As the size of semiconductor devices gradually decreases, it is important to measure and analyze semiconductor devices, to improve the image quality of semiconductors. We use VDSR, one of the Super-Resolution methods to improve the quality of semiconductor devices’ SEM images. VDSR is also a convolutional neural network that can be optimized with various parameters. In this study, a VDSR model for semiconductor devices’ SEM images was optimized using parameters such as depth of layers and amount of training data. Meanwhile, the quantitative evaluation and the qualitative evaluation did not match at the low scale factor. To solve this problem, we proposed an MTF measurement method using the slanted edge for better quantitative evaluation. This method was verified by comparing the results with the PSNR and SSIM index results, which are known as quality indicators. Based on the results, it was confirmed that using the MTF value could be a better approach for the evaluation of SEM images of the semiconductor device than using PSNR and SSIM.

Equipment used in the semiconductor manufacturing process generally have a flow rate control system for each nozzle to regulate the flow rate of chemical solution fed to the wafer. In existing flow rate control systems, flow rate overshoots occur because of excess pressure and the control rates of the overshoots are less because additional operation time is required for the electric valves. In this study, to address the shortcomings of existing flow rate control systems, we proposed a method to improve the speed of flow rate control by introducing a constant pressure valve. The constant pressure valve controls the flow path via gas pressure, thereby facilitating prompt control and efficiently improving the flow rate overshoot caused by the pressure overshoot. To improve the control speed and control stability of the constant pressure valve, a three-step automatic control speed application function was developed, and the measured valve, control amount mapping function, and pre-open function were defined to reduce the initial control speed. The experimental results showed a measurement precision within 1% of the target flow rate and stable control performance as well as control speed reduction from 3 seconds in existing systems to 2 seconds or less for the proposed system.

Various chemicals are used for semiconductor process. In particular, the most important element in the etching and cleaning process is chemical liquid. An ultrasonic flow meter is used to monitor the supplying amount of chemical solution. If the ultrasonic flow meter contains bubble inside the liquid, measurement cannot be performed or measurement error will be occurred. In this research, the waveform was improved by zero-crossing processing so that the influence on measurement performance is negligible even if the bubble in the chemical solution is included. Consequently, the amplitude of the sound wave is attenuated. Existing flow meters monitor the amplitude value to determine the authenticity of the signal and to filter the noise. The improved method in this study distinguishes noise waves and monitors signal frequency. Flow measurement was carrying out even when the amplitude was resulting only less than 3% of input level volt. The system developed of this study has shown an exact measuring performance compared with the other make’s flow meters.