Abstract
Wafer fabrication for semiconductor manufacturing consists of multiple layers, in which the displacements (i.e., overlay errors) between layers should be reduced to enhance the yield. Although it can reduce variance between layers by fixing the exposure machine (i.e. steeper or scanner), it is not practical to expose the wafer on the same machine from layer to layer for the lengthy fabrication process in real setting. Thus, there is a critical need to determine the similarity machine subgroups, in which appreciate backups for unexpected machine down can be also prioritized. This study aims to develop a novel methodology to fill this gap based on the proposed similarity measurement of systematic overlay errors and residuals. The proposed methodology was validated via empirical study in a wafer fab and the results showed practical viability of this approach.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
K.S. Al-Sultan (1997) ArticleTitleHard clustering approach to the part family formation problem Production Planning and Control 8 IssueID3 231–236 Occurrence Handle10.1080/095372897235280
K.S. Al-Sultan C.A. Fedjki (1997) ArticleTitleGenetic algorithm for the part family formation problem Production Planning and Control 8 IssueID8 788–796 Occurrence Handle10.1080/095372897234687
M.R. Anderberg (1973) Cluster analysis for applications Academic Press New York
W.H. Arnold (1983) ArticleTitleImage placement differences between 1:1 projection aligners and 10:1 reduction wafer steppers Proceedings of SPIE: Optical Microlithography 394 87–98
D. Ben-Arieh E. Traintaphyllou (1992) ArticleTitleQuantifying data for group technology with weighted fuzzy features International Journal of Production Research 30 IssueID6 1285–1299
H.M. Chan D.A. Milner (1982) ArticleTitleDirect clustering algorithm for group formation in cellular manufacturing Journal of Manufacturing systems 1 IssueID1 65–74
M.P. Chandrasekharan R. RajaGopalan (1986) ArticleTitleAn ideal seed non-hierarchical clustering algorithm for cellular manufacturing International Journal of Production Research 24 IssueID2 451–464
C. Chien S. Hsu J. Deng (2001) ArticleTitleA cutting algorithm for optimizing the wafer exposure pattern IEEE Transactions on Semiconductor Manufacturing 14 IssueID2 157–162 Occurrence Handle10.1109/66.920727
C. Chien D. Lin Q. Liu C. Peng C. Hsu C. Huang (2002) ArticleTitleDeveloping a data mining method for wafer binmap clustering and an empirical study in a semiconductor manufacturing fab Journal of the Chinese Institute of Industrial Engineers 19 IssueID2 23–38 Occurrence Handle10.1080/10170660209509189
C. Chien K. Chang C. Chen (2003) ArticleTitleDesign of a sampling strategy for measuring and compensating for overlay errors in semiconductor manufacturing International Journal of Production Research 41 IssueID11 2547–2561 Occurrence Handle10.1080/0020754031000087256
C. Chien J. Wu (2003) ArticleTitleAnalyzing repair decisions in the site imbalance problem of semiconductor test machines IEEE Transactions on Semiconductor Manufacturing 16 IssueID4 704–711 Occurrence Handle10.1109/TSM.2003.818955
Johnson, R. A., Wichern, D. W. (1992). applied multivariate statistical analysis, 3rd edn. Englewood Cliffs, New Jersey: Prentice Hall.
S. Kamal L.I. Burke (1996) ArticleTitleFACT: a new neural network-based clustering algorithm for group technology International Journal of Production Research 34 IssueID4 919–946
M.Y. Kiang U.R. Kulkarni K.Y. Tam (1995) ArticleTitleSelf-organizing map network as an interactive clustering tool: an application to group technology Decision Support Systems 15 351–374 Occurrence Handle10.1016/0167-9236(94)00046-1
J.R. King (1980) ArticleTitleMachine-component group formation in production flow analysis: an approach using a rank order clustering algorithm International Journal of Production Research 18 IssueID2 213–232
A. Kusiak (1985) ArticleTitleThe part families problem in flexible manufacturing systems Annals of Operational Research 25 561–569
A. Kusiak (1987) ArticleTitleThe generalized group technology concept International Journal of Production Research 25 IssueID4 561–569
A. Kusiak M. Cho (1992) ArticleTitleSimilarity coefficient algorithms for solving the group technology problem International Journal of Production Research 30 IssueID11 2633–2646
Z. Lin W. Wu (1999) ArticleTitleMultiple linear regression analysis of the overlay accuracy model IEEE Transaction on Semiconductor Manufacturing 12 229–237 Occurrence Handle10.1109/66.762881
D. MacMillen W.D. Ryden (1982) ArticleTitleAnalysis of image field placement deviations of a 5 × microlithographic reduction lens Proceedings of SPIE: Optical Microlithography-Technology 334 78–89
J. McAuley (1972) ArticleTitleMachine grouping for efficient production The Production Engineering 52 53–57 Occurrence Handle10.1049/tpe.1972.0006
Y.B. Moon S.C. Chi (1992) ArticleTitleGeneralized part family formation using neural network techniques Journal of Manufacturing Systems 11 IssueID3 149–159
D.S. Perloff (1978) ArticleTitleA four-point electrical measurement technique for characterizing mask superposition errors on semiconductor wafers IEEE Journal of Solid State Circuits 13 IssueID4 436–444 Occurrence Handle10.1109/JSSC.1978.1051074
H. Seiffodoni P.M. Wolfe (1986) ArticleTitleApplication of similarity coefficient method in group technology IIE Transactions 18 IssueID13 271–277
G. Srinivasan T.T. Narendran B. Mahadevan (1990) ArticleTitleAn assignment model for the part-families problem in group technology International Journal of Production Research 28 IssueID1 145–152
S. Subhash (1996) Applied multivariate techniques Wiley New York
K.Y. Tam (1990) ArticleTitleAn operation sequence based similarity coefficient for part families formations Journal of Manufacturing Systems 9 IssueID1 55–68 Occurrence Handle10.1016/0278-6125(90)90069-T
M.A. Brink Particlevan den C.G.M. DeMol R.A. George (1988) ArticleTitleMatching performance for multiple wafer steppers using an advanced metrology procedure Proceedings SPIE: Integrated Circuit Metrology, Inspection, and Process Control II, 921 180–197
A. Vannelli K. Kumar (1986) ArticleTitleA method for finding minimal bottle-neck for grouping part-machine families International Journal of Production Research 24 IssueID2 387–400
G.U. Yule (1900) ArticleTitleOn the association of attribute in statistics: with illustration from the material of the childhood society Philosophical Transactions of the Royal Society of London Series A 194 257–319
Author information
Authors and Affiliations
Corresponding author
Additional information
Received: May 2005 / Accepted: December 2005
Rights and permissions
About this article
Cite this article
Chien, CF., Hsu, CY. A novel method for determining machine subgroups and backups with an empirical study for semiconductor manufacturing. J Intell Manuf 17, 429–439 (2006). https://doi.org/10.1007/s10845-005-0016-7
Issue Date:
DOI: https://doi.org/10.1007/s10845-005-0016-7