Abstract
We present a low-cost, vision-based method to study the effects of photo resist edge bead removal (EBR) width variability in a manufacturing environment. In micro- and nanofabrication manufacturing wafer edge regions are frequently out of sight and less studied due to their non-yielding attributes. However, they might significantly influence product quality (delamination) and equipment health (contamination). The proposed method utilizes partial wafer edge inspection and open-source image processing to measure the EBR widths without requiring prior image model training. The method is based on the computation of the offset between two local maxima (peaks) in the Hough parametric space equivalent of the Euclidean distance between wafer edge and EBR line. The proposed method is robust to imperfect removal line definitions and highly integrable in automation workflows for equipment health monitoring and statistical process control (SPC). An extensive 180-day survey of EBR width variability revealed low frequency but high severity events.
Original language | English |
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Pages (from-to) | 60-66 |
Number of pages | 7 |
Journal | IEEE Transactions on Semiconductor Manufacturing |
Volume | 35 |
Issue number | 1 |
Early online date | 23 Nov 2021 |
DOIs | |
Publication status | Published (in print/issue) - 3 Feb 2022 |
Data Access Statement
data checkedKeywords
- Photo resist edge bead removal (EBR)
- statistical process control (SPC)
- Hough transform