Real-time spectral signal processing for robust thickness monitoring during wafer thinning

Wafer thinning, as a key step in 3D integration using through-silicon via (TSV), highly relies on precise in-situ thickness monitoring to control accurate endpoint and avoid overgrinding or undergrinding. For ultra-thin wafers, conventional contact-based techniques become increasingly limited due to insufficient accuracy and surface damage. Spectral interferometry has been employed for in-situ thickness measurement. However, its application during wafer grinding is challenged by mechanical vibration, cooling flow, silicon debris, and variations in surface conditions, which may lead to incorrect endpoint detection, increasing the risk of wafer scrap. In this study, a compact water-guided optical probe is developed to maintain a stable optical path and reduce contamination from slurry and debris. Meanwhile, a Fourier transform thickness extraction algorithm is combined with a Z-score quality-factor criterion and a dynamic thickness tracking strategy to identify invalid measurements and suppress outliers during continuous thinning. This approach minimizes misjudgments while maintaining a high valid data rate during real-time acquisition. The proposed method was validated over a wide thickness range and achieved accurate endpoint control down to 3 μm. Static comparison with the F50 showed absolute deviations below 0.5 μm within the designed range of 3–400 μm, while valid data rates remained above 80 % across all thinning tasks. Reliable monitoring was further verified for ultra-thin wafers below 10 μm, demonstrating the robustness of the proposed method under practical grinding conditions.

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Publication Details

Journal
Mechanical Systems and Signal Processing
Published
2026-09-18
DOI
https://doi.org/10.1016/j.ymssp.2026.114971
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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Real-time spectral signal processing for robust thickness monitoring during wafer thinning

Haotian Dong, Chengyuan Yao, Zizheng Wang, Sun Xinlei et al.
Mechanical Systems and Signal Processing
Industrial Vision Systems and Defect Detection
article

Real-time spectral signal processing for robust thickness monitoring during wafer thinning

Haotian Dong, Chengyuan Yao, Zizheng Wang, Sun Xinlei, Chunguang Hu, TongTao Li, Hao Liu, Zhaoran Liu
article en

Abstract

Wafer thinning, as a key step in 3D integration using through-silicon via (TSV), highly relies on precise in-situ thickness monitoring to control accurate endpoint and avoid overgrinding or undergrinding. For ultra-thin wafers, conventional contact-based techniques become increasingly limited due to insufficient accuracy and surface damage. Spectral interferometry has been employed for in-situ thickness measurement. However, its application during wafer grinding is challenged by mechanical vibration, cooling flow, silicon debris, and variations in surface conditions, which may lead to incorrect endpoint detection, increasing the risk of wafer scrap. In this study, a compact water-guided optical probe is developed to maintain a stable optical path and reduce contamination from slurry and debris. Meanwhile, a Fourier transform thickness extraction algorithm is combined with a Z-score quality-factor criterion and a dynamic thickness tracking strategy to identify invalid measurements and suppress outliers during continuous thinning. This approach minimizes misjudgments while maintaining a high valid data rate during real-time acquisition. The proposed method was validated over a wide thickness range and achieved accurate endpoint control down to 3 μm. Static comparison with the F50 showed absolute deviations below 0.5 μm within the designed range of 3–400 μm, while valid data rates remained above 80 % across all thinning tasks. Reliable monitoring was further verified for ultra-thin wafers below 10 μm, demonstrating the robustness of the proposed method under practical grinding conditions.

Mechanical Systems and Signal ProcessingVol. 260
Tianjin University (CN)
Climate action
Openalex Percentile: Top 11%
Industrial Vision Systems and Defect Detection
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Real-time spectral signal processing for robust thickness monitoring during wafer thinning — Haotian Dong, Chengyuan Yao, et al. · Mechanical Systems and Signal Processing (2026) | TGRS Research Map | TGRS