CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Using Discrete Wavelet analysis and Sequential test to detect the endpoint in CMP process

by Sihem Ben Zakour, Hassen Taleb
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 12
Year of Publication: 2012
Authors: Sihem Ben Zakour, Hassen Taleb
10.5120/5747-7953

Sihem Ben Zakour, Hassen Taleb . Using Discrete Wavelet analysis and Sequential test to detect the endpoint in CMP process. International Journal of Computer Applications. 42, 12 ( March 2012), 33-40. DOI=10.5120/5747-7953

@article{ 10.5120/5747-7953,
author = { Sihem Ben Zakour, Hassen Taleb },
title = { Using Discrete Wavelet analysis and Sequential test to detect the endpoint in CMP process },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 12 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 33-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number12/5747-7953/ },
doi = { 10.5120/5747-7953 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:31:09.585287+05:30
%A Sihem Ben Zakour
%A Hassen Taleb
%T Using Discrete Wavelet analysis and Sequential test to detect the endpoint in CMP process
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 12
%P 33-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Due to the development in new technologies like semiconductor industry, with advances in sensors and information technology oblige us to handle with large datasets do not stop increasing, while monitoring devices are becoming more and more complexes and sophisticated. As the measurement points become closer. Among the complex monitoring process, the detection of the end of polishing (EPD) during the chemical mechanical planarization (CMP) process is considered as a critical task in semiconductor manufacturing. In this paper, an Acoustic emission (AE) signal is collected during the progression of the CMP process will be monitored using an online method in which the signal will be preprocessed using wavelet analysis (WA) to clean the data from noise and at the same time, a sequential probability ratio test (SPRT) will be developed. This test was applied to the wavelet decomposed. Eventually, it has shown to be efficient in controlling complex processes and suitable for real-time application by developing a moving block strategy.

References
  1. Joseph M. Steigerwald, Sgyam P. Murarka and Ronald J. Gutma, 1997, Chemical Mechanical Planarization of Microelectronic.
  2. P. B. Zantye, A. Kumar, and A. K. Sikder, 2004, Chemical mechanical planarization for microelectronics applications, Mater. Sci. Eng. R. Rep. , vol. 45, nos. 3–6, pp. 89–220.
  3. W. Lih, S. T. S. Bukkapatnam, P. Rao, N. Chandrasekaran, and R. Komanduri, 2008, Adaptive neuro-fuzzy inference system modeling of MRR and WIWNU in CMP process with sparse experimental data, IEEE Trans. Autom. Sci. Eng. , vol. 5, no. 1, pp. 71–83.
  4. S. Bukkapatnam, P. Rao, and R. Komanduri, 2008, Experimental dynamics characterization and monitoring of MRR in oxide chemical mechanical planarization (CMP) process, Int. J. Mach. Tools Manuf. , vol. 48.
  5. U. Phatak, S. Bukkapatnam, Z. Kong, N. Chandrasekaran, S. Varghese, and R. Komanduri, 2009, Sensor based modeling of slurry chemistry effects on MRR in copper CMP, Int. J. Mach. Tools Manuf. , vol. 49, no. 2, pp. 171–181.
  6. Ramsay, J. O. and Dalzell, C , 1991, Some tools for functional data analysis (with discussion), Journal of the Royal Statistical Society 53.
  7. Lu´?s Aguiar-Conraria , Pedro C. Magalha˜es Maria Joana Soares, 2012, Cycles in Politics:Wavelet Analysis of Political Time Series, American Journal of Political Science,
  8. Gustavo Didiera and Vladas Pipiras, 2010, Adaptive wavelet decompositions of stationary time series, journal of time series.
  9. Steffen Unkel, C. Paddy Farrington and Paul H. Garthwaite, 2012, infectious disease outbreaks: a review, J. R. Statist. 1, pp. 49–82.
  10. S. Ker,Y. Le Gonidec, D. Gibert and B. Marsset, 2011, Multiscale seismic attributes: a wavelet-based method and its application to high-resolution seismic and ground truth data, Geophys. J. Int.
  11. Hongyun Wang, Zhengshang Da, Baiyu Liu and Hui Liu, 2012, Investigation of the arbitrary waveform semiconductor laser as seed light source for high energy laser, Microwave and Optical Technology Letters, Volume 54, Issue 3, pages 751–755.
  12. Mallat, S. G. , 1989, Multiresolution approximations and wavelet orthonormal bases, Transactions of the American Mathematical Society,315(1), 6987.
  13. Daubechies, I , 1990, The Wavelet Transform, Time-Frequency Localization and Signals Analysis, IEEE Transactions on Information Theory, Vol. 36.
  14. Meyer, Y. , 1993, Wavelets: Algorithms and Applications, SIAM, Philadelphia, PA. .
  15. Calderon A. P. , 1964, Intermediate spaces and interpolation, the complex method, Studia Math. 24.
  16. Donoho, D. L. and Johnstone, I. M. , 1994, Ideal spatial adaptation by wavelet shrinkage, Biometrica, 81, 425455.
  17. Donoho,D. L. and Johnstone, I. M. , 1995, Adapting to unknownsmoothness via wavelet shrinkage, Journal of the American Statistical Association, 90(432), 12001224.
  18. Donoho,D. L. , Johnstone, I. M. ,Kerkyacharian,G. and Picard,D. , 1995, Wavelet shrinkage: asymptopia (with discussion), Journal of the Royal Statistical Society, 57(2), 301369.
  19. Donoho, D. L. and Johnstone, I. M. , 1998, Minimax estimation via wavelet shrinkage, The Annals of Statistics, 26, 879921.
  20. Wald A. (1973) Sequential analysis, Dover, New York.
  21. Ganesan R. , A. N. V. Rao, and Das T. , 2008), A Multiscale Bayesian SPRT Approach for Online Process Monitoring, IEEE transactions on semiconductor manufacturing, VOL. 21, NO. 3.
Index Terms

Computer Science
Information Sciences

Keywords

Sequential Probability Ratio Test (sprt) End Point Detection (epd) Chemical Mechanical Planarization (cmp) Acoustic Emission (ae) Wavelet Analysis (wa) Monitoring Process

Powered by PhDFocusTM