The defect size of a photomask blank is evaluated. An inspection-target photomask blank is irradiated with inspection light and reflected light of the region of the inspection-target photomask blank irradiated with the inspection light is collected through an objective lens of an inspection optical system as a magnified image of the region. Then, an intensity change part in the light intensity distribution profile of the magnified image is identified. Next, a difference in the light intensity of the intensity change part is obtained and the width of the intensity change part is obtained as the apparent width of the defect. Then, the width of the defect is calculated on the basis of a predetermined conversion expression showing the relationship among the difference in the light intensity, the apparent width of the defect, and the actual width of the defect, and the width of the defect is estimated.

Provided is a defect review technique that can accurately correct coordinate differences with respect to unusual defects in which it is difficult to accurately correct coordinate misalignments by conventional automatic fine alignment. If it is impossible to correct a coordinate misalignment on the basis of a first optical microscope image acquired by a first light source, a defect review apparatus acquires a second optical microscope image using a second light source, and determines whether it is possible to correct the coordinate misalignment on the basis of the second optical microscope image.

Systems and methods for determining cross-section profiles of underground fluid conveyance structures involves a memory configured to store a profile scan dataset of at least one pipe and at least one pipe template. A processor is configured to compare the profile scan dataset to one or more templates. Profile deviations in a pipe profile are determined using the comparison. A location and an areal measurement of the profile deviations is determined. A user interface is configured to present the profile deviations to a user.

Systems, methods, and devices are provided for the creation of predictable and accurate defects in a fiber tow of an Automated Fiber Placement (AFP) process, with such artificial defects being useful to support calibration of an in situ inspection system used in the AFP process. Various embodiments include methods for creating such artificial defects that support calibration of an in situ inspection system of an AFP system or process. Various embodiments may also include a defect stencils for an AFP system or process.

Disclosed is a method for estimating twin defect density in a single-crystal sample, including: (A) etching the observed surface of a single crystal to form etch pits; (B) selecting bar-shaped etch pits caused by twin defect; (C) from the long-axis direction lengths of the etch pits caused by twin defect, estimating the twin defect density by using the following equation: twin defect density=Σkx′.sub.i/area of sample, wherein 2≤k≤3, and x′.sub.i is the long-axis direction length of an etch pit caused by the i-th twin.

A smart conversion and calibration of the defect coordinate, diagnosis, sampling system and the method thereof for manufacturing fab are provided. The intelligent defect diagnosis method includes receiving pluralities of defect data, design layout data, analyzing the defect data, design layouts, by a Critical Area Analysis (CAA) system. The method utilizes the precisely calibrated coordinate, the defect layout pattern, and the higher accurate calibrated defect size value. So, a more precise killer defect index can be generated with calibrated coordinate deviation calibration and defect size deviation calibration. When judging a defect relating to short circuit or open circuit failure probability, the defect failure result is more accurate and less incorrect judgment.

A smart conversion and calibration of the defect coordinate, diagnosis, sampling system and the method thereof for manufacturing fab is provided. The intelligent defect diagnosis method includes receiving pluralities of defect data, design layout data, analyzing the defect data, design layouts, by a Critical Area Analysis (CAA) system. This method utilizes the precisely calibrated coordinate, the defect layout pattern, and the higher accurate calibrated defect size value. So, a more precise killer defect index can be generated with calibrated coordinate deviation calibration and defect size deviation calibration. When judging a defect relating to short circuit or open circuit failure probability, the defect failure result is more accurate and less incorrect judgment.

A smart conversion and calibration of the defect coordinate, diagnosis, sampling system and the method thereof for manufacturing fab is provided. The intelligent defect diagnosis method includes receiving pluralities of defect data, design layout data, analyzing the defect data, design layouts, by a Critical Area Analysis (CAA) system. This method utilizes the precisely calibrated coordinate, the defect layout pattern, and the higher accurate calibrated defect size value. So, a more precise killer defect index can be generated with calibrated coordinate deviation calibration and defect size deviation calibration. When judging a defect relating to short circuit or open circuit failure probability, the defect failure result is more accurate and less incorrect judgment.

A system has detectors configured to receive a beam of light reflected from a wafer. For example, three detectors may be used. Each of the detectors is a different channel. Images from the detectors are combined into a pseudo-color RGB image. A convolutional neural network unit (CNN) can receive the pseudo-color RGB image and determine a size of a defect in the pseudo-color RGB image. The CNN also can classify the defect into a size category.

An approach for collecting disparate data within a pipe involves a sensor arrangement configured to be deployed within the pipe. The sensor arrangement includes a plurality of sensors configured to detect disparate data related to the pipe. Each sensor of the plurality of sensors is coupled to a respective collection computer on the sensor arrangement. A synchronization module is configured to synchronize the disparate data. A database is configured to store the synchronized data. A processor is configured to process the synchronized data. A user interface configured to present the synchronized data to a user.