An industrial information hub (IIH) and an industrial development hub (IDH) serve as an industrial ecosystem platform where multiple participants can deliver repeatable and standardized services relevant to their core competencies. The IIH system is centered around the development of an ecosystem that creates and delivers value to users—including industrial enterprises, OEMs, system integrators, vendors, etc.—through the aggregation of digital content and domain expertise. The IIH system serves as a trusted information broker between the ecosystem and the OT environments of plant facilities, and provides a platform for connecting assets, contextualizing asset data and providing secure access to the ecosystem. As part of this ecosystem, the IIH system uses a secure remote access architecture to allow users to remotely access data on their plant floor assets via a virtual private network connection.

It is possible to more efficiently make a factory plan configured to maximize a productivity index.

Provided is a factory plan device including a calculation unit configured to specify a process and a production resource candidate based on a shape of a component of a target product by inputting past production performance data of a product, production volume data, design data of the product, specification data of a production resource, and layout data of a factory, and to calculate a process plan configured to determine order of the process and the production resource, a production plan configured to determine working date and time of the production resource, and a layout of the production resource so as to maximize a predetermined productivity index in the factory.

An abnormality analysis device including: an overall information obtainer that obtains overall information indicating an overall feature amount of a manufacturing system; an overall abnormal degree calculator that calculates an overall abnormal degree that is an abnormal degree of a whole of the manufacturing system by statistically processing the overall information; an individual information obtainer that obtains individual information indicating a feature amount of each of the plurality of constituent elements; an individual abnormal degree calculator that calculates an individual abnormal degree that is an abnormal degree of each of the plurality of constituent elements by statistically processing the individual information; and a determiner that determines whether or not the overall abnormal degree exceeds a threshold value, wherein the individual abnormal degree calculator calculates the individual abnormal degree when the determiner determines that the overall abnormal degree exceeds the threshold value.

Provided is a production system including: a first industrial machine configured to control a second industrial machine; and circuitry configured to acquire data relating to an operation of at least one of the first industrial machine or the second industrial machine, wherein the first industrial machine comprises a synchronous area regularly subjected to synchronization and an asynchronous area different from the synchronous area, and wherein the first industrial machine is configured to: write the data into the asynchronous area; and transmit the data written in the asynchronous area to an external device.

A processor may analyze a physical environment. One or more portions of the physical environment may have an edge computing resource requirement. The processor may determine, based on the analyzing, one or more additional edge computing resources to be placed in a surrounding area associated with the one or more portions of the physical environment. The processor may situate, automatically, the one or more additional edge computing resources on a material handling device in the surrounding area and that is directed toward the one or more portions of the physical environment.

A sensor control system (202) for managing at least a first set of one or more sensors (101) for monitoring a first domain of an industrial process and a second set of one or more sensors (102) for monitoring a second domain of the industrial process, wherein the sensor control system (202) comprises at least a first reinforcement learning, RL, agent (A1) and a second RL agent (A2), wherein the first and second RL agents were trained using reinforcement learning and a process graph (196) representing the industrial process.

An industrial integrated development environment (IDE) supports collaborative tools that allow multiple designers and programmers to remotely submit design input to the same automation system project in parallel while maintaining project consistency. The industrial IDE also permits localized development of system projects, and provides an infrastructure for intelligently brokering between conflicting edits submitted to common portions of the system project. Project edits submitted to the IDE system, both applied and unapplied, are stored as edit records, allowing edits to be selectively undone or applied either manually or as part of a rollback to a milestone version.

A method for creating a redundant automation system, a computer program and a computer-readable medium, wherein the redundant automation system includes at least one automation installation to be controlled that is installed at an installation location and two control applications that are communicatively interconnected via a synchronization path, and includes a plurality of communication hubs and communication paths connecting these to one another, where one of the control applications operates as the master and the other control application operates as a reserve, such that when the control application operating as the master fails, the control application operating as the reserve function as the master, and where the locations of the computing resources for the control applications are selected such that the control applications are connected to the at least one automation installation via two different communication paths preferably having no or a minimal number of common communication hubs.

Example wireless feedback control systems disclosed herein include a receiver to receive a first measurement of a target system via a first wireless link. Disclosed example systems also include a neural network to predict a value of a state of the target system at a future time relative to a prior time associated with the first measurement, the neural network to predict the value of the state of the target system based on the first measurement and a prior sequence of values of a control signal previously generated to control the target system during a time interval between the prior time and the future time, and the neural network to output the predicted value of the state of the target system to a controller. Disclosed example systems further include a transmitter to transmit a new value of the control signal to the target system via a second wireless link.

An industrial device matching method and apparatus are used for acquiring a corresponding relationship between industrial devices in different industrial data sources to provide basis for industrial data analysis. The method, in an embodiment, includes collecting data of at least two industrial data sources; determining a first relationship between various industrial devices in each industrial data source, and determining a first relationship topology between the industrial devices in the industrial data source; and comparing the first relationship topologies corresponding to various industrial data sources, to determine a first corresponding relationship between industrial devices in industrial data sources, the first corresponding relationship enabling the first relationship topologies corresponding to at least two industrial data sources to be similar. A relationship between industrial devices in different industrial data sources is determined by comparing a relationship topology between devices according to the similarity of relationships between the devices in different industrial data sources.