| Autor: |
Jijing Chen, Kaixuan Ding, Yihan Pi, Shoujun Zhang, Jiao Li, Zhen Tian |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Photoacoustics, Vol 38, Iss , Pp 100614- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2213-5979 |
| DOI: |
10.1016/j.pacs.2024.100614 |
| Popis: |
Microscopic defects in flip chips, originating from manufacturing, significantly affect performance and longevity. Post-fabrication sampling methods ensure product functionality but lack in-line defect monitoring to enhance chip yield and lifespan in real-time. This study introduces a photoacoustic remote sensing (PARS) system for in-line imaging and defect recognition during flip-chip fabrication. We first propose a real-time PARS imaging method based on continuous acquisition combined with parallel processing image reconstruction to achieve real-time imaging during the scanning of flip-chip samples, reducing reconstruction time from an average of approximately 1134 ms to 38 ms. Subsequently, we propose improved YOLOv7 with space-to-depth block (IYOLOv7-SPD), an enhanced deep learning defect recognition method, for accurate in-line recognition and localization of microscopic defects during the PARS real-time imaging process. The experimental results validate the viability of the proposed system for enhancing the lifespan and yield of flip-chip products in chip manufacturing facilities. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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