Data Mining for Improving a Cleaning Process in the Semiconductor Industry

@inproceedings{Braha2001DataMF,
  title={Data Mining for Improving a Cleaning Process in the Semiconductor Industry},
  author={Dan Braha and Armin Shmilovici},
  year={2001}
}
As device geometry continues to shrink, micro-contaminants have an increasingly negative impact on yield. By diminishing the contamination problem, semiconductor manufacturers will significantly improve the wafer yield. This paper presents a comprehensive and successful application of data mining methodologies to the refinement of a new dry cleaning technology that utilizes a laser beam for the removal of micro-contaminants. Experiments with three classification-based data mining methods… CONTINUE READING
Highly Cited
This paper has 205 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 34 extracted citations

Data Mining for Optimizing IC Feature Designs to Enhance Overall Wafer Effectiveness

IEEE Transactions on Semiconductor Manufacturing • 2014
View 1 Excerpt

206 Citations

0204060'01'04'08'12'16
Citations per Year
Semantic Scholar estimates that this publication has 206 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 30 references

and E

M. Genut, B. Livshits, Y. Uziel, O. Tehar-Zahav
Iskevitch, “Laser removal of foreign materials from semiconductor wafers,” in Proc. SPIE, vol. 3274 • 1998
View 4 Excerpts
Highly Influenced

The Strength of Weak Learnability

Machine Learning • 1990
View 7 Excerpts
Highly Influenced

Linoff,Data Mining Techniques

G.M.J. Berry
1997
View 6 Excerpts
Highly Influenced

Machine Learning

T. M. Mitchell
New York: McGraw-Hill • 1997
View 6 Excerpts
Highly Influenced

and P

U. Fayyad, G. Piatetsky-Shapiro
Smyth, “From data mining to knowledge discovery: An overview,” inAdvances in Knowledge Discovery and Data Mining , U. Fayyad, G. Piatetsky-Shapiro, S. P. Amith, and R. Uthurusamy, Eds. Cambridge, MA: MIT Press • 1996
View 4 Excerpts
Highly Influenced

Semiconductor yield improvement: Results and best practices,

S. P. Cunningham, C. J. Spanos, K. Voros
IEEE Trans. Semiconduct. Manufact. , • 1995
View 4 Excerpts
Highly Influenced

Ed.,Data Mining for Design and Manufacturing: Methods and Applications

D. Braha
Armin Shmilovici received the M.Sc. degree in electronics engineering and the Ph.D. degree in industrial engineering • 2001
View 2 Excerpts

An overview of manufacturing yield and reliability modeling for semiconductors products,

W. Kuo, T. Kim
Proc. IEEE, • 1999
View 2 Excerpts

Laser , dry and plasmaless , photoresist removal

A. C. Tam, W. P. Leung, W. Zapka, W. Ziemlich
Solid State Technol . • 1998

Laser removal of foreign materials from semiconductor wafers

B. Livshits, O. Tehar-Zahav, E. Iskevitch, M. Genut
Proc . SPIE • 1998

Similar Papers

Loading similar papers…