With the advancement of lithography, the overlay budget is becoming extremely tight. As the accuracy of overlay is
important for achieving a good yield, the demand for the accuracy of overlay is ever increasing. According to the
International Technology Roadmap for Semiconductors (ITRS), the overlay control budget for the 32nm technology
node will be 5.7nm. The overlay metrology budget is typically 1/10 of the overlay control budget resulting in overlay
metrology total measurement uncertainty (TMU) requirements of 0.57nm for the most challenging use cases of the 32nm
node. The current state of the art imaging overlay metrology technology does not meet this strict requirement, and further
technology development is required to bring it to this level. Especially for exposure tool inspection (e.g. alignment,
overlay, wafer stage and distortion), more high accuracy should be required using 'resist to resist' pattern.
In this work we simulated the measurement sensitivity for two types of scatterometry based overlay metrology, one is
differential signal scatterometry overlay (SCOL), the other is double exposure type (DET).
We have proposed a new inspection method of in-line focus and dose controls for semiconductor volume production.
We referred to this method as the focus and dose line navigator (FDLN). Using FDLN, the deviations from the optimum
focus and exposure dose can be obtained by measuring the topography of the resist pattern on a process wafer that was
made under a single-exposure condition. Generally speaking, FDLN belongs to the technology of solving the inverse
problem as scatterometry. The FDLN sequence involves following the two steps. Step 1:creating a focus exposure matrix
(FEM) using a test wafer for building the model as supervised data. The model means the relational equation between the
multi measurement results of resist patterns ( e.g. Critical dimension (CD), height, sidewall angle) and FEM's exposure
conditions. Step 2: measuring the resist patterns on a production wafers and feeding the measurement data into the
library to extrapolate focus and dose. To estimate the accuracy of FDLN, we performed some experiments. We
developed a FEM with an ArF lithography tool and measured the resist patterns of the FEM wafer with the advanced
CD-SEM (Critical Dimension-Scanning Electron Microscope). Using the MPPC (Multiple Parameters Profile
Characterization) data from the advanced CD-SEM, we obtained the following results. Focus: 21.5 nm (4.1 nm) and
Dose: 1.5% (2.0 nm). The numerical value in a parenthesis shows the value of the estimated accuracy with changing CD.
We also show other experimental results in this paper and the application of the focus and dose controls for
semiconductor exposure tool.
KEYWORDS: Inspection, Lithography, Control systems, Statistical analysis, Mining, Data analysis, Manufacturing, Process control, Data mining, Semiconductors
To attain quick turn-around time (TAT) and high yield, it is very important to remove all the problems affecting the semiconductor volume production line. For this purpose, we have used a lithography management system (LMS) as an advanced process control system. The LMS stores the critical dimension and overlay inspection results as well as the log data of the exposure tool in a relational database. This enables a quick and efficient grasp of the productivity under the present conditions and helps to identify the causes of errors. Furthermore, we developed a mining tool, called a log data extraction and correlation miner (LMS-LEC), for factor analysis on the LMS. Despite low correlation between all data, a high correlation may exist between parameters in a certain data domain. The LMS-LEC can mine such correlations easily. With this tool, we can discover previously unknown error sources that have been buried in the vast quantity of data handled by the LMS and thereby increase of the effectiveness of the exposure and inspection tool. The LMS-LEC is an extremely useful software mining tool for “equipment health” monitoring, advanced fault detection, and sophisticated data analysis.
We propose a new inspection method of in-line focus and dose control at semiconductor volume production. We have been referred to this method as Focus & Dose Line Navigator (FDLN). Using FDLN, the deviations from the optimum focus and exposure dose can be obtained by measuring the topography of resist pattern on a process wafer that was made with single exposure condition. Generally speaking, FDLN belongs to the technology of solving the inverse problem as scatterometry. The FDLN sequence involves following two steps. Step 1: creating a focus exposure matrix (FEM) using test wafer for building the library as supervised data. The library means relational equation between the topography of resist patterns (critical dimension (CD), height, side wall angle) and FEM's exposure conditions. Step 2: measuring the topography of resist patterns on production wafers and feeding the topography data into the library to extrapolates focus and dose. To estimate the accuracy of FDLN, we had some experiment. We made a FEM with ArF lithography tool and measured the topography of the FEM with optical CD measurement tool. By using the topography data, we obtained following result as accuracy of FDLN. Focus: 27.0nm (5.2nm) and Dose: 1.8% (1.4nm). The numerical value in a parenthesis shows the value of estimated accuracy into change of CD value. We also show other experimental results and some simulation result in this paper.
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