Dear Sandeep Kumar,

You may want to review following info:

The impact of process variation on SRAM yield has become a serious concern in scaled technologies. In this paper, we propose a methodology to analyze the stability of an SRAM cell in the presence of random fluctuations in the device parameters. We provide a theoretical framework for characterizing the DC noise margin of a memory cell and develop models for estimating the cell failure probabilities during read and write operations. The proposed models are verified against extensive Monte-Carlo simulations and are shown to match well over the entire range of the distributions well beyond the 3-sigma extremes.

https://ieeexplore.ieee.org/document/1688760

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Statistical analysis of SRAM cell stability

The impact of process variation on SRAM yield has become a serious concern in scaled technologies. In this paper, we propose a methodology to analyze the stability of an SRAM cell in the presence of random fluctuations in the device parameters. We provide a theoretical framework for characterizing the DC noise margin of a memory cell and develop models for estimating the cell failure probabilities during read and write operations. The proposed models are verified against extensive Monte-Carlo simulations and are shown to match well over the entire range of the distributions well beyond the 3-sigma extremes.

https://www.researchgate.net/publication/221059862_Statistical_analysis_of_SRAM_cell_stability

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Monte Carlo, PVT analysis

You should perform Monte Carlo simulations with at least 10,000 iterations at worst process corner and temperature.

For HSNM and RSNM: FS corner and 125 'C

For WSNM: SF corner and -40 'C