A method may include receiving, via a first computing node, a first pod from a second computing node. The method may also include retrieving a first image file that may include a first set of containers from a registry based on the first pod. The first set of containers may cause a control system to halt operations. The method may then involve generating a first package based on the first set of containers and storing the first package in a filesystem, receiving a second pod from the second computing node, and retrieving a second image file having a second set of containers from the registry. The second pod may include the second set of containers may cause the control system to update software components. The method may also involve generating a second package based on the second set of containers and storing the second package in the filesystem.

According to an aspect of the present disclosure, a computer-implemented includes creating a plurality of basic skill functions for a controllable physical device of an autonomous system. Each basic skill function includes a functional description for using the controllable physical device to interact with a physical environment to perform a defined objective. The method further includes selecting one or more basic skill functions to configure the controllable physical device to perform a defined task. The method also includes determining a decorator skill function specifying at least one constraint. The decorator skill function is configured to impose, at run-time, the at least one constraint, on the one or more basic skill functions. The method further includes generating executable code by applying the decorator skill function to the one or more basic skill functions, and actuating the controllable physical device using the executable code.

A substrate processing system comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device connected to each of the plurality of process chambers. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

A method for processing a takt at a station includes: obtaining takt data of each station within a preset time period, and determining a takt boxplot of each station according to the takt data; obtaining a material blocking time, a material shortage time and a failure time in each takt, determining an effective takt of each station based on the takt data, the material blocking time, the material shortage time and the failure time, and determining an effective takt mode; obtaining planning takt data of each station, generating a station takt wall station based on the takt boxplot, the effective takt mode and the planning takt data; determining a takt fluctuation status and a bottleneck of each station according to the station takt wall. A system for processing a takt at a station, an apparatus, and a storage medium are also disclosed.

A system for controlling automation includes a machine which collects data generated by performance of an operation by the machine. A user device displays a machine control interface (MCI) corresponding to the machine. The MCI displays the collected data to a touch interface of the user device, and defines at least one touch activated user interface element (UIE) for manipulating the data. The user device can be enabled as an automation human machine interface (HMI) device for controlling an operation performed by the machine, such that a touch action applied to a UIE of the MCI controls the operation. A prerequisite condition to enabling the user device as an automation HMI device can include activation of an enabling switch selectively connected to the user device. The MCI can be stored in a memory of the enabling switch and retrieved from the enabling switch by the user device.

A system includes an industrial automation component configured to receive a first voltage from a voltage source to enable the industrial automation component to perform one or more operations, a mechanical device configured to generate a second voltage, and a display configured to present image data. The display is configured to maintain presentation of the image data in absence of the first voltage received from the voltage source or the second voltage received from the mechanical device. The system also includes processing circuitry configured to use the second voltage generated by the mechanical device to adjust the image data presented by the display when the first voltage is unavailable.

The present disclosure relates to automation technology. A first gateway is connected via a first communication network to a field device—and a second gateway is connected to the field device via a second communication network. The first and the second gateway are connected to a control unit. The first communication network and the second communication network are connected to a control room. The control room switches over to the other communication network and establishes a communication connection therewith if a problem is detected in the previous communication connection. Communication access to the first gateway is implemented in the control unit, and communication access to the second gateway is implemented in the control unit via a second driver. The control unit continuously analyses the first communication network and the second communication network and in the event of a control room switchover, switches over to the gateway of that network.

A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.

A functional safety system performs safety analysis on three-dimensional point cloud data measured by a time-of-flight (TOF) sensor that monitors a hazardous industrial area that includes an automation system. To reduce the amount of point cloud data to be analyzed for hazardous conditions, the safety system executes a real-time emulation of the automation system using a digital twin and live controller data read from an industrial controller that monitors and controls the automation system. The safety system generates simulated, or shadow, point cloud data based on the emulation and subtracts this simulate point cloud data from the measured point cloud data received from the TOF sensor. This removes portions of the point cloud data corresponding to known or expected elements within the monitored area. Any remaining entities detected in the reduced point cloud data can be further analyzed for safety concerns.

A self-testing automation system includes a decentralized distributed ledger-type database comprising a plurality of subscriber nodes, wherein the subscriber nodes exchange data with one another per transaction, and the database stores the transactions in data blocks which are linked together; a regulating mechanism which is implemented into each of the subscriber nodes, said regulating mechanism comprising information on the number and identity of all of the subscriber nodes as well as rules relating to actions, properties, and states of each of the subscriber nodes; and a plurality of automation components which are subscriber nodes of the decentralized database. Each of the subscriber nodes is designed to test or validate transactions between the subscriber nodes at all times using the regulating mechanism, and each of the subscriber nodes is designed to carry out at least one measure if a violation of the regulating mechanism is detected.