A component mounter images suction states of components picked up by a suction nozzle, processes images of the suction states of the components to recognize the suction state of the component, and stores the images in a storage device with linking production information related to the components. An inspection machine images a mounted state of each component on a board, processes an image of mounted state of each component to recognize the mounted state of each component, and inspects whether a mounting error occurred for each component based on the recognition result. The inspection machine determines that a mounting error occurred for any of the components the image of the mounted state of the component for which a mounting error was determined to have occurred and a searched image of the suction state of the component are displayed on the display monitor in a comparative manner.

Provided is a computer-implemented method for determining at least one quality attribute for at least one defect of interest, including the steps: a. providing an input data set including the at least one defect of interest; b. determining the at least one quality attribute for the at least one defect of interest using a classification algorithm based on the input data set; and c. providing the determined at least one quality attribute and/or additional output information as output. Further, a computing unit and a computer program product are provided.

A component mounter images suction states of components picked up by a suction nozzle, processes images of the suction states of the components to recognize the suction state of the component, and stores the images in a storage device with linking production information related to the components. An inspection machine images a mounted state of each component on a board, processes an image of mounted state of each component to recognize the mounted state of each component, and inspects whether a mounting error occurred for each component based on the recognition result. The inspection machine determines that a mounting error occurred for any of the components the image of the mounted state of the component for which a mounting error was determined to have occurred and a searched image of the suction state of the component are displayed on the display monitor in a comparative manner.

A computer device for validating the installation of a part in a device is provided. The computer device is programmed to receive a first image of a device identifier for the device, receive a second image of a part identifier for the part, receive a third image of serial identifier the part, compare the device identifier, the part identifier, and the serial identifier to validate the part, receive a fourth image of the part after installation, determine whether the part was properly installed based on the fourth image, if the determination is that the part was not properly installed, instruct the display device to display a notification that the part was improperly installed, and if the determination is that the part was properly installed, store installation information.

Provided is a management system for performing quality management on manufacturing equipment. A management system that includes: an acquisition component that acquires state information for manufacturing equipment that is subject to management; a determination component that, on the basis of the acquired state information, determines whether an event has occurred; a display component that displays both an image that schematically or realistically represents a manufacturing line included in the manufacturing equipment and, separated into the four perspectives Machine, Man, Material, and Method, indexes that indicate the likelihood that there is a factor that caused an event; and an output component that, when a specific event has occurred, outputs, in response to a user selection, analysis results for each of one or more factors belonging to each of the four perspectives, the analysis results indicating a likelihood of having caused the specific event that occurred.

Provided is a management system for performing quality management on production equipment. A management system that includes: an acquisition component that acquires status information for production equipment that is subject to management; a detection component that, on the basis of the acquired status information, detects the occurrence of some event; and a display component that displays, separated according to inclusion in the four perspectives Machine, Man, Material, and Method, a plurality of factors that could be presumed to have caused the detected event in a manner in which the contents thereof and a probability of having caused the event can be compared.

A tool wear monitoring and predicting method is provided, and uses a hybrid dynamic neural network (HDNN) to build a tool wear prediction model. The tool wear prediction model adopts actual machining (cutting) conductions, sensing data detected at the current tool run of operation and the predicted tool wear value at the previous tool run of operation to predict a predicted tool wear value at the current tool run. A cyber physical agent (CPA) is adopted for simultaneously monitoring and predicting tool wear values of plural machines of the same machine type.

An automated constructing method of cloud manufacturing service is provided for a distributed system including a virtual machine and a service manager. The method includes: obtaining a library package which is locally built, analyzing the library package to obtain key information, and generating a library information file; automatically generating a project source code file according to the library information file, and generating a web service package according to the project source code file; and deploying, by the service manager, the web service package on the virtual machine.

Provided is a computer-implemented method for determining at least one quality attribute for at least one defect of interest, including the steps: a. providing an input data set including the at least one defect of interest; b. determining the at least one quality attribute for the at least one defect of interest using a classification algorithm based on the input data set; and c. providing the determined at least one quality attribute and/or additional output information as output. Further, a computing unit and a computer program product are provided.

A tool wear monitoring and predicting method is provided, and uses a hybrid dynamic neural network (HDNN) to build a tool wear prediction model. The tool wear prediction model adopts actual machining (cutting) conductions, sensing data detected at the current tool run of operation and the predicted tool wear value at the previous tool run of operation to predict a predicted tool wear value at the current tool run. A cyber physical agent (CPA) is adopted for simultaneously monitoring and predicting tool wear values of plural machines of the same machine type.