Laser Data Classification for Semiconductor Exposure Monitoring

The patent segments the collected data into distinct categories by adding classification information that identifies whether each data record corresponds to exposure period or non-exposure period. This segmentation allows the system to maintain comprehensive data quantity while preserving the ability to distinguish between different operational states through structured data organization with explicit period identification markers.

The patent applies local quality by adding specific attribute information to data records based on their operational context. Each data record is enhanced with classification attributes that indicate whether it belongs to exposure or non-exposure period, allowing the storage structure to remain relatively simple while enabling precise performance analysis when needed by querying only the relevant period-specific data.

The patent extracts the classification determination logic as a separate function that operates independently from the main data collection and storage processes. By taking out the classification information addition as a distinct processing step, the system achieves period distinction capability while managing complexity through modular data processing architecture where classification is handled separately from other data operations.

The patent performs preliminary classification of data during the data collection phase itself, adding period identification attributes before the data is stored. This preliminary action ensures that when data is stored, it is already organized with the necessary classification information, enabling targeted analysis of exposure periods without requiring additional storage overhead for separate classification structures or post-processing organization.