A work assistance device that assists works for resolving a plurality of problems for simultaneously occurring in a system having a plurality of devices for producing products, the work assistance device including a processor configured to acquire, at occurrence of the plurality of problems, actual historical information on a processing time desired to previously produce the product in each of the devices; perform maximum a posteriori probability estimation of a processing time desired to produce the product in each of the devices, based on prior distribution stored in a storage unit and the acquired actual historical information on the processing time; and determine a work priority order of each of the devices based on the estimated processing times, and output the work priority order.

An inspection management system manages, in a production line for a product including a plurality of processes, a final inspection for a product finished through the plurality of processes and a plurality of intermediate inspections before the final inspection. The production line includes a plurality of manufacturing apparatuses and a plurality of inspection apparatuses corresponding to the plurality of processes. The inspection management system includes an inspection data obtainer, an inspection result obtainer, and an inspection setting supporter that generates an inspection record diagram showing, as information about an inspection item in one of the plurality of intermediate inspections, a presence or an absence of a product determined defective in the final inspection and information identifying whether the product determined defective in the final inspection is determined defective under an inspection item in another of the plurality of intermediate inspections, and displays the inspection record diagram.

A non-transitory computer-readable medium stores instructions that, when executed by a processor, cause the processor to receive, via the processor, a characteristic of data to be collected from an operational technology (OT) device disposed within an OT network associated with an industrial automation system configured to perform an industrial automation process, determine, via the processor, that the characteristic exceeds a threshold value, and deploy, via the processor, in response to determining that the characteristic exceeds the threshold value, a container to a compute surface within the OT network that is disposed within a threshold distance of the OT device. The container is configured to receive the data from the OT device and process the received data.

A Self-monitoring manufacturing system adapted to produce at least one object. The system includes at least a first processing facility adapted to perform a respective first processing step with the object, and a production control unit, wherein the production data comprises nominal pre-processing object data. A production monitoring unit for checking a pre-processing object state of the object is arranged, such unit being adapted to obtain actual property data of the object in-line of the production in-advance of applying the first processing step, to generate deviation data by comparing the actual property data with the production data for the first processing step, and to provide the deviation data for performing the first production step with the first processing facility in deviation-adjusted manner.

A method can include receiving scheduled tasks associated with subsystems of a wellsite system wherein the scheduled tasks are associated with achievement of desired states of the wellsite system; transmitting task information for at least a portion of the scheduled tasks to computing devices associated with the subsystems; receiving state information via the wellsite system; assessing the state information with respect to one or more of the desired states; based at least in part on the assessing, scheduling a task; and transmitting task information for the task to one or more of the computing devices associated with the subsystems.

A system and method are provided for programming workpiece feature inspection operations for a coordinate measuring machine. An editing environment is operated to display a 3-dimensional workpiece representation comprising a first surface feature of a workpiece. A first feature surface sampling pattern is created having at least one pattern parameter adjusted to correspond to a first surface feature of the workpiece. A corresponding representation of the sampling pattern includes operative sampling pattern locations located proximate to the first surface feature. User operations in the GUI further adjust pattern parameters of the sampling pattern. The further adjustment of the pattern parameters simultaneously affects a plurality of the sampling pattern locations. The sampling pattern representation may include various types of operative and inoperative sampling pattern locations, which may be displayed in a manner that distinguishes them from one another, such as by being represented with different colors, shapes or patterns.

A vision-based product inspection system captures multiple images of each of multiple individual instances of a product as each instance passes through various phases of a production process. The system includes multiple cameras with each camera situated at a known location along a moving conveyor, conveyor belt, production line, or assembly line that moves instances of the product through various phases of the production process. Each camera can be associated with a known location along the conveyor and each image can be associated with a value representing the position of the conveyor as it moves product. Based on each camera's location and the values representing the conveyor's position, a sequence of images can be accumulated representing the progression of any single instance of a product as it moves through the production process. Automated quality control inspection can be performed by comparing or analyzing images in the sequence.

A real time monitoring system and a method thereof of an optical film manufacturing process are provided. The real time monitoring system includes a plurality of production systems and a cloud big data platform which connects to the plurality of production systems. The process data of the production line is collected by as production line data collector of the production system. The process data is uploaded to a database of the cloud big data platform. The historical process data across the plurality of production systems can be combined as a process waveform feature by a profile database. A processor connects to the database and the profile database. The differences between the process data and the process waveform feature are compared in real time. When the difference value exceeds a threshold value, an abnormal message is sent to the corresponding production line.

A method for performing an autonomous inspection. The method comprises traversing, by an autonomous sensor apparatus, a path through a site having three-dimensional objects located therein. The site includes three-dimensional objects located therein. The method comprises obtaining, by a plurality of sensors on-board the autonomous sensor apparatus, one or more data sets throughout the path. Each of the one or more data sets are associated with an attribute of one or more three-dimensional objects. The method comprises generating, by the first, second, or third processor, a working model from a collocated data set; and comparing, by the first, second, or third processor, the working model with one or more pre-existing models; to determine the presence and/or absence of anomalies. The presence and/or absence of anomalies are communicated as human-readable instructions.

A vision-based product inspection system captures multiple images of each of multiple individual instances of a product as each instance passes through various phases of a production process. The system includes multiple cameras with each camera situated at a known location along a moving conveyor, conveyor belt, production line, or assembly line that moves instances of the product through various phases of the production process. Each camera can be associated with a known location along the conveyor and each image can be associated with a value representing the position of the conveyor as it moves product. Based on each camera's location and the values representing the conveyor's position, a sequence of images can be accumulated representing the progression of any single instance of a product as it moves through the production process. Automated quality control inspection can be performed by comparing or analyzing images in the sequence.