TFT-LCD Substrate Alignment Detection Using Segmented Marks
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Solution Overview
Problem
Current alignment detection methods for TFT-LCD substrates are inefficient due to inappropriate segment differences in alignment marks, difficulty in determining offsets with large errors, need for numerous marks, and lack of automation, leading to potential alignment errors and increased labor costs.
Innovation Solution
An alignment detection method involving a coordinate system, unique spacing of alignment marks on opposing substrates, and optical detection to determine the highest overlap level and adjust alignment accuracy, allowing for automated detection and reduced labor costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional alignment marks with uniform spacing are used, then the detection process is simple, but the alignment precision is insufficient when large offset errors exist
Solution Approach 1:
The alignment mark structure is segmented into two distinct components: a first alignment mark with a first spacing and a second alignment mark with a second spacing. This segmentation allows each mark to serve different detection purposes - the first mark for fine alignment and the second mark for coarse alignment, thereby improving overall measurement precision without requiring a single complex mark structure
Solution Approach 2:
The patent employs asymmetric spacing design where the distance between features in the first alignment mark differs from the distance between features in the second alignment mark. This asymmetric configuration creates distinct overlap patterns that enable the detection system to differentiate between small and large offset errors, improving alignment precision across different error magnitudes
2Adaptability or versatility
If multiple alignment marks are used to cover large offset errors, then the detection range is improved, but the number of marks and detection complexity increase
Solution Approach 1:
The detection system is segmented into two stages corresponding to two alignment marks with different spacings. The first alignment mark handles fine-range detection while the second alignment mark handles coarse-range detection. This segmentation allows the system to achieve extended detection range without requiring a single complex multi-scale mark structure
Solution Approach 2:
The patent introduces a dimensional difference in the spacing configuration between the two alignment marks. By varying the spatial dimension (spacing distance) between marks, the system can detect different magnitudes of offsets using the same detection apparatus, thereby expanding detection range without adding multiple separate detection systems
3Extent of automation
If manual detection methods are used, then the equipment is simple, but labor costs increase and automation is lacking
Solution Approach 1:
The patent replaces manual visual inspection with an automated optical detection system. The detection apparatus uses optical sensors to automatically capture images of the alignment marks and computationally determine overlap levels, substituting mechanical/manual operations with automated optical-mechanical systems. This enables automation of the alignment detection process while maintaining relatively simple equipment
Solution Approach 2:
The detection system creates optical copies (images) of the alignment marks and processes these copies computationally to determine alignment accuracy. By working with digital representations rather than directly manipulating physical marks, the system achieves automation while keeping the physical detection apparatus relatively simple
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 method improves alignment accuracy, reduces labor costs, and enables automated production by determining the precise alignment of TFT and CF substrates, minimizing errors and increasing efficiency.
Implementation Method 1
selecting the group of the first alignment mark and the second alignment mark having the highest overlap level includes detecting, by an optical detector, a grayscale value of an overlapping portion
Data Source
AI summary
An alignment detection method includes: establishing a coordinate system; providing at least one group of a first and second mark regions arranged on a first and second substrates respectively, the first and second mark regions being arranged opposite to each other so as to form at least two groups of first and second alignment marks; detecting an overlap level between an orthogonal projection of each of the first alignment marks onto the first substrate and that of the second alignment marks onto the second substrate, selecting a group of the first and second alignment marks having the highest overlap level, and acquiring, in the coordinate system, coordinate values of the first and second alignment marks in the group having the highest overlap level; and comparing the coordinate values with a threshold, so as to determine alignment accuracy between the first and second substrates.