Abstract
Semiconductor industry has been one of the most complicated industries driven by Moore’s Law for continuous technology evolution. In order to meet the requirements of high resolution and alignment accuracy, the lithography equipments have been advanced from step-and-repeat system to step-and-scan system. As the tolerance of linewidths is becoming tight and slight, overlay errors must be controlled within the tolerance to maintain the yield. In particular, overlay errors can be compensated by modifying the corresponding equipment setup parameters. However, little research has been done to deal with overlay errors of the step-and-scan system. This study aimed to develop a modeling and decision analysis framework in which the overlay error model for step-and-scan system was constructed and the optimal sampling strategy for measuring and compensating the overlay errors was thus designed. Furthermore, we validated the proposed model and sampling strategy by empirical studies conducted in a fab. We compared the proposed sampling strategy with alternative sampling strategies including the existing sampling strateg based on the model adequacy of R-squares and the model effectiveness of residual errors. The results demonstrated the practical viability of the proposed approach.
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References
Buckley J. D., Karatzas C. (1989) Step and scan: A system overview of a new lithography tool. Proceedings of SPIE: Optical/Laser Microlithography II 1088: 424–433
Chien C.-F., Chang K.-H., Chen C.-P. (2003) Design of a sampling strategy for measuring and compensating for overlay errors in semiconductor manufacturing. International Journal of Production Research 41(11): 2547–2561
Chien C.-F., Hsu C.-Y. (2006) A novel method for determining machine subgroups and backups with an empirical study for semiconductor manufacturing. Journal of Intelligent Manufacturing 17(4): 429–440
Chien C.-F., Wang H.-J., Wang M. (2007) A UNISON framework for analyzing alternative strategies of IC final testing for enhancing overall operational effectiveness. International Journal of Production Economics 107(1): 20–30
Chien C.-F., Wu J.-Z. (2003) Analyzing repair decisions in the site imbalance problem of semiconductor test machines. IEEE Transactions on Semiconductor Manufacturing 16(4): 704–711
Cronin D. J., Gallatin G. M. (1994) Micrascan II overlay error analysis. Proceedings of SPIE: Optical/Laser Microlithography VII 2197: 932–942
Fink D., Sullivan N. T., Lekas J. S. (1994) Overlay sample plan optimization for the detection of higher order contributions to misalignment. Proceedings of SPIE: Integrated Circuit Metrology, Inspection, and Process Control VIII 2196: 389–399
Hong J., Lee J., Park J., Cho H., Moon J. (1999) Optimization of sample plan for overlay and alignment accuracy improvement. Japanese Journal of Applied Physics 38: 7164–7167
Leachman R., Ding S., Chien C.-F. (2007) Economic efficiency analysis of wafer fabrication. IEEE Transactions on Automation Science and Engineering 4(4): 501–512
Levinson H. J., Preil M. E., Lord P. J. (1997) Minimization of total overlay errors on product wafers using an advanced optimization scheme. Proceedings of SPIE: Optical Microlithography X 3051: 362–373
Lin Z.-C., Wu W.-J. (1999) Multiple linear regression analysis of the overlay accuracy model. IEEE Transaction on Semiconductor Manufacturing 12(2): 229–237
MacMillen D., Ryden W. D. (1982) Analysis of image field placement deviations of a 5 × microlithographic reduction lens. Proceedings of SPIE: Optical Microlithography-Technology 334: 78–89
Montgomery D. C. (2001) Design and analysis of experiments. Wiley, New York
Pellegrini J. C., Hatab Z. R., Brsh M., Glass T. R. (1999) Super sparse overlay sampling plans: An evaluation of methods and algorithms for optimizing overlay quality control and metrology tool throughput. Proceedings of SPIE: Metrology, Inspection, and Process Control for Microlithography XIII 3677: 72–82
Rangarajan B., Templeton M., Capodieci L., Subramanian R., Scranton A. (1998) Optimal sampling strategies for sub-100 nm overlay. Proceedings of SPIE: Metrology, Inspection, and Process Control for Microlithography XII 3332: 348–359
Schoot J. V., Bornebroek F., Suddendorf M., Mulder M., van der Spek J., Stoeten J., Hunter A. (1999) 0.7 NA DUV step & scan system for 150 nm imaging with improved overlay. Proceedings of SPIE: Optical Microlithography XII 3679: 448–463
Sewell H. (1994) Step and scan: The maturing technology. Proceedings SPIE: Optical/Laser Microlithography VIII 2440: 49–60
van den Brink M. A., de Mol C. G. M., George R. A. (1988) Matching performance for multiple wafer steppers using an advanced metrology procedure. Proceedings SPIE: Integrated Circuit Metrology, Inspection, and Process Control II 921: 180–197
van den Brink M., Jasper H., Slonaker S., Wijnhoven P., Klaassen F. (1996) Step-and-scan and step-and-repeat: A technology comparison. Proceedings of SPIE: Optical Microlithography IX 2726: 734–753
Wu J.-Z., Chien C.-F. (2008) Modeling strategic semiconductor assembly outsourcing decisions based on empirical settings. OR Spectrum 30(3): 401–430
Zwart G., van den Brink M., George R., Satriasaputra D., Baselmans J., Butler H., van Schoot J., de Klerk J. (1997) Performance of a step and scan system for DUV lithography. Proceedings of SPIE: Optical Microlithography X 3051: 817–829
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Chien, CF., Hsu, CY. UNISON analysis to model and reduce step-and-scan overlay errors for semiconductor manufacturing. J Intell Manuf 22, 399–412 (2011). https://doi.org/10.1007/s10845-009-0298-2
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DOI: https://doi.org/10.1007/s10845-009-0298-2