Statistical optimization of sampling plan and its relation to OPC model accuracy

Geng Han; Andrew Brendler; Scott Mansfield; Jason Meiring

doi:10.1117/12.712725

4 April 2007 Statistical optimization of sampling plan and its relation to OPC model accuracy

Geng Han, Andrew Brendler, Scott Mansfield, Jason Meiring

Proceedings Volume 6518, Metrology, Inspection, and Process Control for Microlithography XXI; 651808 (2007) https://doi.org/10.1117/12.712725
Event: SPIE Advanced Lithography, 2007, San Jose, California, United States

Abstract

In this paper, we seek a systematic strategy for creation of a wafer sampling plan and to determine the relationship between this plan and the OPC model accuracy. We start our study with the traditional error components analysis of wafer data. From this, we introduce our methodology of calculating the effective sample size based on each pattern and its error components. With all the error components separated, the confidence of the estimated mean can be calculated and, hence, an error bar can be added to each mean of the wafer data. This error bar is then used to determine which patterns are over-fitting and which patterns require an improved fit. We will present a method of providing an optimized and economical solution for wafer sampling. With this calculated error bar, the ultimate metric for OPC model accuracy will also be discussed.

Citation Download Citation

Geng Han, Andrew Brendler, Scott Mansfield, and Jason Meiring "Statistical optimization of sampling plan and its relation to OPC model accuracy", Proc. SPIE 6518, Metrology, Inspection, and Process Control for Microlithography XXI, 651808 (4 April 2007); https://doi.org/10.1117/12.712725

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