A genetic algorithm for low variance control in semiconductor device manufacturing: some early results
Edward A. Rietman, Robert C. Frye · IEEE Transactions on Semiconductor Manufacturing · 1996
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 /spl Aring/ and a standard deviation of 730 /spl Aring/. In simulations using real production data and a neural network model of the process our new recipes have reduced the standard deviation below 200 /spl Aring/. These results indicate that significant improvement in the process can be realized by applying these techniques.