Fiducial-Based Defect Map Alignment for Semiconductor Review
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current semiconductor assembly line processes for defect inspection rely on manual analysis and expensive hardware, leading to unsatisfactory results due to misalignment between defect scanners and reviewers, which increases overhead and sensitivity to defect offsets.
Innovation Solution
An automated defect offset correction system that embeds fiducials in semiconductor workpieces, uses a defect offset correction module to detect and correct fiducial offsets in image data, and adjusts defect maps to align with the reviewer's coordinate system, reducing manual intervention and improving quality control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis by engineers and operators is used for defect inspection, then quality control can be performed, but overhead costs and hardware expenses increase significantly
Solution Approach 1:
The defect inspection system performs self-correction by automatically detecting fiducial markers and calculating offset values to align defect maps with reviewer coordinate systems. The system serves itself by eliminating the need for manual alignment adjustments, thereby reducing overhead while maintaining quality control reliability
Solution Approach 2:
The patent replaces manual mechanical alignment processes with an automated computational system. Instead of engineers physically adjusting defect maps, the system uses image processing algorithms to detect fiducials and apply coordinate transformations, substituting mechanical operations with electronic processing
2Adaptability or versatility
If defect scanners and reviewers use different coordinate systems, then flexibility in inspection methods is maintained, but defect alignment accuracy deteriorates
Solution Approach 1:
The patent introduces fiducial markers as intermediary reference objects between the defect scanner and reviewer coordinate systems. These fiducials serve as a common reference framework that enables accurate coordinate transformation while allowing both systems to maintain their own coordinate systems and inspection methods
Solution Approach 2:
The system dynamically changes coordinate system parameters by calculating offset values based on detected fiducial positions. The defect map coordinates are transformed using calculated translation and rotation parameters, enabling precise alignment while preserving the flexibility of different inspection methodologies
3Productivity
If automated defect correction is implemented, then productivity and alignment accuracy improve, but system complexity increases
Solution Approach 1:
The system performs preliminary alignment corrections by detecting fiducial markers and calculating offset values before the actual defect review process. This preliminary action prepares the defect map in advance, ensuring accurate alignment is established before inspection begins, thereby improving productivity without adding complexity during the review phase
Data Source
AI summary
A method includes: receiving a defect map from a defect scanner, wherein the defect map comprises at least one defect location of a semiconductor workpiece; annotating the defect map with a reference fiducial location of the semiconductor workpiece; determining a detected fiducial location within image data of the semiconductor workpiece; determining an offset correction based on comparing the detected fiducial location with the reference fiducial location; producing a corrected defect map by applying the offset correction to the defect map, wherein the applying the offset correction translocates the at least one defect location; and transferring the corrected defect map to a defect reviewer configured to perform root cause analysis based on the corrected defect map.