Metrology data cleaning and statistical assessment flow for modeling applications

Modern OPC modeling relies on substantial volumes of metrology data to meet pattern coverage and precision requirements. This data must be reviewed and cleaned prior to model calibration to prevent bad data from adversely affecting calibration. We propose implementing specific tools in the metrology flow to improve metrology engineering efficiency and resulting data quality. The metrology flow with and without these tools will be discussed, and the inherent tradeoffs will be identified. To demonstrate the benefit of the proposed flow, engineering efficiency and the impact of better data on model calibration will be quantified.