Abstract:
A system includes a station information system, a portable vision system, and a quality monitoring system. The station information system includes a station computing device configured to provide a notification related to a manufacturing operation performed on a component. The portable vision system includes a quality check module configured to include a station task module configured to execute a quality check task based on an image. The quality monitoring system includes a quality monitoring computing device configured to request the portable vision system to execute the quality check task based on a trigger message from the station information system and to provide a task data message related to the quality check task executed by the portable vision system to the station information system. The station computing device is configured to provide the notification based on the task data message from quality monitoring system via the user interface device.
Abstract:
Provided are a damage figure creation supporting apparatus, a damage figure creation supporting method, a damage figure creation supporting program, and a damage figure creation supporting system that enable efficient creation of a damage figure using marking colors. The damage figure creation supporting method includes a step of acquiring an image obtained by photographing a surface of a structure in color, a step of analyzing the acquired image and detecting markings applied to damaged portions on the surface of the structure for respective colors, and a step of creating a damage figure, based on detection results of the markings for the respective colors. The damage figure is configured as a diagram of tracing the markings and has a layered structure with layers each corresponding to a color.
Abstract:
In some implementations, a test device may initiate a set of measurements by a set of sensors of the test device and of a device under test (DUT), wherein the DUT is a memory device. The test device may obtain the set of measurements of the DUT from the set of sensors based on initiating the set of measurements. The test device may analyze the set of measurements of the DUT, using a first model, to identify one or more defects present with the DUT. The test device may determine, using a second model, that the one or more defects present with the DUT satisfy a failure threshold. The test device may provide, based on the failure threshold being satisfied for the DUT, an output indicating that the failure threshold is satisfied for the DUT.
Abstract:
A method of identifying an item on a surface of a workpiece is disclosed. An optical device identifies an item on the surface of a workpiece. An item identification system includes a light projector and a photogrammetry system. One of the light projector and the photogrammetry system generates a three-dimensional coordinate system within the work cell. One of the light projector and the photogrammetry system identifies a location of the surface of the workpiece within the three-dimensional coordinates system. The controller calculates geometric location of the item on the surface of the work piece in the three-dimensional coordinate system as identified by the optical device. The controller signals the light projector to project a beam of light onto the surface of the workpiece identifying a disposition of the item disposed upon the surface of the workpiece.
Abstract:
A defect inspection device is provided with an illumination optical system that irradiates light or an electron beam onto a sample, a detector that detects a signal obtained from the sample through the irradiation of the light or electron beam, a defect detection unit that detects a defect candidate on the sample through the comparison of a signal output by the detector and a prescribed threshold, and a display unit that displays a setting screen for setting the threshold. The setting screen is a two-dimensional distribution map that represents the distribution of the defect candidates in a three dimensional feature space having three features as the axes thereof and includes the axes of the three features and the threshold, which is represented in one dimension.
Abstract:
A system and method is disclosed for detecting defects in the surface of a workpiece such as a fiberglass or composite part. A light source is positioned to direct light at the workpiece at an oblique angle with respect to the surface of the workpiece. At least one camera is positioned to detect light reflected from the workpiece and to generate a light signal corresponding to the reflected light. A polarizing lens is positioned between each of the at least one cameras and the workpiece. A processor is coupled to each of the at least one cameras to receive the corresponding light signals. The processor is programmed to process the light signals to detect any defects in the surface of the workpiece based on relative magnitudes of the received light signal. A video display and a printer are preferably coupled to the processor to show any detected defects.
Abstract:
A defect recognition procedure in prepreg materials (1) draws a first transversal cross line (4b) at the beginning boundary (3b) of a defective area (2) in a prepreg material (1). A second transversal cross line (4e) at the end boundary (3e) of a defective area (2) is drawn as well. The cross lines (4b, 4e) form an angle (α) with respect to the prepreg material (1) motion direction (5).Each transversal cross line (4b, 4e) delimiting the beginning and the end of a defective area (2) has identification codes (Bi, Ei).
Abstract:
A defect recognition procedure in prepreg materials (1) draws a first transversal cross line (4b) at the beginning boundary (3b) of a defective area (2) in a prepreg material (1). A second transversal cross line (4e) at the end boundary (3e) of a defective area (2) is drawn as well. The cross lines (4b, 4e) form an angle (α) with respect to the prepreg material (1) motion direction (5).Each transversal cross line (4b, 4e) delimiting the beginning and the end of a defective area (2) has identification codes (Bi, Ei).
Abstract:
A device inspection apparatus inspects a plurality of semiconductor devices on an individual device basis. An inspection target sorting part (8) omits an execution of an inspection to be applied to the semiconductor devices according to information which specifies a defective device that has been determined to be defective in a manufacturing process that has been applied to the device.
Abstract:
A processing method includes obtaining a processing image of a apparatus and performing a second processing on the processing image to generate a target image to analyze the target image according to a target defect detection method to realize defect detection of the apparatus. The processing image is obtained by performing a first processing on an initial image of the apparatus. The first processing includes performing scale processing on the initial image according to defect parameters corresponding to the initial image.