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A genetic algorithm for low variance control in semiconductor device manufacturing: some early results

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2 Author(s)
Rietman, E.A. ; Lucent Technols., bell Labs., Murray Hill, NJ, USA ; Frye, R.C.

Genetic algorithms are a computational paradigm modeled after biological genetics. They allow one to efficiently search a very large optimization space for good solutions. In this paper we describe the use of a genetic algorithm for developing robust plasma etch recipes that reduce the variance about a target mean and allow the dc bias to drift within 15% of a nominal value. The tapered via etch process in our production facility results in a oxide films of about 7093 Å and a standard deviation of 730 Å. In simulations using real production data and a neural network model of the process our new recipes have reduced the standard deviation below 200 Å. These results indicate that significant improvement in the process can be realized by applying these techniques

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Semiconductor Manufacturing, IEEE Transactions on  (Volume:9 ,  Issue: 2 )