Inspection Tool Parameter Optimization Heuristic
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Solution Overview
Problem
Current optical inspection tools face challenges in achieving high resolution and throughput while requiring manual calibration of numerous configuration parameters for optimal performance, which is inefficient and not adaptable to different semiconductor wafers and photomask layers.
Innovation Solution
A method utilizing a heuristic prioritization scheme to optimize configurable parameters of inspection tools, which involves selecting a prioritized sequence of parameters, calculating an optimization target function using local scan images, and updating configuration settings to maximize signal-to-noise ratio, thereby automating the calibration process and generating optimized recipe files for different types of defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration of numerous configuration parameters is performed, then optimal inspection performance is achieved, but the process is inefficient and not adaptable to different semiconductor wafers and photomask layers
Solution Approach 1:
The system performs automatic optimization of configuration parameters using a heuristic algorithm that self-calibrates the inspection tool by evaluating multiple parameter combinations and selecting the optimal set based on signal-to-noise ratio calculations, eliminating the need for manual calibration
Solution Approach 2:
The system systematically varies configuration parameters according to a prioritized sequence, evaluating each parameter's impact on detection performance and automatically adjusting parameter values to optimize inspection results for different wafer and photomask configurations
2Reliability
If dozens of configuration parameters are calibrated manually, then optimal detection is achieved, but the device complexity and operation difficulty increase
Solution Approach 1:
The inspection tool automatically optimizes its own configuration parameters through a heuristic algorithm that evaluates detection performance and self-adjusts parameters, making the complex calibration process transparent to the user and eliminating operation difficulty
Solution Approach 2:
The system pre-establishes a prioritized sequence of parameter optimization and automatically executes the calibration process before inspection, preparing optimal configuration settings in advance without requiring user intervention during operation
3Measurement precision
If a comprehensive search of all configurable parameter values is performed, then optimal settings are found, but the search space becomes computationally infeasible
Solution Approach 1:
The system divides the parameter optimization process into segments by establishing a prioritized sequence of parameters, optimizing one parameter at a time rather than searching all parameters simultaneously, which reduces the computational search space while maintaining optimization effectiveness
Solution Approach 2:
The system pre-determines the optimal sequence of parameter optimization based on their relative importance, performing preliminary analysis to identify which parameters have the greatest impact on detection performance and optimizing them first, thereby reducing overall computation time
Data Source
AI summary
A method, computer product and system for optimization of configurable parameters of inspection tools are provided. The method includes applying a heuristic that utilizes a prioritized sequence of selections of configurable parameters. For each configuration setting of the heuristic the method includes providing a set of local scan images of a list of DOIs, calculating an optimization target function and updating the configuration settings with the best value of each scanned parameter according to said prioritization heuristic. The method includes outputting the one or more updated configuration settings to a recipe file.