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Experimental Investigation of Dynamic Errors in Coordinate Measuring Machines for High Speed Measurement

  • Younes Echerfaoui
  • Abderrazak El Ouafi
  • Ahmed Chebak
Regular Paper
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Abstract

Accuracy enhancement of coordinate measuring machine (CMM) by software compensation for geometric and thermal error has proved its effectiveness in the modern manufacturing. In some applications, measurement errors can be reduced by more than 70% when using error compensation. However, due to the demand for shorter cycle times of measurement tasks, CMMs are increasingly required to be used at high measuring velocity. In such conditions, dynamic errors will certainly have a much more influence on the measurement accuracy and constitutes a barrier to the reduction of measuring cycle time. This paper presents an experimental investigation of dynamic errors in CMMs. A structured experimental design and improved statistical analysis tools are combined to evaluate the measurement parameters effects at high measuring velocity. Carried out on a bridge type CMM, these parameters are combined and used to investigate the variation of several dynamic error attributes. A laser interferometer system is used to assess error components under different dynamic conditions. Based on these results, the contributions of each parameter in the variation of the dynamic error attributes are estimated revealing many options to consider for building an efficient prediction model for error compensation. Neural network based prediction model suggests a promising performance.

Keywords

Coordinate measuring machine High-speed measurement Dynamic errors Laser interferometer Design of experiments Error compensation 

