BARAS: Novel and highly efficient simulation system for process control sweeping and statistical variation

Abstract

For the realization of today's miniaturization and low voltage drive of ULSIs, it has become much more important to understand and predict the effect of process variations on device performance. Predicting the quantitative effect of every process variation on device characteristics has the following advantages: in designing, required performance range can be appropriately specified, and in manufacturing, when some device characteristic is out of specification, processes to control can be feed-forwarded for proper production. In order to realize this by utilizing simulations, it would be crucial for the simulation system to have a user interface with ease of operation and an efficient data processing ability based on the actual process parameter distribution of the manufacturing equipment. There are some simulation tools which enable the above tasks. However, they have difficulty in handling mask shape variations and in utilizing actual process distributions which do not follow the Gaussian distribution. We have developed BABAS, the automatic simulation system capable of very efficient process control sweeping, statistical variation analysis and output data processing, which has functions for producing input data files automatically and has an easy-to-use GUI. Furthermore, BABAS has succeeded in reducing CPU time drastically by utilizing moment expansion method and enabled Monte Carlo simulations based on real process parameter variations.