2013) Sensitivity analysis of geometric errors for five-axis CNC machine tool based on multi-body system theory. Appl Mech Mater 2181:493–497

    Google Scholar 

  13. Tang Y, Fan J, Chen D, Yuan S (2017) Tracing method for key geometric errors of a machine tool based on Monte Carlo simulation. J B Univ Technol 43:1619–1628

  14. Abdessalem AB, El-Hami A (2014) Global sensitivity analysis and multi-objective optimisation of loading path in tube hydroforming process based on metamodelling techniques. Int J Adv Manuf Technol 71:753–773

    Article  Google Scholar 

  15. Lagerwall G, Kiker G, Oz-Carpena RM, Wang N (2014) Global uncertainty and sensitivity analysis of a spatially distributed ecological model. Ecol Model 275:22–30

    Article  Google Scholar 

  16. Cheng Q, Gu P, Feng Q, Zhang G, Liu Z (2016) Sensitivity analysis of machining accuracy of multi-axis machine tool based on POE screw theory and Morris method. Int J Adv Manuf Technol 84:2301–2318

    Article  Google Scholar 

  17. Lee K, Yang S (2016) Compensation of position-independent and position-dependent geometric errors in the rotary axes of five-axis machine tools with a tilting rotary table. Int J Adv Manuf Technol 85:1677–1685

    Article  Google Scholar 

  18. Tian W, Guo L, Liu H (2016) Rapid identification method for geometric errors of CNC machine tools. J Tianjin Univ (Sci Technol) 49(2016):171–177

  19. Fan K, Yang J, Yang L (2013) Orthogonal polynomials-based thermally induced spindle and geometric error modeling and compensation. Int J Adv Manuf Technol 65:1791–1800

    Article  Google Scholar 

  20. Chen S (2016) Research on the geometric error measurement method of the numerical control machine tools based on twelve line. Huazhong University of Science & Technology, Dissertation

    Google Scholar 

  21. Li J, Xie F, Liu X, Li W, Zhu S (2016) Geometric error identification and compensation of linear axes based on a novel 13-line method. Int J Adv Manuf Technol 87:2269–2283

    Article  Google Scholar 

  22. Zhu SW, Ma SW, Yan KY, Ding GF, Qin SF (2013) Workpiece locating error prediction and compensation in fixtures. Int J Adv Manuf Technol 67:1423–1432

    Article  Google Scholar 

  23. Nojehdeh MV, Arezoo B (2016) Functional accuracy investigation of work-holding rotary axes in five axis CNC machine tools. Int J Mach Tool Manu 111:17–30

    Article  Google Scholar 

  24. Ibaraki S, Matsushita T, Iritani 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 Tool Manu 68:21–29

    Article  Google Scholar 

  25. Jalaludin AH, Abd Shukor MH, Mardi NA, Sarhan AADM, Ab Karim MS, Besharati SR, Badiuzaman WNIW, Dambatta YS (2017) Development and evaluation of the machining performance of a CNC gantry double motion machine tool in different modes. Int J Adv Manuf Technol 93:1347–1356

    Article  Google Scholar 

  26. Yang J (2015) Five-axis motion control modeling and accuracy improvement study. Huazhong University of Science & Technology, Doctor of Philosophy in Engineering Wuhan

    Google Scholar 

  27. Hui S (2010) Multi-objective optimization for hydraulic hybrid vehicle based on adaptive simulated annealing genetic algorithm. Engineering Applications of Artificial Intelligence: Int J Intel Real-Time Auto 23:27–33

    Article  Google Scholar 

  28. Zong Y, Cui J (2018) Application of simulated annealing genetic algorithm in manipulator’s trajectory planning. Meas Contr Technol 37:1–5

  29. ISO 230-1:2012 Test code for machine tools-part 1: geometric accuracy of machines operating under no-load or quasi-static conditions[S]. 2012

  30. ISO 230-4:2005 Test code for machine tools-part 4: circular tests for numerically controlled machine geuhge[S].

  31. Liu J, Hong Y (2016) Analysis and robust design of geometric accuracy of a three-axis CNC surface grinding machine. J Hunan Univ: Nat Sci Ed 43:1–8

Download references

Funding

This study was financially supported by the National Science and Technology Major Project of China (2015ZX04005004).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hualin Zheng.

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, H., Zheng, H., Wang, W. et al. A method for tracing key geometric errors of vertical machining center based on global sensitivity analysis. Int J Adv Manuf Technol 106, 3943–3956 (2020). https://doi.org/10.1007/s00170-019-04876-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-019-04876-8

Keywords

Navigation