Lithography Process Sequencing for Per-Wafer Overlay Correction
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Solution Overview
Problem
Current lithographic processes face challenges in accurately aligning successive layers of features in semiconductor device manufacturing, leading to limited granularity in corrections and wafer-to-wafer variations due to the use of lot-level corrections and limited degrees of freedom in available actuators.
Innovation Solution
A method that involves obtaining characteristics of previous and subsequent processes in a sequence, determining predicted performance parameters, and applying granular corrections on a per-wafer basis using a context-to-performance model to optimize the lithographic process, decoupling the contributions of individual processes to performance parameters like after-etch CD and overlay fingerprints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If lot-level corrections are used, then process simplicity is maintained, but manufacturing precision deteriorates due to wafer-to-wafer variations
Solution Approach 1:
The patent segments the correction approach from lot-level to per-wafer level. Each wafer receives individualized corrections based on its specific characteristics and the predicted fingerprints of subsequent processes, rather than applying uniform corrections to entire lots. This segmentation enables precise control of overlay accuracy while managing complexity through systematic data collection and modeling.
Solution Approach 2:
The patent implements preliminary action by measuring and characterizing each wafer before it enters the lithographic process, and by predicting the fingerprints of subsequent processes in advance. This allows corrections to be determined and applied proactively for each individual wafer, improving overlay precision without requiring complex real-time adjustments during processing.
2Manufacturing precision
If per-wafer corrections are implemented, then manufacturing precision improves, but device complexity increases due to additional measurement and correction operations
Solution Approach 1:
Measurements and characterizations are performed in advance before the lithographic process, allowing per-wafer corrections to be determined without adding significant time to the critical production path. The predictive modeling of subsequent process fingerprints is also done beforehand, enabling rapid correction application that maintains throughput while improving precision.
Solution Approach 2:
The system uses each wafer's own measured characteristics and process history to determine its specific corrections, rather than requiring external manual intervention for each wafer. The predictive model automatically processes the collected data and generates correction parameters, reducing the need for complex manual optimization while maintaining high precision.
3Measurement precision
If extensive measurement operations are performed, then measurement precision improves, but loss of time increases due to additional mapping operations
Solution Approach 1:
Comprehensive wafer measurements and characterizations are performed in advance before the lithographic process. By collecting all necessary data beforehand, the system avoids time-consuming measurements during the critical production steps, thereby maintaining high measurement precision without significantly impacting throughput.
Solution Approach 2:
The patent implements a balanced measurement strategy that collects sufficient data to achieve the required measurement precision for per-wafer corrections, but avoids excessive or redundant measurements. The measurement operations are optimized to gather only the necessary characteristics needed for accurate predictive modeling and correction determination.
Data Source
AI summary
A method for optimizing a sequence of processes for manufacturing of product units, includes: associating measurement results of performance parameters (e.g., fingerprints) with the recorded process characteristics (e.g., context); obtaining a characteristic (e.g., context) of a previous process (e.g. deposition) in the sequence already performed on a product unit; obtaining a characteristic (e.g., context) of a subsequent process (e.g., exposure) in the sequence to be performed on the product unit; determining a predicted performance parameter (e.g., fingerprint) of the product unit associated with the sequence of previous and subsequent processes by using the obtained characteristics to retrieve measurement results of the performance parameters (e.g., fingerprints) corresponding to the recorded characteristics; and determining corrections to be applied to future processes (e.g. exposure, etch) in the sequence to be performed on the product unit, based on the determined predicted performance parameter.