Modeling of manufacturing sensitivity and of statistically based process control requirements for a 0.18 μm NMOS device

Abstract

Random statistical variations during the IC manufacturing process have an important influence on yield and performance, particularly as technology is scaled into the deep submicron regime. A simulation-based approach to modeling the impact of these variations on a 0.18μm NMOSFET is presented. The result of this modeling is a special Monte Carlo simulation code that can be used to predict the statistical variation of key device electrical characteristics and to determine the reduction in these variations resulting from improved process control. In addition, the level of process control needed to satisfy specified statistical targets for the NMOSFET electrical performance was analyzed. Meeting these targets requires tight control of five key parameters: the gate length (optimal statistical variation is 9% or less), the gate oxide thickness (optimal statistical variation is 5% or less), the shallow source/drain extension junction depth (optimal statistical variation is 5% or less), the channel dose (optimal statistical variation is 7.5% or less), and the spacer width (optimal statistical variation is 8% or less).