Skip to main content
Log in

Development of thermal error model with minimum number of variables using fuzzy logic strategy

  • Materials & Fracture · Solids & Structures · Dynamics & Control · Production & Design
  • Published:
KSME International Journal Aims and scope Submit manuscript

Abstract

Thermally-induced errors originating from machine tool errors have received significant attention recently because high speed and precise machining is now the principal trend in manufacturing processes using CNC machine tools. Since the thermal error model is generally a function of temperature, the thermal error compensation system contains temperature sensors with the same number of temperature variables. The minimization of the number of variables in the thermal error model can affect the economical efficiency and the possibility of unexpected sensor fault in a error compensation system. This paper presents a thermal error model with minimum number of variables using a fuzzy logic strategy. The proposed method using a fuzzy logic strategy does not require any information about the characteristics of the plant contrary to numerical analysis techniques, but the developed thermal error model guarantees good prediction performance. The proposed modeling method can also be applied to any type of CNC machine tool if a combination of the possible input variables is determined because the error model parameters are only calculated mathematically based on the number of temperature variables.

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

  • Bryan, J. B. 1990, “International Status of Thermal Error Research,”Annals of the CIRP, Vol. 39, No. 2, pp. 645–656.

    Article  MathSciNet  Google Scholar 

  • Fan, K. C, Lin, J. F. and Lu, S. S., 1992, “Measurement and Compensation of Thermal Error on a Machining Center,”29th MATADOR Conf, England, April, pp. 261–268.

  • Hatamura, Y., 1993, “Development of an Intelligent Machining Center Incorporating Active Compensation for Thermal Distortion,”Annals of the CIRP, Vol. 42, No. 1, pp. 549–552.

    Article  Google Scholar 

  • Horikawa, S., Furuhashi, T. and Uchikawa, Y., 1992, “On Fuzzy Modeling Using Fuzzy Neural Networks with the Back-Propagation Algorithm,”IEEE Trans, on Neural Networks, Vol. 3, No. 5, pp. 801–806.

    Article  Google Scholar 

  • Hwang, S. H., Lee, J. H. and Yang, S., 1999, “Optimal Variable Selection in a Thermal Error Model for Real Time Error Compensation,”Journal of the Korean Society of Precision Engineering, Vol. 16, No. 3, pp. 215–221. (in Korea)

    Google Scholar 

  • Ivakhnenko, A. G., 1971, “Polynomial Theory of Complex Systems,”IEEE Trans, on Systems, Man, and Cybernetics, Vol. SMC-1, No. 4, pp. 364–378.

    Article  MathSciNet  Google Scholar 

  • Lee, Jae-Ha, Lee, Jin-Hyeon and Yang, Seung -Han, 2000, “Thermal Error Modeling of a Horizontal Machining Center Using the Fuzzy Logic Strategy,”Transactions of the Korean Society of Mechanical Engineers, Vol. 24, No. 10, pp. 2589 -2596. (in Korea)

    Google Scholar 

  • Lee Jin-Hyeon and Yang, Seung-Han, 2001, “Statistical Optimization and Assessment of a Thermal Error Model for CNC Machine Tools,”Int. j. Mach. Tools’&l Manufact., Vol. 42, No. 1, pp. 147–155, 2001.

    Article  Google Scholar 

  • Moriwaki, T., 1988, “Thermal Deformation and its On-line Compensation of Hydrostatically Supported Precision Spindle,”Annals of the CIRP, Vol. 37, No. 1, pp. 283–286.

    Article  Google Scholar 

  • Soons, J. A., Spaan, H. A. and Schellekens, P. H., 1994, “Thermal Error Models for Software Compensation of Machine Tools,”Proc. 9th Ann. Meet. American Society for Precision Engineering, October, pp. 69–75.

  • Takagi, T. and Sugeno, M., 1983, “Derivation of Fuzzy Control Rules from Human Operator’s Control Actions,”Proc. of the IFAC Symposium on Fuzzy Information, Knowledge Representation, and Decision Analysis, Marseille, France, July, pp. 50–60.

  • Takagi, T. and Sugeno, M., 1985, “Fuzzy Identification of Systems and Its Applications to Modeling and Control,”IEEE Trans, on Systems, Man, and Cybernetics, Vol. SMC-15, No. 1, pp. 116–132.

    MATH  Google Scholar 

  • Tanaka, H., Uejima, S. and Asai, K., 1982, “A Linear Regression Analysis with Fuzzy Functions,”Journal of the Operations Research Society of Japan, Vol. 25, No. 2, pp. 162–174.

    MATH  Google Scholar 

  • Venugopal, R. and Barash, M., 1986, “Thermal Effect on the Accuracy of Numerically Controlled Machine Tool,”Annals of the CIRP, Vol. 35, No. 1, pp. 255–285.

    Article  Google Scholar 

  • Week, M. and Zangs, L., 1975, “Computing the Thermal Behavior of Machine Tools Using the Finite Element Method-Possibilities and Limitations,”Proceedings of the 16th MTDR Conference, Vol. 16, pp. 185–194.

    Google Scholar 

  • Yang, S., Yuan, J. Ni, J., 1996, “Accuracy Enhancement of a Horizontal Machining Center by Real-Time Error Compensation,”Journals of Manufacturing Systems, Vol. 15, No. 2, pp. 113 -118.

    Article  Google Scholar 

  • Yang, S., Yuan, J. and Ni, J., 1996, “The Improvement of Thermal Error Modeling and Compensation on Machine Tools by CMAC Neural Network,”Int. J. Mach. Tools & Manufact., Vol. 36, No. 4, pp. 527–537.

    Article  Google Scholar 

  • Zadeh, L. A., 1965, “Fuzzy Sets,”Information and Control, Vol. 8, pp. 338–353.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Seung-Han Yang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, JH., Lee, JH. & Yang, SH. Development of thermal error model with minimum number of variables using fuzzy logic strategy. KSME International Journal 15, 1482–1489 (2001). https://doi.org/10.1007/BF03185737

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03185737

Key Words

Navigation