A Novel Approach to Link Process Parameters to BSIM Model Parameters

Abstract

Abstract-In this paper, we demonstrate a methodology to link process parameters to BSIM model parameters. Here, we have combined well-known statistical methods like principal component analysis (PCA), design of experiments (DOE), and response surface methodology (RSM) to bridge the missing link between process parameters and model parameters. The proposed methodology uses the concept of a correlation matrix, which transforms the process level information to the device and circuit level information through the BSIM model parameters. The proposed methodology has been successfully implemented on an advanced CMOS process. Our results show a strong linear correlation for the data obtained from two techniques namely TCAD technique and the standard HSPICE simulation technique. In both cases the process conditions were kept identical for comparison.Index Terms-CMOS, design of experiments, principal component analysis, process variations, response surface methodology, variability.

SRAM device and cell co-design considerations in a 14nm SOI FinFET technology

“…Accurate compact modelling [6] [7] [8] lies at the heart of PDK development. The quality of nominal transistor fitting from a BSIM-CMG [9] group-extraction procedure is demonstrated in Fig.7.…”

Device oriented statistical modeling method for process variability in 45nm analog CMOS technology

“…A well-known statistical method, principal component analysis (PCA)were reported to develop the models [7]. Another methodology proposed to link process parameters to BSIM model parameters by combining principal component analysis (PCA), design of experiments (DOE), and response surface methodology (RSM) [9].…”