A visualized data generation device includes an acquisitor, an analyzer, and a generator. The acquisitor acquires manufacturing data including one or more pieces of first data Yi regarding a product state with respect to one product. The analyzer analyzes the first data Yi acquired by the acquisitor and derives a first index value with respect to each piece of the first data Yi. The generator generates visualized data including a first analysis result display region for causing a display device to display information about the first index value. The generator generates the visualized data in which an amount of information and a priority is set for each first analysis result display region on the basis of the first index value and a display form of the first analysis result display region is set on the basis of the amount of information and the priority.

An approach alerting users based on a detected defect during manufacturing quality inspection based on graphical images is disclosed. The approach initiates a device inspection, wherein a model controller collects metadata about a product to be inspected and select a first model with a highest score to identify defects in the device. The approach utilizes an API to obtain results from the inspection and after determining that another model is available, initiating the second model run via an edge device performing the inspection of the device. And the algorithm awaits a response in detecting a defect during either the first model run or the second model run, providing an alert detailing the defect detected in the device.

A control method and a control device of fabrication equipment are provided. The method includes: when defects existing on the display panels are detected, determining a category of the defects belonging to, and obtaining a number of each of the detects to obtain a plurality of detection data; obtaining a total of each of the defects existing on the display panels manufactured by each of the fabrication equipment according to the plurality of detection data; judging whether an exception occurring on the fabrication equipment according to the total of each defect to perform exception handling on the fabrication equipment.

A method, system, and computer program product, include recording high-frequency wave data of local arid adjacent fault curves of a power grid to compare the high-frequency wave data with historical fault data to detect an actual fault region in the power grid, the power grid having a plurality of sensors distributed in the power grid, each sensor being upstream of one adjacent sensor and downstream of an other adjacent sensor.

A prediction model creation apparatus includes a feature amount acquisition unit that acquires values of types of feature amounts that are calculated from operating state data indicating an operating state of a production facility that produces a product, for both a normal time at which the production facility produces the product normally and a defective time at which a defect occurs in the product that is produced, a feature amount selection unit that selects a feature amount effective in predicting the defect from among the acquired types of feature amounts, based on a predetermined algorithm that specifies a degree of association between the defect and the types of feature amounts, from the values of the types of feature amounts acquired at the normal time and the defective time, and a prediction model construction unit that constructs a prediction model for predicting occurrence of the defect, using the selected feature amount.

A control system (1) according to the present invention comprises: a control device (100) that monitors the operation of a plurality of moving parts for machining a workpiece (155), and controls the operation of the plurality of moving parts in each control cycle by issuing command values to the plurality of moving parts; and an inspection device (200) for inspecting the workpiece (155). The control device (100) comprises: an identification unit (160) for identifying, based on inspection results of the inspection device (200) and the command values issued to the plurality of moving parts, which moving part from among the plurality of moving parts has caused an abnormality in the inspection results; and a storage unit (170) for collecting and storing data on the moving part that has been identified by the identification unit (160) and caused the abnormality in the inspection results.

A distributed light-guided processing method includes obtaining an order from a requester, for at least one completed product. Raw components are provided to at least one selected remote processing location. The selected remote processing location includes a light guided system. Work instructions are provided to the selected remote processing location, wherein the work instructions enable the light guided system to guide construction of the completed product. The completed product is processed, using at least the raw components, the work instructions, and the light guided system. The completed product is shipped from the selected remote processing location upon completion of the processing.

Embodiments of present disclosure relate to adjusting a robot motion path. In the method for adjusting a robot motion path, a first processing procedure may be performed on a first workpiece to obtain a first product. Then, first process data may be obtained, where the first process data describes an attribute of the first processing procedure for obtaining the first product from the first workpiece. Next, based on the obtained first process data, a robot motion path of a second processing procedure that is to be performed on the first product by a robot may be adjusted. Further, embodiments of present disclosure provide apparatuses, systems, and computer readable media for adjusting a robot motion path.

A manufacturing system includes a plurality of manufacturing facilities, a remote terminal, and a remote authority controller that controls authority of a remote operation from the remote terminal. When an error is detected in a first manufacturing facility out of the plurality of manufacturing facilities, the remote authority controller grants authority of a remote operation of a second manufacturing facility to the remote terminal. The second manufacturing facility causes the error and is other than the first manufacturing facility.

A diagnostic device is a device for estimating the tension of a belt of an industrial machine for transmitting power, and is provided with a control unit configured to control a diagnostic operation in which the belt is driven, a data acquisition unit configured to acquire at least feedback data at the time of the diagnostic operation, a preprocessing unit configured to analyze frequency-gain characteristics of the feedback data and create, as input data, a range including a resonant frequency and an anti-resonant frequency in the characteristics, and a machine learning device configured to perform processing related to machine learning, based on the data created by the preprocessing unit. The diagnostic device supports inference or abnormality detection of the value of the belt tension.