Applied Sciences (Dec 2023)

Analysis of Electromagnetic Interference Effect on Semiconductor Scanning Electron Microscope Image Distortion

  • You-Jin Park,
  • Rong Pan,
  • Douglas C. Montgomery

DOI
https://doi.org/10.3390/app14010223
Journal volume & issue
Vol. 14, no. 1
p. 223

Abstract

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Most electronic devices are susceptible to electromagnetic interference (EMI); thus, it is necessary to recognize and identify the cause and effect of EMI as it can corrupt electronic signals and degrade equipment performance. Particularly, in semiconductor manufacturing, the equipment used for image capturing is subject to various noises induced by EMI, causing the image analysis to be unreliable during the image recognition and digitization process. Thus, in this research, we aim to detect and quantify the influence of EMI on semiconductor SEM (scanning electron microscope) images. For this, we apply several useful denoising and edge detection techniques to find a clearer distorted shape from EMI-generated images and then compute five shape-related measures to evaluate the distortion. From a comprehensive experimental analysis and statistical tests, it is found that the medians of all the extracted shape-related measures of high-EMI SEM images are higher than those of both medium- and weak-EMI SEM images, and also all the p-values of the statistical tests are close to 0, and thus we can conclude that all the measures are good quantification metrics for assessing the impact of EMI on semiconductor SEM images.

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