The process control system converts, into images, time-varying waveforms of inspection data of an assembled product, parts, and sub-assembling processes that constitute the assembling process, performs matching between an inspection waveform image (IWI) of the assembled product and a predetermined deterioration pattern image (DPI), determines whether IWI of the assembled product is similar to DPI, performs, when IWI is similar to DPI, a first determination for performing matching between an IWI of each of sub-assembling processes and DPI and determining whether there is a sub-assembling process similar to DPI, performs, when there is a sub-assembling process similar to DPI in the first determination, a second determination for performing matching between IWI of each of parts assembled in the sub-assembling process similar to DPI and DPI and determining whether there is a part similar to DPI, and specifies a deterioration factor based on results of the first and second determinations.

A product state estimation device includes: an examination result acquisition device that acquires an examination result related to a state of a product obtained through each shot by a die-casting machine; a time series data acquisition device that acquires time series data based on an output from a sensor that detects an operation state of the die-casting machine at each shot; a time series data manipulation device that performs manipulation that clips data of a predetermined time interval out of the time series data; an estimation model generation device that generates an estimation model by using a neural network with the examination result of the product and the manipulated time series data as learning data; and an estimation device that estimates information related to quality of the product based on the manipulated time series data obtained from a plurality of detection signals at each shot by using the estimation model.

A visual inspection data collection and analysis system comprising: a plurality of visual inspection appliances (VTA) configured to inspect and acquire visual inspection data relating to inspected items; and a data collection and analytics server (DCAS) configured to receive information comprising the visual inspection data from the multiple VIAs and to analyze the received information to form a big data analysis. The VIAs are adapted for detecting defects or gating or counting the inspected items without the involvement of the DCAS.

A method for generating a twin sensor by parameter inheritance, the twin sensor being suitable for substituting a sensor including coupling a mobile terminal to the sensor to transmit signals, configuring the sensor by way of the mobile terminal, wherein the configuring is based on configuration parameters transmitted to the sensor by way of the mobile terminal, generating a one-to-one generation code for inheriting the parameters by way of a configuration module, based on the configuration parameters, and providing the generation code by the configuration module, for generating the twin sensor by way of inheriting the parameters, wherein the inheriting of the parameters is based on the generation code.

Broadly speaking, the present techniques provide a method and system for controlling a wafer production process in real-time using a trained machine learning, ML, model. Advantageously, the ML model uses multiple sensed parameters to determine a state of a plasma used in the wafer production process, and this can be used to adjust at least one control parameter of a plasma reactor used in the wafer production process to reduce process variability.

A system for manufacturing a product having predetermined specifications includes a working station for manufacturing the product, which has a plurality of working operating parameters; first sensors for detecting first data regarding the working environment; second sensors for detecting second data regarding the plant where the system is installed; and a first control device operatively connectable to the working station and to the first and the second sensors, which has a storage unit containing a plurality of optimal operating parameters. During operation of the working station, the control device detects the first and the second data and compares the working operating parameters with the corresponding optimal operating parameters so as to detect deviations. A second device determines the optimal operating parameters during operation of the working station.

A monitoring and inspection system for a work area includes a non-visual sensory detection sensor, such as a microphone or vibration detection sensor, and a processor. The sensor is configured to sense sounds or vibrations generated in the work area during the performance of an action that are then received by the processor. The processor analyzes the received acoustic and/or vibrational signals and compares the received signals to an expected signal to verify that the identified acoustic and/or vibration signature of the detected signal is an acoustic and/or vibration signature associated with the operational step that was performed to confirm that the operational step has been performed, and that it has been performed properly.

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.

A system for wireless monitoring of operating and production parameters of a clipping machine for food production having a sealed housing protected at least against moisture. The system comprises at least one measuring and control device for controlling the production process and measuring the operating and/or production parameters of the machine, sensors for determining operating parameters of the machine, devices for determining production parameters of the machine, at least one wireless communication device, a user interface and display device, and at least one smart device having at least an optical reading unit, wherein the at least one wireless communication device is configured to generate login details for wireless communication and encrypt the login details into a binary code which can be read by the optical reading unit of the smart device via the user interface and display device.

A computer-implemented system and method for searching comprises receiving digital twin instance part assembly information (IPAD) from a sensor scan of a physical part assembly produced by assembling a first physical part with a second physical part. Digital twin framework part assembly data (FPAD) is received representing a correctly assembled physical part assembly and that corresponds to the physical part assembly. Context data associated with a context within which the physical part assembly is produced is also received. The FPAD is compared with the IPAD, utilizing the context data, to determine whether a deviation of the IPAD from the FPAD exceeds a threshold. Responsive to the deviation exceeding a threshold, the method comprises providing corrective information to a device of an assembler for re-assembling the first physical part to the second physical part to produce a reassembled physical part assembly based on the corrective information.