摘要:
In order to be able to detect an irradiation position of an electron beam matching a defect position and conduct composition analysis of a defect with high precision and high efficiency, in the present invention, when a composition analysis target defect is selected and irradiation conditions of the electron beam are set for EDX analysis, a low-resolution reference image of low resolution is acquired using the electron beam at a defect corresponding position corresponding to the position of this defect on a chip in the vicinity of a target chip including defects, and a low-resolution defect image of the same low resolution is next acquired at the defect position of the target chip. Then, by comparing these low-resolution images, the defect position is acquired, the electron beam is slanted and irradiated on this defect position to acquire a composition spectrum of the defect.
摘要:
In a wafer inspection and sampling system, wafer defects are detected and stored in a data store as defect data. Information is also provided, representative of clusters of defects on the wafer. A statistically based sampling of the defects is made to obtain a set of sampled defects. Subsequent detailed inspection and analysis of the sampled defects produces additional data which facilitate an understanding of process errors.
摘要:
In a wafer inspection and sampling system, wafer defects are detected and stored in a data store as defect data. Information is also provided, representative of clusters of defects on the wafer. A statistically based sampling of the defects is made to obtain a set of sampled defects. Subsequent detailed inspection and analysis of the sampled defects produces additional data which facilitate an understanding of process errors.
摘要:
To efficiently extract identification of apparatuses causing problems in a thin-film device manufacturing process, candidates for the problem-generating manufacturing apparatus are extracted by evaluating data obtained in relation to produced inspections and data indicating the states of the manufacturing apparatus, with respect to products that enable efficient extraction of problem-generated apparatuses in a thin-film devise manufacturing process. This facilitates inferring the identification of the problem-generating apparatus.
摘要:
In an automatic defect classifying method, defects not reviewed are assigned with defect classes having the same definitions as those of reviewed defects in order to effectively use information on defects not reviewed, the defects not reviewed occupying most of defects on a wafer. Defects not reviewed are assigned defect classes having the same definitions, by using defect data of defects detected with an inspection equipment and defect classes of already reviewed defects given by ADC of a review equipment. Since all defects are assigned the defect classes having the same definitions, more detailed analysis is possible in estimating the generation reasons of defects.
摘要:
The distribution states of defects are analyzed on the basis of the coordinates of defects detected by an inspection apparatus to classify them into a distribution feature category, or any one of repetitive defect, congestion defect, linear distribution defect, ring/lump distribution defect and random defect. In the manufacturing process for semiconductor substrates, defect distribution states are analyzed on the basis of defect data detected by an inspection apparatus, thereby specifying the cause of defect in apparatus or process.
摘要:
With the objective of achieving defect kind training in a short period of time to teach classification conditions of defects detected as a result of inspecting a thin film device, according to one aspect of the present invention, there is provided a visual inspection method, and an apparatus therefor, comprising the steps of: detecting defects based on inspection images acquired by optical or electronic defect detection means, and at the same time calculating features of the defects; and classifying the defects according to classification conditions set beforehand, wherein said classification condition setting step further includes the steps of: collecting defect features over a large number of defects acquired beforehand from the defect detection step; sampling defects based on the distribution of the collected defect features over the large number of defects; and setting defect classification conditions based on the result of reviewing the sampled defects.
摘要:
The distribution states of defects are analyzed on the basis of the coordinates of defects detected by an inspection apparatus to classify them into a distribution feature category, or any one of repetitive defect, congestion defect, linear distribution defect, ring/lump distribution defect and random defect. In the manufacturing process for semiconductor substrates, defect distribution states are analyzed on the basis of defect data detected by an inspection apparatus, thereby specifying the cause of defect in apparatus or process.
摘要:
The distribution states of defects are analyzed on the basis of the coordinates of defects detected by an inspection apparatus to classify them into a distribution feature category, or any one of repetitive defect, congestion defect, linear distribution defect, ring/lump distribution defect and random defect. In the manufacturing process for semiconductor substrates, defect distribution states are analyzed on the basis of defect data detected by an inspection apparatus, thereby specifying the cause of defect in apparatus or process.
摘要:
With the objective of achieving defect kind training in a short period of time to teach classification conditions of defects detected as a result of inspecting a thin film device, according to one aspect of the present invention, there is provided a visual inspection method, and an apparatus therefore, comprising the steps of: detecting defects based on inspection images acquired by optical or electronic defect detection means, and at the same time calculating features of the defects; and classifying the defects according to classification conditions set beforehand, wherein said classification condition setting step further includes the steps of: collecting defect features over a large number of defects acquired beforehand from the defect detection step; sampling defects based on the distribution of the collected defect features over the large number of defects; and setting defect classification conditions based on the result of reviewing the sampled defects.