Wafer inspection systems help a semiconductor manufacturer increase and maintain integrated circuit (IC) chip yields by detecting defects that occur during the manufacturing process.
One purpose of inspection systems is to monitor whether a manufacturing process meets specifications. The inspection system indicates the problem and/or the source of the problem if the manufacturing process is outside the scope of established norms, which the semiconductor manufacturer can then address.
Evolution of the semiconductor manufacturing industry is placing ever greater demands on yield management and, in particular, on metrology and inspection systems. Critical dimensions are shrinking while wafer size is increasing. Economics is driving the industry to decrease the time for achieving high-yield, high-value production. Thus, minimizing the total time from detecting a yield problem to fixing it determines the return-on-investment for the semiconductor manufacturer.
Semiconductor manufacturers needs to review images or results from an area of a wafer or semiconductor device, such as areas flagged during inspection. This is challenging because the images or results may not easily align to an inspection image or to a design file. This also is challenging because the various images, results, or design files may use different coordinate systems. For example, a user of a scanning electron microscope (SEM) review tool may need to align an image from the SEM with an inspection image. This can be accomplished through manual deskew, offset correction, or automatic deskew, but these techniques each have drawbacks.
For manual deskew, the locations given by the inspection tool are viewed on a review tool, such as an SEM, and an actual location of defects is marked. Only real defects can be used for this technique. Manual deskew will not work in a semiconductor manufacturing setting with defect-free devices or defect-free parts of a wafer. The offsets between the command location and actual defect location are calculated. The calculated offsets are translational, rotational, scaling, and non-orthogonality between the review and inspection coordinate systems. A deskew transform is generated, which is then applied to all defect locations of given defect coordinates of a particular scan. The generated deskew transform can be stored in a cache which can be used for further recipe job runs.
Manual deskew has multiple drawbacks. Manual deskew is a tedious and time-consuming technique because a user needs to search for real defects across the entire wafer. These defects may need to be greater than a particular size threshold to be viewable. Performing the deskew pass and the time taken for deskew depends on a user's knowledge and experience. Manual deskew requires presence of real defects with a particular size all across the wafer. If the defects are too small, it is difficult to find in the higher field of view (FOV), which may be required for accommodating the deskew errors. Very large defects cannot be used because a user does not know which part of the large defect is flagged by the inspection system. Furthermore, on high SEM non-visible (SNV) rate inspections, real defects are very difficult to find and manual deskew is impractical.
For offset correction, a number of real defects are manually marked and translational offset between the command location and actual defect location is calculated by the software. Offset correction will not work in a semiconductor manufacturing setting with defect-free devices or defect-free parts of a wafer. The calculated translational offsets are used to calculate the mean translational offset between the review and inspection coordinate systems. Offset correction can only correct for translational offsets between the two coordinate systems. Offset correction suffers from all the other disadvantages of manual deskew. Furthermore, offset correction only corrects for translational offset. Other errors between the review and inspection coordinate systems are ignored.
Automatic deskew does not manually mark the defects. Instead, the defect locations are automatically detected using a defect detection algorithm. Similar to manual deskew, translational, rotational, scaling, and non-orthogonality offsets are calculated. However, this deskew solution is not robust and frequently fails. For example, automatic deskew can fail if a capture rate on the layer is insufficient. In another example, one or more reference images are needed with the defect site image, which increases complexity and can increase failure rates. Automatic deskew has seen limited commercial use due to reliability issues. Like manual deskew, automatic deskew requires presence of defects of a particular size across the wafer. Automatic deskew will not work in a semiconductor manufacturing setting with defect-free devices or defect-free parts of a wafer. Furthermore, this deskew technique is impractical on high SNV rate inspections.
Therefore, improved deskew techniques are needed.
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