Advertisement

AMST ’99 pp 197-206 | Cite as

Grind-Hardening Modeling with the Use of Neural Networks

  • K. Tsirbas
  • D. Mourtzis
  • S. Zannis
  • G. Chryssolouris
Part of the International Centre for Mechanical Sciences book series (CISM, volume 406)

Abstract

This paper describes the modeling procedure and results of a non-conventional process, called grind-hardening. The main idea of the grind-hardening process is that the heat dissipation in the cutting area is used for the heat treatment of the workpiece. Grind hardening is a complex manufacturing process governed by a multiplicity of parameters.

In order to satisfy the need for industrial exploitation of the process, it must first be thoroughly investigated and optimized. This goal can be achieved by efficient modeling. For this purpose, artificial intelligence methods were used, namely Neural Networks. This advanced simulation method is highly efficient in the case when relationships among parameters are non-linear, which is the case in grind-hardening.

The case studied in this paper is a double-face grind-hardening process. The part in question is a punched disk simultaneously ground and hardened on both sides. Quantitative and qualitative parameters are used to describe the process. The qualitative parameters are modeled using vector representation. Experimental data taken from this process are used to train the network.

After the network training stage has been completed, the network is then used to determine the impact of the process parameters on the working result, namely the surface hardness on both sides of the part. The network results, concerning the level of accuracy of its predictions for different combinations of process parameters, have been obtained and evaluated as satisfactory.

Key Words

Grind-Hardening Neural Networks Process Modeling & Simulation. 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Toenshoff, H.K., J. Peters, I. Inasaki and T. Paul: Modeling and Simulation of Grinding Processes, 1992, CIRP Annals, V. 41 n. 2: 677–688.Google Scholar
  2. 2.
    Brinksmeier E., H.K. Toenshoff, I. Inasaki: Basic Parameters in Grinding, 1993, Annals of the CIRP, Vol 42.Google Scholar
  3. 3.
    Rowe, W.B., Li, Y., Inasaki, I., Malkin S.: Applications of Artificial Intelligence in Grinding, 1994, ClRP Annals, V. V. 43/2: 1–11.Google Scholar
  4. 4.
    Rowe, W.B., Y. Li, X. Chen and B. Mills: An Intelligent Multiagent Approach for Selection of Grinding Conditions, 1997, CIRP Annals, V. 46 n. 1: 233–236.Google Scholar
  5. 5.
    Chryssolouris G.: A comparison of statistical & AI approaches to the selection of process parameters in intelligent machining, May 1990, Transactions of the ASME-Journal of Engineering for Industry, vol. 112, pp 122–131.Google Scholar
  6. 6.
    Leem, C. S., Domfeld, D. A., Dreyfus, S. E.: A customized neural network for sensor fusion in on-line monitoring of cutting tool wear, May 1995, Transactions of the ASME-Journal of Engineering for Industry, vol. 117, pp 152–159.Google Scholar
  7. 7.
    Rangwala S., D. Dornfeld: Sensor Integration Using Neural Networks for Intelligent Tool Condition Monitoring, Journal of Engineering for Industry, August 1990, Vol 112.Google Scholar
  8. 8.
    Chryssolouris G., M. Lee, J.Pierce, M. Domroese: Use of Neural Networks for the design of Manufacturing Systems, Manufacturing Review, Vol 3, September 1990.Google Scholar
  9. 9.
    Sakakura M., I. Inasaki: A neural network approach to the decision-making process for grinding operations, 1992, Annals of the CIRP Vol. 41.Google Scholar
  10. 10.
    Fan, H. T., Wu, S. M.: Case studies on modeling manufacturing processes using artificial neural networks, August 1995, Transactions of the ASME-Journal of Engineering for Industry, vol. 117, pp 412–417.Google Scholar
  11. 11.
    Schutz G., D. Fichtner, A. Nestler, J. Hoffman: An Intelligent Tool for the Determination of Cutting Values based on Neural Networks.Google Scholar
  12. 12.
    Brinksmeier E.: Utilization of grinding heat as a new heat treatment process, 1996, Annals of the CIRP Vol. 45.Google Scholar
  13. 13.
    Chryssolouris G.: Manufacturing Systems Theory & Practice, 1992, Springer Verlag, New York, pp 275–276 & 306–311.Google Scholar

Copyright information

© Springer-Verlag Wien 1999

Authors and Affiliations

  • K. Tsirbas
    • 1
  • D. Mourtzis
    • 1
  • S. Zannis
    • 1
  • G. Chryssolouris
    • 1
  1. 1.University of PatrasPatrasGreece

Personalised recommendations