Modeling optical emission spectroscopy data generated during reactive ion etching using an autoencoder neural network

Intelligent Engineering Systems Through Artificial Neural Networks

Volumn 12, Issue , 2002, Pages 945-950

  Hong, Sang Jeen ^a   May, Gary S ^a   Park, Dong Chul ^b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b Myong Ji University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ANISOTROPY; AROMATIC HYDROCARBONS; NEURAL NETWORKS; OPTICAL DATA PROCESSING; PRESSURE EFFECTS; REACTIVE ION ETCHING;

PLASMA EMISSIONS;

EMISSION SPECTROSCOPY;

EID: 0036999876     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. Baldi, P. and Hornik, K., 1989, "Neural Networks and Principal Component Analysis", Neural Networks, Vol. 2, pp. 53-58.
2. Hong, S., and May, G., 2002, "Neural Network Modeling of Reactive Ion Etching using Principal Component Analysis of Optical Emission Spectroscopy Data", Proc. Adv. Semi. Manuf. Conf., Boston, MA, pp. 415-420.
3. Kim, B. and May, G., 1996, "Reactive ion etch modeling using neural networks and simulated annealing," IEEE Trans. Semi. Manufac., Vol. 19, No. 1, pp. 3-8.
4. May, G., 1994, "Manufacturing ICs the neural way", IEEE Spectrum, pp. 47-51.
5. Roger, B., Berry, M., Thrlik, I., Garrow, P., and Castillo, D., 1994, "Soft mask for via patterning in Benzocyclobutene,: Int. J. Micro. And Elect. Packaging, Vol. 17, No. 3, pp. 210-218.
6. Roland, J., Marcoux, P., Ray, G., and Rnakin, G., 1985, "Endpoint detection in plasma etching," J. Vac. Sci. Technol. A, Vol. 3, pp. 631-636.
7. Shabushing, J. and Demiko, P.R., 1984, "Application of optical emission spectroscopy to semiconductor device fabrication," American Laboratory, pp. 60-67.