Semiconductor Search Apparatus Parameter Space Optimization
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Solution Overview
Problem
The complexity of semiconductor processing requires precise control of multiple input parameters to achieve nanometer-level accuracy, leading to an excessively large search space that is computationally infeasible to explore within a reasonable time, especially with the presence of non-linear relationships and local solutions, making it difficult to find optimal processing conditions efficiently.
Innovation Solution
A search apparatus and method that generates a prediction model based on input and output data to identify the most promising search areas within the vast parameter space, allowing for the efficient exploration of input parameters to achieve target processing results by narrowing down the search area and excluding suboptimal regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the control range of semiconductor processing apparatus is increased to process various materials and structures, then the performance and productivity of semiconductor devices are improved, but the number of control parameters increases making it extremely difficult to ascertain optimal parameter combinations
Solution Approach 1:
The patent segments the vast parameter space into multiple subspaces by dividing control parameters into different groups or categories. This allows the system to search for optimal parameters in manageable segments rather than attempting to search the entire parameter space at once, thus handling the increased complexity from expanded control range.
Solution Approach 2:
The patent employs parameter changes by systematically varying control parameters within defined ranges to explore the parameter space. The system changes parameters in a structured manner to identify optimal combinations that achieve target processing results, addressing the difficulty of ascertaining optimal parameter combinations in high-dimensional spaces.
2Measurement precision
If multiple sensors and monitors are mounted to acquire processing status data, then the ability to analyze and control processing variations is improved, but the amount of acquired data increases making analysis extremely difficult
Solution Approach 1:
The patent extracts only the necessary and relevant features from the large volume of sensor and monitor data. Rather than analyzing all acquired data, the system identifies and extracts key parameters and patterns that are most relevant to processing quality and control, thus making data analysis manageable while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary data processing and filtering before detailed analysis. By pre-processing the large amount of acquired data to remove noise, aggregate redundant information, and identify key trends in advance, the system reduces the complexity of subsequent analysis while preserving the essential information needed for control decisions.
3Manufacturing precision
If traditional exhaustive search methods are used to find optimal input parameters, then all possible combinations can be evaluated, but the search time becomes excessively long and computationally infeasible
Solution Approach 1:
The patent employs dynamic search strategies that adapt the search process based on intermediate results. Rather than following a fixed exhaustive search schedule, the system dynamically adjusts the search direction, step size, and focus areas based on feedback from evaluations, enabling faster convergence to optimal parameters while maintaining accuracy.
Solution Approach 2:
The patent incorporates feedback mechanisms where the results of parameter evaluations are used to guide subsequent search decisions. The system learns from previous evaluations and uses this feedback to prioritize promising regions of the parameter space, avoiding exhaustive search of clearly suboptimal areas and thus significantly reducing search time while maintaining the ability to find optimal solutions.
Data Source
AI summary
A search apparatus receives an input target value, which indicates a condition to be set in a semiconductor processing apparatus or a result obtained by processing the semiconductor using the processing apparatus, a reference value of the condition inside a search area, and the result, wherein the reference value is indicated by the target value. A prediction model indicating a relation between the condition and the result based on a setting value of the condition inside the search area is generated and, a measured value of the result is obtained. A prediction value is acquired by assigning the target value to the prediction model. The prediction value is set to the reference value when it is determined that the prediction value is closer to the target value, and a prediction value satisfying an achievement condition is set when the prediction value satisfies the achievement condition of the target value.