Modeling of OES data to estimate etch rate for etching equipment

Yi Cheng; Richard J. Markle; Joe Qin; Thomas F. Edgar; Michael J. Gatto; Chris Nauert

doi:10.1117/12.284627

25 August 1997 Modeling of OES data to estimate etch rate for etching equipment

Yi Cheng, Richard J. Markle, Joe Qin, Thomas F. Edgar, Michael J. Gatto, Chris Nauert

Proceedings Volume 3213, Process, Equipment, and Materials Control in Integrated Circuit Manufacturing III; (1997) https://doi.org/10.1117/12.284627
Event: Microelectronic Manufacturing, 1997, Austin, TX, United States

Abstract

Optical emission spectroscopy (OES) data for 495 wavelengths and wafer measurements (pre- and post-oxide film thickness) from a commercial etch tool were collected for 18 oxide wafers to explore the feasibility of using OES as an in-situ sensor to estimate average oxide etch rate. A variable selection method is proposed based on the principle of partial least square (PLS) regression, which select several most informative wavelengths to build ordinary least square (OLS) regression models. Compared with the PLS models, it is found that OLS regression models based on selected wavelengths are more robust.

Citation Download Citation

Yi Cheng, Richard J. Markle, Joe Qin, Thomas F. Edgar, Michael J. Gatto, and Chris Nauert "Modeling of OES data to estimate etch rate for etching equipment", Proc. SPIE 3213, Process, Equipment, and Materials Control in Integrated Circuit Manufacturing III, (25 August 1997); https://doi.org/10.1117/12.284627

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