Optimizing Wafer and Die Inspections: High-Speed, High-Precision Vision Architecture
As the semiconductor industry advances toward higher performance and smaller sizes, defect inspection of wafers and dies becomes increasingly critical in advanced packaging processes. Especially in high-tech applications such as 5G, artificial intelligence (AI), and the Internet of Things (IoT), the demand for semiconductor component quality continues to rise—placing higher requirements on precision inspection technologies.
Wafer and die inspection targets
In semiconductor manufacturing, wafer surface inspection and die inspection are two important but distinct stages of quality control:
Wafer surface inspection targets the entire wafer, focusing on macroscopic defects such as contamination, scratches, pattern misalignment, and structural integrity during the manufacturing processes. Vision inspection systems require a large field of view and high-speed scanning capabilities to cover the entire wafer surface.
Die inspection focuses on detailed analysis of individual dies, emphasizing microscopic defects such as edge chipping, poor dicing, and internal structural issues.
Four major challenges in wafer and die AOI inspection
CPU bottlenecks in high-speed, real-time image processing
Wafer and die inspections require processing massive volumes of high-resolution images—often 25 MP or more, with hundreds of thousands of images per unit. These inspections must be completed in fractions of a second, especially for die inspection (within 0.7 seconds). Traditional CPU-based systems often struggle under this load, leading to delays, limited throughput, and inefficient data handling that slow down both development and production.Lack of flexible algorithms and low adaptability Fixed algorithms struggle to detect irregular or low-contrast defects and have difficulty handling special materials like silicon carbide (SiC) and gallium nitride (GaN), which have unique reflective properties. When die size, materials, or structures change, existing algorithms may not adapt quickly, reducing detection accuracy and extending development time.
Difficulty in detecting microscopic defects In advanced packaging processes, detecting tiny surface defects—such as micro-cracks or contamination—becomes increasingly challenging, especially as defect sizes approach the resolution limits of the camera and optics.
Complexity of high-reflectivity surface inspection Reflective surfaces, like wafer and die surfaces, and metal layers, are hard to inspect with standard optics, often causing false positives or missed defects.
Continue reading: How to overcome these AOI challenges
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