Small feature sizes and reduced tolerances of state-of-the-art microelectronic devices make them extremely sensitive to manufacturing variations. This paper describes two approaches dealing with manufacturing variations: process control and statistical design for manufacturability. Process control seeks to reduce the variability of each process module and statistical design seeks to minimize the impact of the variability. An example illustrates the use of process control to minimize variability. Then, a novel approach for statistical design and its application to statistical optimization of deep submicron CMOS is described. This approach is based on a Markov representation of a process flow that captures the sequential and stochastic nature of semiconductor manufacturing. Using this approach we have been able to predict the variability in device performance for a number of process flows. Transistor designs and process flows optimized using this approach show lower variation in key device performances on fabrication.
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Saxena et al. (1997) studied this question.