Foreign Matter Analysis Using Feature Value Filtering
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Solution Overview
Problem
The increasing number of measurement points in microscopic spectroscopy requires significant memory capacity and processing speed, making foreign matter analysis expensive and time-consuming, as all spectra data need to be analyzed, which is inefficient.
Innovation Solution
A method that calculates feature values for each spectrum to determine if a measurement point is on foreign matter, allowing only relevant data to be retained and analyzed, using techniques like multivariate analysis, spectrum search, and machine learning to identify and classify foreign matter constituents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all spectra data from numerous measurement points are used for foreign matter analysis, then measurement precision is improved, but memory usage and processing time increase significantly
Solution Approach 1:
The patent extracts only the necessary spectral data for foreign matter analysis by calculating feature values and comparing them against reference spectra. Only spectra containing foreign matter are retained for detailed analysis, while other data are discarded or stored separately, thus reducing memory usage while maintaining detection accuracy.
Solution Approach 2:
The analysis process is segmented into multiple stages: initial feature value calculation for all measurement points, foreign matter identification by comparing feature values against references, and detailed analysis only for identified foreign matter regions. This segmentation allows selective processing of data to reduce overall memory requirements.
2Measurement precision
If all spectra data from numerous measurement points are used for foreign matter analysis, then measurement precision is improved, but processing time increases significantly
Solution Approach 1:
The patent performs preliminary feature value calculation and foreign matter identification before detailed spectral analysis. By pre-identifying regions containing foreign matter using efficient feature comparison, the system avoids performing computationally intensive detailed analysis on all measurement points, thus significantly reducing total processing time while maintaining accuracy.
Solution Approach 2:
Instead of performing complete detailed analysis on all spectra data, the patent applies partial analysis only to the subset of spectra identified as containing foreign matter. This partial action approach maintains measurement precision for foreign matter detection while avoiding unnecessary processing time expenditure on clean regions.
3Productivity
If high memory capacity and fast processing arithmetic elements are implemented, then foreign matter analysis capability is improved, but device cost increases
Solution Approach 1:
The patent changes the processing parameters by using feature value extraction and comparison as intermediate steps before detailed spectral analysis. This parameter change allows the use of simpler arithmetic elements for the majority of processing, reserving high-performance computation only for the final detailed analysis of identified foreign matter regions, thus reducing overall device complexity and cost.
Data Source
AI summary
A method of analyzing foreign matter in a sample includes:measuring an optical spectrum for each of a plurality of measurement points of a measurement region on the sample by a microscopic spectroscope;calculating a feature value of each measured spectrum by a computer;determining whether each of the measurement points is on the foreign matter or not based on each feature value;retaining the spectrum of the measurement point that is determined to be on the foreign matter, anddeleting the spectrum of the measurement point that is not determined to be on the foreign matter or storing the same to a storage unit; andexecuting multivariate analysis of the spectra of the plurality of the measurement points that are determined to be on the foreign matter or classifying the same with AI search.