Fiducial Alignment Using Shape-Invariant Coordinate Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for workpiece alignment using fiducials are time-consuming and error-prone, requiring significant operator intervention and different processing approaches for various fiducial shapes, which complicates the precise determination of coordinates in semiconductor and device manufacturing.
Innovation Solution
The method involves obtaining an image of a workpiece at a first resolution, selecting a region of interest (ROI) that includes a fiducial, processing it to a higher resolution, masking it with a template based on the fiducial design, and projecting image values along template axes to establish workpiece coordinates, allowing for automated alignment and processing without operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If operator intervention is used to locate fiducials and establish coordinates, then measurement precision can be maintained, but productivity decreases and loss of time increases
Solution Approach 1:
The system performs self-alignment by automatically detecting fiducial features and computing transformation parameters without operator intervention. The processor autonomously identifies fiducial locations, establishes coordinate systems, and applies geometric transformations to align the workpiece, eliminating the need for manual positioning while maintaining precision.
Solution Approach 2:
The patent replaces manual mechanical positioning and visual alignment methods with automated image processing and computational geometry. The system uses digital image analysis, feature detection algorithms, and mathematical transformations to substitute the operator's manual coordination and measurement tasks, achieving both speed and accuracy.
2Measurement precision
If multiple processing approaches are used for different fiducial shapes, then measurement precision is maintained, but device complexity increases
Solution Approach 1:
The patent implements a universal fiducial detection system that can handle various fiducial shapes (circular, square, rectangular, cross-shaped) using a single integrated approach. The processor automatically identifies fiducial geometry and applies appropriate detection algorithms, eliminating the need for separate processing procedures for each fiducial type while maintaining detection accuracy.
Solution Approach 2:
The system adapts processing parameters automatically based on detected fiducial characteristics. The processor identifies fiducial shape and size, then adjusts detection thresholds, template matching parameters, and coordinate transformation equations accordingly, allowing a single system to handle diverse fiducial designs without manual reconfiguration.
3Measurement precision
If multiple images are obtained and reference markers are placed manually, then measurement precision improves, but loss of time increases and productivity decreases
Solution Approach 1:
The system performs preliminary fiducial detection and coordinate establishment automatically during the imaging process. By pre-identifying fiducial features and computing transformation parameters from the acquired images, the system eliminates the need for subsequent manual marker placement and alignment operations, reducing total processing time while maintaining precision.
Solution Approach 2:
The patent uses image processing algorithms as an intermediary between raw image data and precise coordinate determination. The processor automatically extracts fiducial features from images, computes geometric transformations, and establishes coordinate systems, replacing the need for manual reference marker placement and visual alignment while achieving accurate location finding.
Data Source
AI summary
Fiducial coordinates are obtained by aligning template with region of interest extracted from a workpiece image. Image values in the region of interest are projected along a template axis and the project values evaluated to establish a fiducial location which can be used as a reference location for locating workpiece areas for ion beam milling or other processing.