Skip to main content
SpringerLink
Log in

Fault detection of cycle-based signals using wavelet transform in FAB processes

  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

This paper presents a wavelet multiresolution analysis based process fault detection algorithm to improve the accuracy of fault detection. Using Haar wavelet, coefficients that well reflect the process condition are selected and Hotelling’s T2 control chart that uses the selected coefficients is constructed for assessing the process condition. To enhance the overall efficiency and accuracy of fault detection, the following two steps are suggested: First, a denoising method that is based on wavelet transform and soft-thresholding. Second, coefficient selection methods that use the difference in the variance. For performance evaluation, various types of abnormal process conditions are simulated and the proposed algorithm is compared with other methodologies. Also, We apply the proposed algorithm to the industrial data of the dry etching process, which is one of the FAB processes. Our method has a better fault-detection performance for various sections and various changes in mean than other methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Misra, M., “Novel Techniques for Real-time and Predictive FDC Systems,” Future Lab Intl., Issue 22, 2007.

  2. Shi, J. and Jin, J., “Diagnostic feature extraction from stamping tonnage signals based on design of experiments,” Journal of Manufacturing Science and Engineering, Vol. 122, No. 22, pp. 360–369, 2000.

    Google Scholar 

  3. Zhou, S. and Jin, J., “Automatic feature selection for unsupervised clustering of cycle-based signals in manufacturing processes,” IIE Transactions, Vol. 37, No. 6, pp. 569–584, 2005.

    Article  Google Scholar 

  4. Bakshi, B. R., “Multiscale PCA with application to multivariate statistical process monitoring,” AIChE Journal, Vol. 44, No. 7, pp. 1596–1610, 1998.

    Article  Google Scholar 

  5. Koh, C. K. H., Shi, J., Williams, W. J. and Ni, J., “Multiple fault detection and isolation using the haar transform, Part 1: Theory,” Journal of Manufacturing Science and Engineering, Vol. 121, No. 2, pp. 290–294, 1999.

    Article  Google Scholar 

  6. Koh, C. K. H., Shi, J., Williams, W. J. and Ni, J., “Multiple fault detection and isolation using the haar transform, Part 2: Application to the stamping Process,” Journal of Manufacturing Science and Engineering, Vol. 121, No. 2, pp. 295–299, 1999.

    Article  Google Scholar 

  7. Jeong, M. K., Lu, J. C. and Wang, N., “Wavelet-based SPC procedure for complicated functional data,” International Journal of Production Research, Vol. 44, No. 4, pp. 729–744, 2006.

    Article  MATH  Google Scholar 

  8. Zhou, S., Sun, B. and Shi, J., “An SPC monitoring system for cycle-based waveform signals using haar transform,” IEEE Transactions on Automation Science and Engineering, Vol. 3, No. 1, pp. 60–72, 2006.

    Article  Google Scholar 

  9. Jin, J. and Shi, J., “Automatic feature extraction of waveform signals for in-process diagnostic performance improvement,” Journal of Intelligent Manufacturing, Vol. 12, No. 3, pp. 267–268, 2001.

    Article  Google Scholar 

  10. Donoho, D. L., “Denoising by soft thresholding,” IEEE Transactions on Information Theory, Vol. 41, No. 3, pp. 613–627, 1995.

    Article  MATH  MathSciNet  Google Scholar 

  11. Burrus, C. S., Gopinath, R. A. and Guo, H., ”Introduction to Wavelets and Wavelet Transforms: A Primer,” Prentice-Hall, pp. 31–40, 1997.

  12. Burt, P. J. and Adelson, E. H., “The Laplacian pyramid as a compact image code,” IEEE Transactions on Communications, Vol. 31, No. 4, pp. 532–540, 1983.

    Article  Google Scholar 

  13. Donoho, D. L. and Johnstone, I. M., “Ideal spatial adaptation by wavelet shrinkage,” Biometrika, Vol. 81, No. 3, pp. 425–455, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  14. Ganesan, R., Das, T. K. and Venkataraman, V., “Wavelet-based multiscale statistical process monitoring: A literature review,” IIE Transactions, Vol. 36, No. 9, pp. 787–806, 2004.

    Article  Google Scholar 

  15. Nounou, M. N. and Bakshi, B. R., “On-line multiscale filtering of random and gross errors without process models,” AIChE Journal, Vol. 45, No. 5, pp. 1041–1058, 1999.

    Article  Google Scholar 

  16. Montgomery, D. C., ”Introduction to Statistical Quality Control, 5th Edition,” John Wiley & Sons, pp. 486–541, 2004.

  17. Jeong, H. C., Choi, G. M. and Kim, D. J., “The Precision of Lead Frame Etching Characteristics Using Monte-Carlo Simulations,” Int. J. Precis. Eng. Manuf., Vol. 8, No. 1, pp. 73–78, 2007.

    Google Scholar 

  18. Zhang, J. F., Wang, B. and Dong, S., “Analysis of Factors Impacting Atmospheric Pressure Plasma Polishing,” Int. J. Precis. Eng. Manuf., Vol. 9, No. 2, pp. 39–43, 2008.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Information Management Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul, South Korea, 136-701

    Jun Seok Kim, Jun-Geol Baek & Sung-Shick Kim

  2. E-LAND, Changjeon-dong, Mapo-gu, Seoul, South Korea, 121-751

    Jae Hyun Lee

  3. College of Business Administration, Kwangwoon University, Wolgye-dong, Nowon-gu, Seoul, South Korea, 139-701

    Ji-Hyun Kim

Authors
  1. Jun Seok Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jae Hyun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ji-Hyun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jun-Geol Baek
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sung-Shick Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jun-Geol Baek.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, J.S., Lee, J.H., Kim, JH. et al. Fault detection of cycle-based signals using wavelet transform in FAB processes. Int. J. Precis. Eng. Manuf. 11, 237–246 (2010). https://doi.org/10.1007/s12541-010-0027-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-010-0027-y

Keywords

Search

Navigation