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Spatial Monitoring of Wafer Map Defect Data Based on 2D Wavelet Spectrum Analysisopen access

Authors
Lim, MunwonBae, Suk Joo
Issue Date
Dec-2019
Publisher
MDPI
Keywords
image processing; condition based maintenance; statistical process control; wavelet spectrum; wafer bin map
Citation
APPLIED SCIENCES-BASEL, v.9, no.24, pp.1 - 10
Indexed
SCIE
SCOPUS
Journal Title
APPLIED SCIENCES-BASEL
Volume
9
Number
24
Start Page
1
End Page
10
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/146685
DOI
10.3390/app9245518
ISSN
2076-3417
Abstract
Featured Application Image based manufacturing process diagnosis and clinical image data analysis for malignancy detection. Abstract Since machine vision systems (MVS) lead to a wide usage of monitoring systems for industrial applications, the research on the statistical process control (SPC) of image data has been promoted as an automated method for early detection and prevention of unusual conditions in manufacturing processes. In this paper, we propose a non-parametric SPC approach based on the 2D wavelet spectrum (WS-SPC) to extract the feature that contains the spatial and directional information of each subspace in an image. Using the 2D discrete wavelet transform and spectrum analysis, the representative statistic, the Hurst index, is calculated, and a single matrix space that consists of estimated statistics is reconstructed into a spatial control area for SPC. When a control limit is determined by the density of statistics, real-time monitoring based on WS-SPC is available for time releasing images. In the application, an analysis of wafer bin maps (WBMs) is conducted at a semiconductor company in Korea in order to evaluate the performance of the suggested approach. The results show that the proposed method is effective in terms of its fast computation speed and spectral monitoring.
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