Provided are a system and method for work quality assurance in vehicle manufacturing, which are capable of preventing defects in manufacturing, wherein the system for work quality assurance in vehicle manufacturing which assembles fastening objects to a vehicle transferred through a conveyor line through a working unit, includes a server configured to set a working area of the vehicle, assign work corresponding to the working area, check a position of the working unit in real time to calculate a stay period during which the working unit stays in the working area, receive work information from the working unit, and determine whether the work is successful on the basis of the stay period, the assigned work, and the work information.

The invention relates to a method (100) for controlling film production, in which at least one film is produced according to at least one formula information (R), the following steps being carried out: initiation of execution (210) of a film production process such that a film is produced on the basis of a specific formulation information (R); determination of monitoring information (I) during the execution (210) of the process; determination of at least one fingerprint (F) on the basis of the specific formula information (R) and on the basis of the monitoring information (I) such that the execution (210) of the process is characterised on the basis of the fingerprint (F); and comparison of the fingerprint (F) with a control matrix (M) such that at least one comparative result is determined in order to control the film production on the basis of the control matrix (M) as an evaluation basis.

A laser processing system includes a processing machine for performing laser processing on a processing target using a laser beam according to a predetermined processing design; a setting module for preparing a processing recipe including a plurality of set values for testing of processing parameters for the controlling the quality value of a predetermined quality item; a controller for repeatedly performing test processing for the processing target in multiple implementation rounds by driving the processing machine by selectively using any one of the set values for testing as the set value of the processing parameters according to a predetermined order; and an analysis module for analyzing each of results of the test processing and individually measuring the quality value of each of the results of the test processing.

An industrial monitoring system comprises a monitoring device attached to an industrial device by a bond. Sensor data collected by the monitoring device during a commissioning period is received and used to train a machine learning model. Subsequent to the commissioning period, additional sensor data is collected by the monitoring device. An abnormal state of the bond between the monitoring device and industrial device is determined based on the additional sensor data and a characteristic inferred by the trained machine learning model. A notification of the abnormal state is generated.

Disclosed is a method for automatically determining quality of a self-piercing riveting process, including the following operations: inputting standard values, acquiring data in real-time, and comparing data and determining quality of riveting. Riveting parameters and process curves are obtained in real time by a data acquisition system, the measured values for determining quality of riveting is calculated according to the real-time change of the riveting force curve and information of the riveted plates, the quality of the riveting process can be automatically determined by comparing the measured values and the standard values, the efficiency of monitoring quality is improved, inspection of all riveting points can be realized, abandonment of white vehicle bodies due to poor riveting quality is greatly reduced, and the problem that a large number of white vehicle bodies with defective quality cannot be found is avoided, and the riveting quality of the white vehicle bodies is guaranteed.

A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.

The present disclosure relates to a laser processing system including a processing machine for performing laser processing on a processing target using a laser beam according to a predetermined processing design; a setting module for preparing a processing recipe including a plurality of set values for testing of processing parameters for the controlling the quality value of a predetermined quality item; a controller for repeatedly performing first test processing for the processing target in multiple implementation rounds by driving the processing machine by selectively using any one of the set values for testing as the set value of the processing parameters according to a predetermined order; and an analysis module for analyzing each of results of the first test processing and individually measuring the quality value of each of the results of the first test processing, and selecting, among the set values for testing, a set value for testing used in a specific implementation round of the first test processing, at which the quality value that most satisfies predetermined reference quality is measured, as a set value for mass production of the processing parameters.

A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.

There is provided a configuration that includes a device-status-monitoring controller that stores, in a storage section, device data generated by the apparatus; an analysis-support controller that acquires the device data related to abnormality analysis information from the storage section based on basic information that includes: information that defines an abnormal event, at least one of the device data corresponding to the abnormal event, and step information indicating a step where the at least one of the device data is generated; and recipe-specific information that includes at least a recipe name; and a display device that displays the device data related to the abnormality analysis information in a manner that goes back to a past time from a time when a latest recipe specified by the recipe name is executed.

A method includes acquiring, by a vibro-acoustic sensor in a vicinity of a machine, vibro-acoustic signals due to an operation of the machine. The acquired vibro-acoustic signals are analyzed so as to estimate at least two operational parameters of the machine, selected from a group of the operational parameters consisting of an uptime factor, a production speed factor, and a production quality factor of the machine. An overall equipment effectiveness (OEE) of the machine is computed, the computed OEE including at least one of a minimum and a product of the at least two estimated operational parameters.