Abstract: A method for detecting and compensating CNC tools being implemented in an electronic device, receives from a detector first parameters and second parameters in respect of a first tool. Such first parameters include at least one of service life, blade break information, and blade chipping information of the first tool, and such second parameters include at least one of length extension information, length wear information, radial wear information, and blade thickness wear information of the first tool. Based on the first parameters, instructions to process the workpiece are transmitted or not. Upon receiving the second parameters, instructions to adjust operation of the first tool are transmitted, to compensate for deterioration in normal use.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: The present application provides an SSD card adapter bracket and a circuit board assembly. The SSD card adapter bracket includes a bracket member, a first screw, a conductive bouncing sheet, and a second screw. The bracket member includes a card base part and an extension part, and one side of the card base part is provided with a screw base. One side of the extension part is connected to the card base part, and the other side of the extension part is provided with a connection part. The first screw is threadedly connected to the screw base, and can press the SSD card to the screw base. The conductive bouncing sheet has a first end part and a second end part, the first end part is sandwiched between the first screw and the screw base, and the second end part corresponds to the connection part.

Abstract: A support assembly and a chassis structure for positioning and support of large and heavy computer cards. The chassis structure includes a housing, a main board in the housing, and a graphics card slot on the main board. The housing includes a positioning frame on the main board and the support assembly on the frame. The support assembly is detachable. The support assembly includes positioning base plate, positioning member, and adjusting member. The positioning member is on a base which is detachable from the positioning frame. The adjusting member is moveable. The positioning member includes a first support portion, the adjusting member includes a second support portion. Depending on card size, either the first support portion or the second support portion abuts against an end side of a graphics card away from the graphics card slot, to position and firmly hold in place graphics cards of different sizes.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: An inspection method includes the following steps: identifying a plurality of patterns within an image; and comparing the plurality of patterns with each other for measurement values thereof. The above-mentioned inspection method uses the pattern within the image as a basis for comparison; therefore, measurement values of the plurality of pixels constructing the pattern can be processed with statistical methods and then compared, and the false rate caused by variation of a few pixels is decreased significantly. An inspection system implementing the above-mentioned method is also disclosed.

Abstract: A method for promoting semiconductor manufacturing yield comprising the following steps and a computer readable medium encoded with a computer program implementing the method is provided. First, a processed layer is inspected to generate an inspected image with defects thereon. Next, the inspected image is aligned to an original design layout information of the processed layer. In addition, the defects are classified according to geometric features of the original design layout information of the processed layer and at least previous one layer and/or at least next one layer.

Abstract: A method of classifying the defects on a wafer having some same chips and corresponding system is provided. After receiving images formed by scanning the wafer using a charged particle beam, these images are examined such that both defective images and defect-free images are found. Then, the defect-free images are translated into a simulated layout of the chip, or a database is used to provide the simulated layout of the chip. Finally, the defects on the defective images are classified by comparing the images with the simulated layout of the chip. The system has some modules separately corresponds to the steps of the method.

Abstract: A method for filtering noises in an image scanned by charged particles includes steps of grouping pixels with similar types in the image into a plurality of pixel groups; and removing noises for each pixel group in the image according to a corresponding noise model to obtain the scanned image with better quality and/or contrast. A system for filtering noises in an image scanned by charged particles is also disclosed.

Abstract: A plurality of points with identical geometric feature is compared with their SEM characteristic features to inspect defect in a localized image. Original design information is included in the geometric feature such that absolute compare can be performed in this inspection method. Further, this method can also be applied to the localized image with or without repeated or redundant pattern.

Abstract: A method of classifying the defects on a wafer having some same chips and corresponding system is provided. After receiving images formed by scanning the wafer using a charged particle beam, these images are examined such that both defective images and defect-free images are found. Then, the defect-free images are translated into a simulated layout of the chip, or a database is used to provide the simulated layout of the chip. Finally, the defects on the defective images are classified by comparing the images with the simulated layout of the chip. The system has some modules separately corresponds to the steps of the method.

Abstract: A method for determining a defect during charged particle beam inspection of a sample locates at least one examination region within a charged particle microscopic image of the sample by making reference to a database graphic of the sample corresponding to the charged particle microscopic image. Each located examination region concerns at least one element of the sample, and each element has at least one characteristic in common. At least one point response value is then generated for each point in the located examination regions. The presence of a defect at the location of the concerned point is then determined by applying at least one decision tree operator to the generated point response values of the concerned point. Applications of the proposed method as a computing agent and a charged particle beam inspection system are also disclosed.

Abstract: A method for determining a defect during charged particle beam inspection of a sample locates at least one examination region within a charged particle microscopic image of the sample by making reference to a database graphic of the sample corresponding to the charged particle microscopic image. Each located examination region concerns at least one element of the sample, and each element has at least one characteristic in common. At least one point response value is then generated for each point in the located examination regions. The presence of a defect at the location of the concerned point is then determined by applying at least one decision tree operator to the generated point response values of the concerned point. Applications of the proposed method as a computing agent and a charged particle beam inspection system are also disclosed.

Abstract: Method of classifying the defects on a wafer having some same chips and corresponding system. After receiving images formed by scanning the wafer using a charged particle beam, these images are examined such that both defective images and defect-free images are found. Then, the defect-free images are translated into a simulated layout of the chip, or a database is used to provide the simulated layout of the chip. Finally, the defects on the defective images are classified by comparing the images with the simulated layout of the chip. The system has some modules separately corresponds to the steps of the method.