Mask Inspection System Defect Criticality Evaluation
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Solution Overview
Problem
The increasing complexity and miniaturization of semiconductor mask patterns lead to challenges in defect detection and evaluation, resulting in inefficiencies in mask inspection and evaluation processes, with existing methods struggling to accurately determine the criticality of defects and their impact on wafer patterns, leading to increased manufacturing time and pseudo defects.
Innovation Solution
A mask evaluation system that integrates a mask inspection apparatus and an aerial image measurement apparatus, where the inspection apparatus acquires optical images, generates reference images from design data, and extracts pattern data for defective areas, which are then used by the aerial image measurement apparatus to determine the criticality of defects based on line width and hole diameter errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mask inspection time is increased to detect finer defects, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The system performs preliminary classification of defects into critical and non-critical categories using automated evaluation criteria before full inspection processing. This allows the inspection system to prioritize and process critical defects with higher precision while applying faster, less resource-intensive methods to non-critical defects, thereby improving overall productivity without sacrificing detection precision for important defects.
Solution Approach 2:
The patent applies partial action by focusing detailed high-precision inspection only on areas identified as containing critical defects, while using quicker screening methods for other areas. This selective approach to inspection intensity optimizes the balance between detection precision and inspection speed.
2Reliability
If all detected defects are repaired, then reliability is improved, but loss of time increases
Solution Approach 1:
The system applies local quality by differentiating between critical defects that require repair and non-critical defects that can be tolerated. Instead of uniformly repairing all defects, the patent selectively targets only critical defects for repair based on their location, size, type, and potential impact on wafer patterns. This localized repair approach maintains mask quality reliability while significantly reducing manufacturing time compared to repairing all detected defects.
Solution Approach 2:
The patent extracts and separates critical defects from non-critical defects using automated evaluation, then applies repair only to the extracted critical defect subset. This extraction process enables the system to focus repair resources on defects that truly matter for reliability while avoiding unnecessary repairs that would waste time.
3Manufacturing precision
If complex optical proximity correction patterns are added, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary automated evaluation system that acts as a mediator between the complex OPC patterns and the defect inspection process. This intermediary system translates complex pattern information into simplified defect criticality assessments, enabling the inspection system to handle complex OPC patterns without proportionally increasing its own complexity. The evaluation criteria serve as an intermediary layer that manages the complexity burden.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This integrated system reduces mask manufacturing time by focusing repairs only on critical defects, improving inspection efficiency and accuracy by determining the impact of defects on wafer patterns and reducing pseudo defect occurrences.
Implementation Method 1
light emitted from a light source is irradiated onto a mask through an optical system. The mask is loaded and chucked on a stage, and the illuminated light scans the mask by movement of the stage. The light transmitted through or reflected by the mask, images on a sensor through lenses of an optical system.
Implementation Method 2
In order to acquire an optical image, a charge accumulation type time delay integration (TDI) sensor and a sensor amplifier that amplifies the output of the TDI sensor are used.
Data Source
AI summary
A mask inspection apparatus includes an optical image acquisition unit configured to acquire an optical image by irradiating light on a mask, a reference image generation unit configured to generate a reference image from design data of the mask, a comparison circuit configured to compare the optical image with the reference image, a pattern data extraction unit configured to obtain coordinates of a defective portion determined to be defective by the comparison unit and to extract, from the design data, pattern data of a predetermined dimension range including the coordinates, and an interface unit configured to supply an aerial image measurement apparatus with information associated with the defect, the information including the defect coordinates and the extracted pattern data.