A system displays a representation of an original equipment remote control device for a target device to be controlled using a macro button of a configurable controlling device. The displayed representation of the original equipment remote control device includes representations of buttons that would be used on the original equipment remote control device to control controllable functions of the target device. The system accepts input by which one or more of the displayed representations of buttons are selected. The macro button is then configured whereby an activation of the macro button will cause a transmission of commands from the configurable controlling device to control those controllable functions of the target devices that correspond to the one or more of the displayed representations of buttons that were selected.

A system displays a representation of an original equipment remote control device for a target device to be controlled using a macro button of a configurable controlling device. The displayed representation of the original equipment remote control device includes representations of buttons that would be used on the original equipment remote control device to control controllable functions of the target device. The system accepts input by which one or more of the displayed representations of buttons are selected. The macro button is then configured whereby an activation of the macro button will cause a transmission of commands from the configurable controlling device to control those controllable functions of the target devices that correspond to the one or more of the displayed representations of buttons that were selected.

Various embodiments of the present technology generally relate to solutions for improving industrial automation programming and data science capabilities with machine learning. More specifically, embodiments of the present technology include systems and methods for implementing machine learning engines within industrial programming and data science environments to improve performance, increase productivity, and add functionality. In an embodiment, a system comprises a machine learning-based recommendation engine configured to, an industrial programming environment, generate a recommendation to add a component to control logic based on an existing portion of the control logic. A notification component is configured to surface the recommendation in the programming environment. A programming component is configured to, in the programming environment, add the component to the control logic. A configuration component is configured to configure the component based at least in part on the existing portion of the control logic.

The obtainment unit obtains information indicative of a content of manual-operation performed by a user regarding control of an intended apparatus from a group of loads, and stores it as manual-operation information including an obtaining time. The identification unit identifies a type of control of the manual-operation information. The determination unit counts the number of times of obtaining the manual-operation information within a counting period equal to two days or more, for each type and for each time period, and determines whether the number of times of obtaining the same type of manual-operation information within the same time period is equal to a predetermined threshold or more. When the number of times of obtaining the same type of manual-operation information within the same time period is determined to be equal to the predetermined threshold or more, the schedule change unit changes a control schedule based on this manual-operation information.

A field device and method for starting up an industrial automation network, wherein to allow virtual start-up of at least one field device, an field device integration package is provided, whose user interface plug-in has an extension that allows a software tool to access a simulation model for the behavior of the at least one field device, and upon virtual start-up, the simulation model is used to reproduce the response of the field device, where a process model or interfacing of an external process model via a co-simulation coupling can also be used to stimulate the reproduced field device behavior, and where because the models with the FDI package are provided by the field device manufacturer, correct simulation and hence minimization of the risks upon start-up of industrial installations can be expected.

Various embodiments of the present technology generally relate to solutions for improving industrial automation programming and data science capabilities with machine learning. More specifically, embodiments of the present technology include systems and methods for implementing machine learning engines within industrial programming and data science environments to improve performance, increase productivity, and add functionality. In an embodiment, a system comprises a user interface component configured to display a programming environment for editing control logic, wherein operational data from the industrial automation environment is accessible from within the programming environment through a data pipeline. A machine learning-based data science engine is configured to process the operational data from the industrial automation environment to generate processed data and identify a portion of the processed data relevant to a component of the control logic. The user interface component is further configured to surface the portion of the processed data in the programming environment.

A system displays a representation of an original equipment remote control device for a target device to be controlled using a macro button of a configurable controlling device. The displayed representation of the original equipment remote control device includes representations of buttons that would be used on the original equipment remote control device to control controllable functions of the target device. The system accepts input by which one or more of the displayed representations of buttons are selected. The macro button is then configured whereby an activation of the macro button will cause a transmission of commands from the configurable controlling device to control those controllable functions of the target devices that correspond to the one or more of the displayed representations of buttons that were selected.

Various embodiments of the present technology generally relate to solutions for improving industrial automation programming and data science capabilities with machine learning. More specifically, embodiments of the present technology include systems and methods for implementing machine learning engines within industrial programming and data science environments to improve performance, increase productivity, and add functionality. In an embodiment, a system comprises a user interface component configured to display a programming environment for editing control logic, wherein operational data from the industrial automation environment is accessible from within the programming environment through a data pipeline. A machine learning-based data science engine is configured to process the operational data from the industrial automation environment to generate processed data and identify a portion of the processed data relevant to a component of the control logic. The user interface component is further configured to surface the portion of the processed data in the programming environment.