NOMENCLATURE

MPE

Maximum positioning error

RPE

Residual positioning error

MAE

Maximum approaching error

RAE

Residual approaching error

% C

Percent contribution

F

Fisher test

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References

  1. 1.
    Hammad Mian, S. and Al-Ahmari, A., “New Developments in Coordinate Measuring Machines for Manufacturing Industries,” International Journal of Metrology & Quality Engineering, Vol. 5, No. 1, pp. 101–110, 2014.CrossRefGoogle Scholar
  2. 2.
    Hocken, R. J. and Pereira, P. H., “Coordinate Measuring Machines and Systems,” CRC Press, 2016.Google Scholar
  3. 3.
    Han, Z. Y., Jin, H. Y., Liu, Y. L., and Fu, H. Y., “A Review of Geometric Error Modeling and Error Detection for CNC Machine Tool,” Applied Mechanics and Materials, Vols. 303–306, pp. 627–631, 2013.CrossRefGoogle Scholar
  4. 4.
    Schwenke, H., Knapp, W., Haitjema, H., Weckenmann, A., Schmitt, R., and Delbressine, F., “Geometric Error Measurement and Compensation of Machines -An Update,” CIRP Annals, Vol. 57, No. 2, pp. 660–675, 2008.CrossRefGoogle Scholar
  5. 5.
    Mekid, S. and Ogedengbe, T., “A Review of Machine Tool Accuracy Enhancement through Error Compensation in Serial and Parallel Kinematic Machines,” International Journal of Precision Technology, Vol. 1, Nos. 3–4, pp. 251–286, 2010.CrossRefGoogle Scholar
  6. 6.
    Fan, J., Guan, J., Wang, W., Luo, Q., Zhang, X., and Wang, L., “A Universal Modeling Method for Enhancement the Volumetric Accuracy of CNC Machine Tools,” Journal of Materials Processing Technology, Vol. 129, Nos. 1–3, pp. 624–628, 2002.CrossRefGoogle Scholar
  7. 7.
    Aguado, S., Samper, D., Santolaria, J., and Aguilar, J. J., “Towards an Effective Identification Strategy in Volumetric Error Compensation of Machine Tools,” Measurement Science and Technology, Vol. 23, No. 6, Paper No. 065003, 2012.Google Scholar
  8. 8.
    Choi, J., Min, B., and Lee, S., “Reduction of Machining Errors of a Three-Axis Machine Tool by On-Machine Measurement and Error Compensation System,” Journal of Materials Processing Technology, Vol. 155, pp. 2056–2064, 2004.CrossRefGoogle Scholar
  9. 9.
    Zhang, Z., and Hu, H., “A General Strategy for Geometric Error Identification of Multi-Axis Machine Tools Based on Point Measurement,” The International Journal of Advanced Manufacturing Technology, Vol. 69, Nos. 5–8, pp. 1483–1497, 2013.CrossRefGoogle Scholar
  10. 10.
    Barakat, N., Elbestawi, M., and Spence, A., “Kinematic and Geometric Error Compensation of a Coordinate Measuring Machine,” International Journal of Machine Tools and Manufacture, Vol. 40, No. 6, pp. 833–850, 2000.CrossRefGoogle Scholar
  11. 11.
    Tan, K. K., Huang, S. N., Lim, S. Y., Leow, Y. P., and Liaw, H. C., “Geometrical Error Modeling and Compensation Using Neural Networks,” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), Vol. 36, No. 6, pp. 797–809, 2006.CrossRefGoogle Scholar
  12. 12.
    Zhu, S., Ding, G., Qin, S., Lei, J., Zhuang, L., and Yan, K., “Integrated Geometric Error Modeling, Identification and Compensation of CNC Machine Tools,” International Journal of Machine Tools and Manufacture, Vol. 52, No. 1, pp. 24–29, 2012.CrossRefGoogle Scholar
  13. 13.
    Kruth, J.-P., Vanherck, P., and Van Den Bergh, C., “Compensation of Static and Transient Thermal Errors on CMMs,” CIRP Annals-Manufacturing Technology, Vol. 50, No. 1, pp. 377–380, 2001.CrossRefGoogle Scholar
  14. 14.
    Ramesh, R., Mannan, M., and Poo, A., “Error Compensation in Machine Tools -A Review: Part II: Thermal Errors,” International Journal of Machine Tools and Manufacture, Vol. 40, No. 9, pp. 1257–1284, 2000.CrossRefGoogle Scholar
  15. 15.
    Yang, H. and Ni, J., “Dynamic Modeling for Machine Tool Thermal Error Compensation,” Journal of Manufacturing Science and Engineering, Vol. 125, No. 2, pp. 245–254, 2003.CrossRefGoogle Scholar
  16. 16.
    De Nijs, J., Lammers, M., Schellekens, P., and Van der Wolf, A., “Modelling of a Coordinate Measuring Machine for Analysis of Its Dynamic Behaviour,” CIRP Annals-Manufacturing Technology, Vol. 37, No. 1, pp. 507–510, 1988.CrossRefGoogle Scholar
  17. 17.
    Ricciardi, G., Borsati, L., and Micheletti, G., “Theoretic and Experimental Methodologies for Increasing Dynamic Performances of General Purpose Robots and Measuring Machines,” CIRP Annals-Manufacturing Technology, Vol. 34, No. 1, pp. 375–379, 1985.CrossRefGoogle Scholar
  18. 18.
    Weekers, W. G. and Schellekens, P. H. J., “Assessment of Dynamic Errors of CMMs for Fast Probing,” CIRP Annals-Manufacturing Technology, Vol. 44, No. 1, pp. 469–474, 1995.CrossRefGoogle Scholar
  19. 19.
    Dong, C., Zhang, C., Wang, B., and Zhang, G., “Prediction and Compensation of Dynamic Errors for Coordinate Measuring Machines,” Journal of Manufacturing Science and Engineering, Vol. 124, No. 3, pp. 509–514, 2002.CrossRefGoogle Scholar
  20. 20.
    Dong, C., Zhang, C., Wang, B., and Zhang, G., “Prediction and Compensation of Dynamic Errors for Coordinate Measuring Machines,” Journal of Manufacturing Science and Engineering, Vol. 124, No. 3, pp. 509–514, 2002.CrossRefGoogle Scholar
  21. 21.
    Dong, C., Zhang, C., Wang, B., and Zhang, G., “Reducing the Dynamic Errors of Coordinate Measuring Machines,” Journal of Mechanical Design, Vol. 125, No. 4, pp. 831–839, 2003.CrossRefGoogle Scholar
  22. 22.
    Mu, Y. H. and Ngoi, B. K. A., “Dynamic Error Compensation of Coordinate Measuring Machines for High-Speed Measurement,” The International Journal of Advanced Manufacturing Technology, Vol. 15, No. 11, pp. 810–814, 1999.CrossRefGoogle Scholar
  23. 23.
    Pereira, P. H. and Hocken, R. J., “Characterization and Compensation of Dynamic Errors of a Scanning Coordinate Measuring Machine,” Precision Engineering, Vol. 31, No. 1, pp. 22–32, 2007.CrossRefGoogle Scholar
  24. 24.
    Weekers, W. G. and Schellekens, P. H. J., “Compensation for Dynamic Errors of Coordinate Measuring Machines,” Measurement, Vol. 20, No. 3, pp. 197–209, 1997.CrossRefGoogle Scholar
  25. 25.
    Chang, D. and Spence, A., “CMM Dynamic Error Analysis, Control and Compensation,” Proc. of the American Society for Precision Engineering Annual Meeting, 2007.Google Scholar
  26. 26.
    Laser Automated Precision Inc., “Measuring All 6 Degrees of Freedom -XD Laser” https://www.apisensor.com/measuring-6-degrees-freedom-xd-laser-automated-precision-inc/(Accessed 9 JUL 2018)
  27. 27.
    Montgomery, D. C., “Design and Analysis of Experiments,” John Wiley & Sons, 2017.Google Scholar
  28. 28.
    Huang, S. H. and Zhang, H.-C., “Artificial Neural Networks in Manufacturing: Concepts, Applications, and Perspectives,” IEEE Transactions on Components, Packaging, and Manufacturing Technology: Part A, Vol. 17, No. 2, pp. 212–228, 1994.MathSciNetCrossRefGoogle Scholar
  29. 29.
    Meireles, M. R., Almeida, P. E., and Simões, M. G., “A Comprehensive Review for Industrial Applicability of Artificial Neural Networks,” IEEE Transactions on Industrial Electronics, Vol. 50, No. 3, pp. 585–601, 2003.CrossRefGoogle Scholar
  30. 30.
    Dagli, C. H., “Artificial Neural Networks for Intelligent Manufacturing,” Springer Science & Business Media, 2012.Google Scholar

Copyright information

© Korean Society for Precision Engineering and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mathematics, Computer and EngineeringUniversity of Quebec at RimouskiRimouskiCanada

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