In one embodiment, an automated high-speed X-ray inspection system may generate a first X-ray image of an inspected sample at a first direction substantially orthogonal to a plane of the inspected sample. The first X-ray image may be a high-resolution grayscale image. The system may identify one or more elements of interest of the inspected sample based on the first X-ray image. The first X-ray image may include interfering elements that interfere with the one or more elements of interest in the first X-ray image. The system may determine one or more first features associated with respective elements of interest based on variations of grayscale values in the first X-ray images. The system may determine whether one or more defects are associated with the respective elements of interest based on the one or more first features associated with the element of interest.

In one embodiment, an X-ray inspection system may capture one or more X-ray images for samples of interest processed by a first tool. The X-ray inspection system may be inline with the first tool and have an inspection speed of 300 mm.sup.2 per minute or greater. The system may determine, in real-time, metrology information related to the samples of interest based on the X-ray images. The metrology information may indicate that a sample parameter associated with the samples of interest is outside of a pre-determined range. The system may provide instructions or data to one or more of the first tool or one or more second tools to adjust process parameters associated with the respective tools based on metrology information. The adjusted process parameters may reduce a processing error probability, of the respective tool for processing subsequent samples, related to the sample parameter being outside of the pre-determined range.

An electron beam inspection apparatus according to one aspect of the present invention includes an image acquisition mechanism to acquire a secondary electron image by scanning a substrate, on which a figure pattern is formed, with an electron beam, and detecting a secondary electron emitted due to irradiation with the electron beam by the scanning, a resize processing unit to perform, using design pattern data being a basis of the figure pattern, resize processing on the figure pattern to enlarge its size in a scan direction of the electron beam, a first developed image generation unit to generate, using the design pattern data which has not been resized, a first developed image by developing an image of a design pattern of a region corresponding to the secondary electron image, a second developed image generation unit to generate, using partial patterns enlarged by the resize processing in the figure pattern having been resized, a second developed image by developing an image of partial patterns in a region corresponding to the secondary electron image, a map generation unit to generate a pseudo defect candidate pixel map which can identify a pseudo defect candidate pixel that has no pattern in the first developed image and has a pattern in the second developed image, a reference image generation unit to generate a reference image of the region corresponding to the second electron image, and a comparison unit to compare, using the pseudo defect candidate pixel map, the second electron image with the reference image of the region corresponding to the second electron image.

Method for detecting at least one critical defect in a ceramic rolling element providing the steps of capturing a plurality of two-dimensional digital radiographic images of the rolling element; digitally filtering each radiographic image; delineating, on the basis of the filtered image, at least one region liable to comprise the critical defect; constructing stereoscopically a virtual model of the rolling element having the region; comparing the dimensions of the delineated region with a plurality of predetermined threshold values, and, when the dimensions are greater than the threshold values, generating an alarm signal.

To enable evaluation of a shape of a fine particle and a fine particle type, a substrate is set as a substrate on which an isolated fine particle to be measured and an isolated standard fine particle in the vicinity of the isolated fine particle to be measured are disposed, and a scanning electron microscope body including a detector configured to detect secondary charged particles obtained by scanning a surface of the substrate with an electron beam probe, and a computer that processes a detection signal and generates an image of the isolated fine particle to be measured and the isolated standard fine particle are provided. The computer corrects a shape of the isolated fine particle to be measured by using a measurement result of the isolated standard fine particle disposed in the vicinity of the isolated fine particle to be measured. Further, by attaching a fine particle spreading tank equipped with a fine particle suspension dropping device inside the microscope body, automatic measurement including dropping of fine particle suspension onto a surface of a surface-modified substrate is possible.

A method of detecting an anomaly in a crystallographic structure, the method comprising: illuminating the structure with x-ray radiation in a known direction relative to the crystallographic orientation; positioning the structure such that its crystallographic orientation is known; detecting a pattern of the diffracted x-ray radiation transmitted through the structure; generating the simulated pattern based on the known direction relative to the crystallographic orientation; comparing the detected pattern to a simulated pattern for x-ray radiation illuminating in the known direction; and, detecting the anomaly in the crystallographic structure based on the comparison.

In one embodiment, a computing system may access design data of a printed circuit board to be produced by a first manufacturing process. The system may analyze the design data of the printed circuit board using a machine-learning model, wherein the machine-learning model is trained based on X-ray inspection data associated with the first manufacturing process. The system may automatically determine one or more corrections for the design data of the printed circuit board based on the analysis result by the machine-learning model.

In one embodiment, a computing system may access design data of a printed circuit board to be produced by a manufacturing process. The system may determine one or more corrections for the design data of the printed circuit board based on one or more correction rules for correcting one or more parameters associated with the printed circuit board. The system may automatically adjust one or more of the parameters associated with the design data of the printed circuit board based on the one or more corrections. The adjusted parameters may be associated with an impedance of the printed circuit board. The one or more corrections may cause the impendence of the printed circuit board to be independent from layer thickness variations of the printed circuit board to be produced by the manufacturing process.

A method for controlling the crystallographic orientation of at least one grain of a turbo engine part. The method includes emitting a beam of electromagnetic radiation through an elementary volume of the part and record diffraction information on the electromagnetic radiation passing through the part. This step is repeated on a given area of the part. The method further includes determining the crystal spatial orientation of each of said elementary volumes and deducing the presence of at least one first crystallographic grain for which the elementary volumes are oriented according to the same crystallographic orientation. The method further includes calculating the angular difference between the crystal spatial orientation of said first grain and a predetermined direction taken from the part and comparing it to a first predetermined threshold value and determining a state of use of the part.

The disclosure provides an inspection method determining whether there is a defect in an electrode structural body including a cathode electrode layer, an electrolyte layer and an anode electrode layer electrode by an image processor. The inspection method includes a step of scanning the electrode structural body along a scanning direction to obtain a continuous transmission image, a step of digitizing a shade of each pixel of the transmission image, a step of calculating a difference value between a grayscale of a specific pixel and a median value of grayscales of comparison pixels located in front or rear of the specific pixel along the scanning direction, and a step of determining presence or absence of the defect according to the difference value and a predetermined threshold value.