Monte Carlo simulation of edge placement error

Shinji Kobayashi; Soichiro Okada; Satoru Shimura; Kathleen Nafus; Carlos Fonseca; Joel Estrella; Masashi Enomoto

doi:10.1117/12.2297135

13 March 2018 Monte Carlo simulation of edge placement error

Shinji Kobayashi, Soichiro Okada, Satoru Shimura, Kathleen Nafus, Carlos Fonseca, Joel Estrella, Masashi Enomoto

Proceedings Volume 10585, Metrology, Inspection, and Process Control for Microlithography XXXII; 1058529 (2018) https://doi.org/10.1117/12.2297135
Event: SPIE Advanced Lithography, 2018, San Jose, California, United States

Abstract

In the discussion of edge placement error (EPE), we proposed interactive pattern fidelity error (IPFE) as an indicator to judge pass/fail of integrated patterns. IPFE consists of lower and upper layer EPEs (CD and center of gravity: COG) and overlay, which is decided from the combination of each maximum variation. We succeeded in obtaining the IPFE density function by Monte Carlo simulation. In the results, we also found that the standard deviation (σ) of each indicator should be controlled by 4.0σ, at the semiconductor grade, such as 100 billion patterns per die. Moreover, CD, COG and overlay were analyzed by analysis of variance (ANOVA); we can discuss all variations from wafer to wafer (WTW), pattern to pattern (PTP), line edge roughness (LWR) and stochastic pattern noise (SPN) on an equal footing. From the analysis results, we can determine that these variations belong to which process and tools. Furthermore, measurement length of LWR is also discussed in ANOVA. We propose that the measurement length for IPFE analysis should not be decided to the micro meter order, such as >2 μm length, but for which device is actually desired.

Citation Download Citation

Shinji Kobayashi, Soichiro Okada, Satoru Shimura, Kathleen Nafus, Carlos Fonseca, Joel Estrella, and Masashi Enomoto "Monte Carlo simulation of edge placement error", Proc. SPIE 10585, Metrology, Inspection, and Process Control for Microlithography XXXII, 1058529 (13 March 2018); https://doi.org/10.1117/12.2297135

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KEYWORDS

Semiconducting wafers

Monte Carlo methods

Line width roughness

Critical dimension metrology

Bridges

Statistical analysis

Stochastic processes

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