Defect inspection device, processing device, and defect inspection method

A processing device that is a signal processing device configured to process detection signals output by a first inspection system that applies illumination light to a sample and detects light from the sample by a first method and detection signals output by a second inspection system that applies illumination light to the sample and detects light from the sample by a second method different from the first method,

• wherein the processing device
• compares each of the detection signals of the first inspection system and the detection signals of the second inspection system with a high sensitivity threshold defined for detection including misinformation, to detect defect candidates,
• checks for comparison between coordinates of the defect candidates detected by the first inspection system and coordinates of the defect candidates detected by the second inspection system, to group the defect candidates into a first group including the defect candidates detected by only the first inspection system, a second group including the defect candidates detected by only the second inspection system, and a third group including the defect candidates detected by both the first inspection system and the second inspection system, and
• individually classifies the defect candidates into at least one class according to defect types for each of the first group, the second group, and the third group.

A defect inspection method comprising:

• moving a stage carrying a sample;
• applying illumination light to the sample and detecting light from the sample by a first method with use of a first inspection system;
• applying illumination light to the sample and detecting light from the sample by a second method different from the first method with use of a second inspection system;
• comparing each of the detection signals of the first inspection system and the detection signals of the second inspection system with a high sensitivity threshold defined for detection including misinformation, to detect defect candidates;
• checking for comparison between coordinates of the defect candidates detected by the first inspection system and coordinates of the defect candidates detected by the second inspection system, and grouping the defect candidates into a first group including the defect candidates detected by only the first inspection system, a second group including the defect candidates detected by only the second inspection system, and a third group including the defect candidates detected by both the first inspection system and the second inspection system;
• individually classifying the defect candidates into at least one class according to defect types for each of the first group, the second group, and the third group;
• comparing the defect candidates classified into the at least one class for each of the groups with a low sensitivity threshold set to a value higher than the high sensitivity threshold, and outputting defect inspection data from which the misinformation has been filtered out.