Active neural network control of wafer attributes in a plasma et

Details Active neural network control of wafer attributes in a plasma et Active neural network control of wafer attributes in a plasma et

1993-11-27

1995-11-21

Dang, Thi

Etching a substrate: processes

Gas phase etching of substrate

With measuring, testing, or inspecting

216 59, 216 67, 1566261, 156345, H05H 100, G01N 2100

Patent

active

054678838

ABSTRACT:
The present invention is predicated upon the fact that an emission trace from a plasma glow used in fabricating integrated circuits contains information about phenoma which cause variations in the fabrication process such as age of the plasma reactor, densities of the wafers exposed to the plasma, chemistry of the plasma, and concentration of the remaining material. In accordance with the present invention, a method for using neural networks to determine plasma etch end-point times in an integrated circuit fabrication process is disclosed. The end-point time is based on in-situ monitoring of the optical emission trace. The back-propagation method is used to train the network. More generally, a neural network can be used to regulate control variables and materials in a manufacturing process to yield an output product with desired quality attributes. An identified process signature which reflects the relation between the quality attribute and the process may be used to train the neural network.

REFERENCES:
patent: 5286947 (1994-02-01), Clyde et al.
Widrow et al, "30 Years of Adaptive Neural Networks: Perception, Madaline, and Backpropagation", Proceedings of the IEEE, vol. 78, No. 9, Sep. 1990.
European Patent Application No. 90313203.3 published in Europe on Aug. 28, 1991 by Cummings et al. Translation: yes.
C. D. Himmel et al., "A Comparison of Statistically-Based and Neural Network Models of Plasma Etch Behavior," IEEE/SEMI Int. Semiconductor Manufacturing Science Symposium, 124-129 (Jun. 15-16, 1992).
S-S. Chen, "Intelligent Control of Semiconductor Manufacturing Processes," IEEE International Conference on Fuzzy Systems, 101-108 (Mar. 8-12, 1992).
R. Shadmehr et al., "Principal Component Analysis of Optical Emission Spectroscopy and Mass Spectrometry: Application to Reactive Ion Etch Process Parameter Estimation Using Neural Networks," J. Electrochem. Soc., vol. 139, No. 3, 907-914 (Mar. 1992).
E. A. Rietman et al., "Active Neutral Network Control of Wafer Attributes in a Plasma Etch Process," J. Vac. Sci. Technol. B 11(4), 1314-1316 (Jul./Aug. 1993).

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