Imprint Apparatus Alignment Using Abnormal Mark Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The die-by-die alignment method in imprint apparatuses can result in position deviations between the pattern region on the mold and the substrate due to abnormal marks on the substrate, making it difficult to transfer patterns with high accuracy.
Innovation Solution
An imprint apparatus that includes a detection unit to identify abnormal marks by comparing detection results with predicted values based on deformation information, and a control unit that performs alignment without using the detection results for abnormal marks, ensuring accurate alignment between the mold and substrate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the die-by-die alignment method is used to perform alignment between substrate and mold, then the alignment process can be automated for mass production, but position deviation occurs when abnormal marks are present, reducing manufacturing precision
Solution Approach 1:
The system uses detection results from the detection unit as feedback to identify abnormal marks, then adjusts the alignment process by excluding these abnormal marks from the alignment calculation. This feedback mechanism allows the system to automatically correct for anomalies while maintaining automated operation.
Solution Approach 2:
The system changes the parameter selection for alignment by dynamically determining which marks to include or exclude based on their detection results. When abnormal marks are detected, the system changes the alignment parameters to use only normal marks, thereby maintaining precision while preserving automation.
2Loss of time
If all detected marks are used for alignment, then the alignment process is simple and fast, but abnormal marks cause position deviation and reduce alignment accuracy
Solution Approach 1:
The detection results provide feedback that enables the system to quickly identify abnormal marks and exclude them from alignment calculations. This feedback loop minimizes the time penalty for accuracy verification while ensuring that only valid marks influence the alignment outcome.
Solution Approach 2:
The system performs partial action by using only the necessary subset of marks for alignment - specifically, excluding abnormal marks while including all normal marks. This approach avoids the excessive action of processing all marks equally, thereby maintaining speed while improving accuracy.
3Manufacturing precision
If abnormal marks are excluded from alignment calculation, then manufacturing precision is improved, but the device complexity increases due to additional detection and determination steps
Solution Approach 1:
The control unit performs multiple functions: it detects marks, determines their normality based on detection results, and adjusts alignment parameters accordingly. This multi-functionality consolidates what could be separate complex subsystems into a single control unit, managing complexity while improving precision.
Solution Approach 2:
The system uses its own detection results to automatically identify and exclude abnormal marks without requiring external intervention or complex additional equipment. The detection unit and control unit work together in a self-service manner to maintain precision while minimizing added complexity.
Data Source
AI summary
The present invention provides an imprint apparatus that forms an imprint material supplied on a shot region of a substrate by using a mold, comprising a detection unit configured to detect each mark provided to the shot region and each mark provided to the mold, and a control unit configured to perform alignment between the mold and the substrate based on a detection result by the detection unit, wherein the control unit obtains a predicted value of a position of a mark provided to the shot region by using information about deformation of the shot region, determines, as an abnormal mark, a mark for which a difference between the detection result and the predicted value does not fall within an allowable range and performs the alignment without using the detection result for the abnormal mark.