Data is received that includes a feed of images of a plurality of objects passing in front of each of a plurality of inspection camera modules forming part of each of a plurality of stations. The stations can together form part of a quality assurance inspection system. The objects when combined or assembled, can form a product. The received data derived from each inspection camera module can be separately analyzed using at least one image analysis inspection tool. The analyzing can include visually detecting a unique identifier for each object. The images are transmitted with results from the inspection camera modules along with the unique identifiers to a cloud-based server to correlate results from the analyzing for each inspection camera module on an product-by-product basis. Access to the correlated results can be provided to a consuming application or process via the cloud-based server.

A method for monitoring an industrial process step of an industrial process by a monitoring system. A machine learning system of the monitoring system is provided that contains a correlation between digital image data as input data and process states of the industrial process step to be monitored as output data using at least one machine-trained decision algorithm. Digital image data is recorded by at least one image sensor of at least one image acquisition unit of the monitoring system. At least one current process state is determined using the decision algorithm by generating at least one current process state of the industrial process step as output data rom the recorded digital image data as input data of the machine learning system. The industrial process step is monitored by generating a visual, acoustic and/or haptic output as a function of the at least one determined current process state.

A robot state monitoring device 2 comprises: a camera which captures an image of a robot 3 under the control of a controller; a moving image generation unit which associates video data of the robot 3 acquired by the camera with input/output signals DO[1], AO[1], DI[1], and AI[1] of the controller along a time axis 830, and generates a moving image showing a state change of the robot 3 and the input/output signals DO[1], AO[1], DI[1], and AI[1]; and a moving image playback device which plays back the moving image generated by the moving image generation unit

The moving image generation unit acquires the values of the input/output signals DO[1], AO[1], DI[1], and AI[1] at the recording time of each frame under the same cycle as the frame rate of the video data.

A board production management device configured to manage a board production line including an initial notification section configured to issue notification information including at least one of a contents of an error cause or a contents of countermeasures when the error cause that requires countermeasures occurs at the board production line; and an escalation notification section configured to issue the notification information after escalating in a case in which the error cause is not resolved after a specified time has elapsed since the error cause occurred. Accordingly, because when the specified time has elapsed, a notification is issued as escalating the notifyee or escalating the contents of countermeasures to resolve error causes more effectively, and compared to conventional technology in which only re-notification of the occurrence of the error cause is performed, notification is performed more efficiently, enabling an error cause that requires countermeasures to be resolved more quickly.

A board production management device configured to manage a board production line including an initial notification section configured to issue notification information including at least one of a contents of an error cause or a contents of countermeasures when the error cause that requires countermeasures occurs at the board production line; and an escalation notification section configured to issue the notification information after escalating in a case in which the error cause is not resolved after a specified time has elapsed since the error cause occurred. Accordingly, because when the specified time has elapsed, a notification is issued as escalating the notifyee or escalating the contents of countermeasures to resolve error causes more effectively, and compared to conventional technology in which only re-notification of the occurrence of the error cause is performed, notification is performed more efficiently, enabling an error cause that requires countermeasures to be resolved more quickly.

[Problem] To provide an abnormal-sound detection device in which incorrect detection is rare. [Solution] An abnormal-sound detection device has an imaging means, an operation range identification means, a sound collection means, an abnormal-sound detection means, an abnormal-sound generation position identification means, and an abnormal-sound source determination means. The imaging means captures an image of a diagnosis object. The operation range identification means identifies and stores the operation range of the diagnosis object on the basis of the image captured by the imaging means. The sound collection means collects sounds arriving from the diagnosis object and the vicinity thereof. The abnormal-sound detection means detects abnormalities in sounds included in the collected sounds. When an abnormality in a sound is detected by the abnormal-sound detection means, the abnormal-sound generation position identification means identifies the position at which the abnormality of the sound was generated. The abnormal-sound source determination means compares the operation range and the abnormal-sound generation position of the diagnosis object, and determines whether the abnormality of the sound is derived from an abnormality of the diagnosis object.

In order to easily identify a specimen to be extracted because, for example, an item remains uninspected, from a rack 31 collected in a storage part 13 or the rack 31 taken out from the storage part, a camera of a smart device takes an image of the rack; and a calculation unit included in the smart device provides a mark, by AR technology, at the position of a specimen to be extracted. For example, the item that remains uninspected is identified on the basis of information about a combination of a rack ID and an identifier and information, which is received from an operation unit about specimens at respective positions. Thus, irrespective of a place or whether the specimen to be extracted is inside or outside of the device, the specimen to be extracted can be reliably specified from a plurality of specimen containers provided on a holder.

Systems, techniques, and computer-program products are provided for tracking and traceability of parts of a finished product. In some embodiments, the tracking and traceability generates streams of semantic data obtained from an imaging sensor system that records the execution of a manufacturing process in industrial equipment. The execution of the manufacturing process yields a finished product from initial materials and/or parts. The tracking and traceability also implements artificial reasoning about the execution of the manufacturing process to generate assertions that characterize the execution of the manufacturing process. Semantic data and assertions can be aggregated into a digital trace record that tracks a defined component of the finished product throughout the execution of the manufacturing process and permit tracing the component to a defined event within the manufacturing process.

A wireless field device for use in an industrial process control or monitoring system includes a controller configured to control operation of the wireless field device. Wireless communication circuitry is configured to wirelessly communicate with a remote location. An internal power source powers the wireless field device. An image capture device is coupled to the controller and configured to capture an image of an environment of the wireless field device. The controller is adapted to receive image information from the image capture device and transmit compressed image information to the remote location.

Systems, techniques, and computer-program products are provided for tracking and traceability of parts of a finished product. In some embodiments, the tracking and traceability generates streams of semantic data obtained from an imaging sensor system that records the execution of a manufacturing process in industrial equipment. The execution of the manufacturing process yields a finished product from initial materials and/or parts. The tracking and traceability also implements artificial reasoning about the execution of the manufacturing process to generate assertions that characterize the execution of the manufacturing process. Semantic data and assertions can be aggregated into a digital trace record that tracks a defined component of the finished product throughout the execution of the manufacturing process and permit tracing the component to a defined event within the manufacturing process.