Virtual metrology
In semiconductor manufacturing, virtual metrology refers to methods to predict the properties of a wafer based on machine parameters and sensor data in the production equipment, without performing the (costly) physical measurement of the wafer properties. Statistical methods such as classification and regression are used to perform such a task.
Examples of virtual metrology include:
- the prediction of the silicon nitride ( ) layer thickness in the chemical vapor deposition process (CVD), using multivariate regression methods;[1]
- the prediction of critical dimension in photolithography, using multi-level and regularization approaches;[2]
- the prediction of layer width in etching.[3]
References
- ↑ Purwins, Hendrik; Bernd, Barak; Nagi, Ahmed; Engel, Reiner; Hoeckele, Uwe; Kyek, Andreas; Cherla, Srikanth; Lenz, Benjamin; Pfeifer, Guenther; Weinzierl, Kurt (2014). "Regression Methods for Virtual Metrology of Layer Thickness in Chemical Vapor Deposition". IEEE - ASME Transactions on Mechatronics. 19 (1): 1–8. doi:10.1109/TMECH.2013.2273435.
- ↑ Susto, Gian Antonio; Pampuri, Simone; Schirru, Andrea; Beghi, Alessandro; De Nicolao, Giuseppe (2015-01-01). "Multi-step virtual metrology for semiconductor manufacturing: A multilevel and regularization methods-based approach". Computers & Operations Research. 53: 328–337. doi:10.1016/j.cor.2014.05.008.
- ↑ Susto, G. A.; Johnston, A. B.; O'Hara, P. G.; McLoone, S. (2013-08-01). "Virtual metrology enabled early stage prediction for enhanced control of multi-stage fabrication processes". 2013 IEEE International Conference on Automation Science and Engineering (CASE): 201–206. doi:10.1109/CoASE.2013.6653980.
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