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.

A method of detecting and classifying anomalies during semiconductor processing includes executing a wafer recipe a semiconductor processing system to process a semiconductor wafer; monitoring sensor outputs from a sensors that monitor conditions associated with the semiconductor processing system; providing the sensor outputs to models trained to identify when the conditions associated with the semiconductor processing system indicate a fault in the semiconductor wafer; receiving an indication of a fault from at least one of the models; and generating a fault output in response to receiving the indication of the fault.

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.

A plant control system includes a plant system and a control system controlling the plant system. Runtime conditions of an operating point of the plant control system are received. The runtime conditions include a runtime state of the plant system, a runtime output of the plant system, and a runtime control action applied to the plant system. Reference conditions of a reference point corresponding to the operating point are determined. Stability radius measures of a state difference, an output difference, and a control action difference are computed. One or more of an observability anomaly indicator, health observability indicator, tracking performance anomaly indicator, tracking performance health indicator, controllability anomaly indicator, and controllability health indicator are determined based on respective spectral correlations between two of the stability radius measure of the output difference, the stability radius measure of the state difference, and the stability radius measure of the control action difference.

An apparatus for identifying a path pattern of devices that produces a defective product in a production line where a product is produced via a plurality of device is provided. The device is configured to estimate a path pattern quality indicating a quality of a group of products produced through a production path included in a path pattern, based on a production path quality and an association relationship between a path pattern and a production path indicating devices via which the product is produced and an order of passing through the devices; and to identify a path pattern suspected to be defective based on the estimated path pattern quality.

Example implementations involve fault detection and isolation in industrial networks through defining a component as a combination of measurements and parameters and define an industrial network as a set of components connected with different degrees of connections (weights). Faults in industrial network are defined as unpermitted changes in component parameters. Further, the fault detection and isolation in industrial networks are formulated as a node classification problem in graph theory.

Example implementations detect and isolate faults in industrial networks through 1) uploading/learning network structure, 2) detecting component communities in the network, 3) extracting features for each community, 4) using the extracted features for each community to detect and isolate faults, 5) at each time step, based on the faulty components provide maintenance recommendation for the network.

The disclosure provides a method for detecting a display screen peripheral circuit, by receiving a quality detection request sent by a console deployed on a production line of the display screen peripheral circuit, where the quality detection request includes an image of the display screen peripheral circuit captured by an image capturing device on the production line of the display screen peripheral circuit; enlarging or reducing the image of the display screen peripheral circuit to obtain an image to be detected, where the defect detection model is obtained by using a historical image of a defective display screen peripheral circuit to perform object detection FAST RCNN algorithm training; inputting the image to be detected into the defect detection model to obtain a defect detection result; and determining, according to the defect detection result, quality of a display screen peripheral circuit corresponding to the image of the display screen peripheral circuit.

This disclosure relates to a method of machining articles from a disc comprising superhard material, such as polycrystalline diamond (PCD) or polycrystalline cubic boron nitride (PCBN). The method includes providing a disc having a diameter of no more than 100 mm and a thickness of no more than 10 mm, providing a nesting pattern, scanning the disc to identify and locate any flaws in the disc and subsequently creating a machining program that takes into account said flaws.

An integration server manages production in a manufacturing line that includes a first stage and a second stage carried out after the first stage. The integration server includes a communicator that acquires a first production log and a second production log. The first production log includes a first production count of processing objects in the first stage. The second production log includes the number of processing objects in the second stage. The integration server also includes an irregularity detector that detects the presence of irregularity in the first production log and the second production log on the basis of the first production count and the number of the processing objects in the second stage.

Provided is a method for computer-aided processing of quality information of an object manufactured by stacked printed layers in an additive manufacturing system, including the steps of: receiving a quality indicator for each printed layer of the object from the manufacturing system, assigning a color out of a predefined set of colors to each quality indicator depending on the value of the quality indicator, visualizing the quality indicators of the received manufactured layers as a sequence of colored bars ordered according to the sequence of the manufactured layers the color of each bar indicating the value of the quality indicator of the respective printed layer on a graphical user interface.