Exemplary embodiments relate to methods, mediums, and systems for associating information, including critical-to-quality (CTQ) information such as minimum or maximum part dimensions, with parts in a three-dimensional model of a product. The information may be identified by performing a failure mode effect analysis (FMEA) against the model. The information is stored with the model data (e.g., in the form of an annotation applied to a model feature corresponding to the part in question). The model data may be consulted by product lifecycle management (PLM) applications during various phases of the product's lifecycle. Among other possibilities, the information may be used to automatically generate regulatory compliance documentation, to ensure product quality standards are met during a manufacturing process, or to perform postproduction quality monitoring of the product.

In one embodiment, a non-transitory computer readable medium may include computer-executable instructions that, when executed by a processor, may cause processor to receive a set of user data associated with a user that is attempting to access an electronic lock, receive a request to actuate a locking mechanism of the electronic lock configured to prevent the user from accessing a machine in an industrial automation system, actuate the locking mechanism in response to the request and the set of user data corresponding to an expected set of data, store a log of the request and the set of user data, and send the log to a cloud-based computing system.

An apparatus and methods of inspecting, analyzing, classifying, and/or grading quality of a transparent sheet using a data set of photoelasticity measurements, thickness measurements, segmentation specifications, measurement specifications and quality control specifications of the transparent sheet. A results measurement is calculated on a computing system, quality control specifications are applied to the results measurement allowing writing to the database and creating reports, sending results to an operator interface and machine control.

A state monitoring method, a state monitoring apparatus and a state monitoring system for a developing device are provided. After image information is obtained through the acquired video information of the developing device, it is determined by an analysis unit whether the image information includes nozzle anomaly information, and alarm information is issued after the nozzle anomaly information is determined. Moreover, similarity between the image information that does not include the nozzle anomaly information and second preset nozzle anomaly information is compared, and the nozzle information is stored in the analysis unit in a case that the similarity between the image information and the second preset nozzle anomaly information is greater than a first threshold.

A processing apparatus group management system manages operational statuses of a processing apparatus group that is a group of substrate processing apparatuses. This system includes an information storage, a display, and a display controller. The information storage stores apparatus-specific information specific to each substrate processing apparatus, and apparatus operational information relating to the operational statuses of substrate processing apparatuses and continuously transmitted from the substrate processing apparatuses. The display controller causes the display to display the operational status of each substrate processing apparatus as an operational status table in accordance with the apparatus-specific information and the apparatus operational information about the substrate processing apparatus. The operational status table includes display items including an apparatus identifier used to identify each substrate processing apparatus, and the number of times an abnormal processing stop occurs in each substrate processing apparatus. This allows collective management of the operations statuses of the substrate processing apparatuses.

Implementations disclosed describe a method of using a model to predict a change of a physical state of a sample caused by one or more stages of a technological process in a substrate processing apparatus and obtaining imaging data associated with an actual performance of the one or more stages of the technological process. The imaging data includes a distribution of one or more chemical elements for a number of regions of the sample. The method further includes identifying, based on the imaging data, a difference between the predicted change of the physical state of the sample and an actual change of the physical state of the sample caused by the actual performance of the one or more stages of the technological process. The method further includes determining parameters of the model based on the identified difference.

A work support system is capable of avoiding situations where a worker performs erroneous work. The system includes an identification unit which identifies a target of an inquiry from a worker based on a video acquired by an imaging device, a selection unit which selects determination model information corresponding to each of one or more targets of inquiry identified by the identification unit from a storage unit storing determination model information to be used in a determination model. A determination unit determines whether each of the targets of inquiry is correct by using each of the determination models in which the determination model information, which was selected by the selection unit, corresponding to each of the one or more targets of inquiry identified by the identification unit, has been set in the determination model. An output unit outputs a determination result of the determination unit.

Various factors may cause an error between the shape of a workpiece machined by an industrial machine and the target shape of the workpiece. An image analysis device includes a first image generating section that generates first image data indicating a first distribution of locations on a workpiece of an error between a shape of the workpiece machined by an industrial machine and a pre-prepared target shape of the workpiece; a second image generating section that generates second image data indicating a second distribution of locations on the workpiece of an error between a command transmitted to the industrial machine for machining the workpiece and feedback from the industrial machine corresponding to the command; and a correlation acquisition section that obtains a correlation between the first distribution and the second distribution, based on the first image data and the second image data.

A semiconductor analysis system includes a machining device that machines semiconductor wafer to prepare a thin film sample for observation, a transmission electron microscope device that acquires a transmission electron microscope image of the thin film sample, and a host control device that controls the machining device and the transmission electron microscope device. The host control device evaluates the thin film sample based on the transmission electron microscope image, updates machining conditions based on an evaluation result of the thin film sample, and outputs the updated machining conditions to the machining device.

The embodiment of the present disclosure provides an Industrial Internet of Things for inspection data processing, comprising a management platform. The management platform is configured to perform operations including: determining an inspection task, the inspection task including detecting at least one detection site; sending instructions to an inspection robot based on the inspection task to move the inspection robot to a target position to be inspected; obtaining detection data based on the inspection robot, and determining subsequent detection or processing operations based on the detection data.