Automated Mask Examination Using Computing Unit Analysis
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Solution Overview
Problem
The increasing complexity and susceptibility to defects in mask production, particularly in reflective masks, require a more automated and efficient method for examining masks to identify and address defects effectively.
Innovation Solution
A method and device utilizing a computing unit to automatically determine structural features and assign measuring tasks at defect positions on masks, using predefined decision criteria and structure data sets to perform measurements and analysis, thereby enhancing the automation of mask examination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual examination methods are used for mask defect inspection, then measurement precision can be maintained, but productivity is reduced and time consumption increases
Solution Approach 1:
The system automatically determines structural features and selects measuring tasks without human intervention. The computing unit autonomously processes position data, analyzes structural features, and executes appropriate measurement tasks, enabling the examination system to serve itself and eliminate manual operation bottlenecks.
Solution Approach 2:
Manual mechanical examination processes are replaced by an automated computing-based system. The computing unit processes position data sets and structure data sets algorithmically, substituting human operators with automated computational methods to achieve faster processing while maintaining accuracy.
2Measurement precision
If comprehensive structure examination is performed at all defect positions, then measurement precision is improved, but device complexity and processing time increase
Solution Approach 1:
The system applies different measuring tasks to different defect positions based on their specific structural features. Instead of using a uniform examination approach, the computing unit analyzes local structural characteristics at each defect position and selects appropriate measurement tasks, optimizing the examination process for each specific location while maintaining overall precision.
Solution Approach 2:
The system performs preliminary analysis of structural features before executing measurement tasks. The computing unit first determines structural features from position data and structure data, then uses this preliminary information to select appropriate measuring tasks, avoiding unnecessary comprehensive examinations and reducing overall process complexity.
3Productivity
If automated determination of structural features is implemented, then productivity is improved, but measurement precision may be compromised
Solution Approach 1:
The system uses feedback loops where measurement results are analyzed and used to refine subsequent measurements. The computing unit processes measurement data, compares it against expected structural features, and adjusts the examination process accordingly, ensuring that automated measurements maintain high precision through continuous validation and correction.
Data Source
AI summary
A method for examining a mask includes providing a position data set having error positions of the mask to be examined, providing a structure data set having the structure of the mask, and specifying structural features of the mask, the values of which are to be determined. At each error position, determining the values of the specified structural features of the structure by using a computing unit, determining a measuring task from specified decision criteria and from the determined values of the structural features of the structure by using the computing unit, and carrying out the determined measuring task in a manner controlled by the computing unit. In addition, a device, in particular a microscope, for carrying out the method is provided.