Wafer Inspection Point Selection for Yield and Throughput
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Solution Overview
Problem
Current semiconductor manufacturing processes face challenges in achieving high resolution inspections due to the limitations of optical microscopes and low throughput of charged particle beam microscopes, leading to non-uniformity in patterning and reduced yield, as defects are often detected after the entire patterning process is completed.
Innovation Solution
A system and method that includes a training tool generating training data from verified inspection results and a point determination tool to dynamically determine inspection regions and exposure recipes for subsequent substrates, optimizing the monitoring process to reduce defects and improve yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If optical microscope inspection is used, then throughput is high, but resolution is limited to a few hundred nanometers
Solution Approach 1:
The inspection process is segmented into multiple stages: optical microscope inspection for high-throughput initial screening, followed by charged particle beam inspection for high-resolution verification of critical areas. This segmentation allows the system to leverage the strengths of both inspection methods without compromising overall throughput or resolution requirements.
Solution Approach 2:
Different inspection methods are applied to different regions of the wafer based on their specific requirements. Optical inspection covers entire wafers for general defect detection, while charged particle beam inspection focuses on specific critical regions requiring sub-100 nanometer resolution, optimizing resource allocation and inspection effectiveness.
2Measurement precision
If charged particle beam microscope is used, then resolution reaches less than a nanometer, but throughput is significantly lower
Solution Approach 1:
Optical microscope inspection is performed as a preliminary action before charged particle beam inspection. This preliminary screening identifies potential defects and guides the subsequent high-resolution inspection, reducing the total inspection time by avoiding exhaustive high-resolution scanning of entire wafers.
Solution Approach 2:
Instead of applying charged particle beam inspection to entire wafers, the system applies it partially to specific critical regions identified through optical inspection or process parameters. This partial action maintains high resolution where needed while preserving overall throughput.
3Productivity
If batch processing is used, then multiple substrates are processed together, but non-uniformity in patterning occurs
Solution Approach 1:
The system implements feedback mechanisms where inspection results from optical and charged particle beam microscopes are used to adjust and optimize exposure recipes for subsequent batches. This feedback loop enables continuous improvement of patterning uniformity across batches while maintaining batch processing efficiency.
Solution Approach 2:
Exposure recipes are made dynamic rather than static, allowing adjustments based on real-time inspection data and process variations. The system dynamically optimizes exposure parameters for different batches and even different regions within batches, compensating for non-uniformities while maintaining high throughput.
4Reliability
If defect inspection is conducted after entire patterning process, then all defects are detected, but defective wafers must be scrapped or down-graded
Solution Approach 1:
The system performs preliminary defect inspection at multiple intermediate stages during the patterning process using both optical and charged particle beam microscopes. This allows early detection of defects that can lead to wafer rejection, enabling corrective actions before the entire patterning process is completed and preserving manufacturing yield.
Solution Approach 2:
The inspection system acts as an intermediary between process stages, providing real-time quality feedback that enables process adjustments and defect prevention. This intermediary role allows the system to maintain high reliability in defect detection while preventing unnecessary wafer scrapping through early intervention.
Data Source
AI summary
Embodiments of the present disclosure provide systems and methods for enhancing the semiconductor manufacturing yield. Embodiments of the present disclosure provide a yield improvement system. The system comprises a training tool configured to generate training data based on receipt of one or more verified results of an inspection of a first substrate. The system also comprises a point determination tool configured to determine one or more regions on a second substrate to inspect based on the training data, weak point information for the second substrate, and an exposure recipe for a scanner of the second substrate.