Abstract: A control system for controlling an apparatus or installation, wherein at least one first safety function controls the apparatus or installation, where the control system includes a first safety-oriented control device that is configured to perform the at least one first safety function, where the first safety-oriented control device is also configured as a first safety-oriented control application that is implemented in a cloud, and where the first safety oriented control application and the apparatus or installation are communicatively coupled via a first safety-oriented communication connection.

Abstract: A method and safety-oriented control device for determining and/or selecting a safe condition using a safety-oriented control device configured for safety-oriented control of an apparatus or installation via execution of a safety-oriented control program which, when executed, results in a safe reaction being triggered in the safety-oriented controller, wherein the method is implemented such that an ML model is configured and formed as a result, which is stored in a memory device, of the application of a machine learning method, such that data relevant to the determination of a safe condition are stored in connection with the triggering of the safe reaction, and such that a first safe condition is determined via the data relevant to the determination of the safe condition being applied to the ML model.

Abstract: A system for programming automation by demonstration where a control program may be created or modified through the process of demonstrating desired behavior using graphical representations (or widgets) of physical, programming, and user interface elements. Widgets have state, or properties, and may also have inherent events associated with them or indirect events that are generated through the demonstration process. The general process of demonstration consists of providing several individual example behaviors. Complete behavior, and thus the resultant code, is generated through inferencing from a number of individual example behaviors. The process of programming automation by demonstration reduces the complexity of the programming task and thereby greatly simplifies the workload of the control programmer, allowing the programmer to concentrate more on the specific automation application at hand rather than on the particulars of the programming language or tools.

Abstract: A system for programming automation by demonstration where a control program may be created or modified through the process of demonstrating desired behavior using graphical representations (or widgets) of physical, programming, and user interface elements. Widgets have state, or properties, and may also have inherent events associated with them or indirect events that are generated through the demonstration process. The general process of demonstration consists of providing several individual example behaviors. Complete behavior, and thus the resultant code, is generated through inferencing from a number of individual example behaviors. The process of programming automation by demonstration reduces the complexity of the programming task and thereby greatly simplifies the workload of the control programmer, allowing the programmer to concentrate more on the specific automation application at hand rather than on the particulars of the programming language or tools.

Abstract: An automation system wherein fault conditions are identified by providing clearer fault messages. The system is defined in terms of components, and further in terms of inputs, outputs, and functional relationships between the inputs and outputs, wherein inputs include potential fault conditions associated with the components or functional elements. Weighting factors are associated with the fault conditions to identify the most likely cause. Functional relationships are developed using libraries of generic components that are used to create a diagnostic program during an off-line phase (410). Model functions (412) are determined and coded according to a suitable coding language (414). The resulting program is passed as a diagnostic model (426) operable of use in an on-line phase (420). The diagnostic model (426) provides input to an object engine (430) that is operational during the on-line phase (420), and receives specific inputs (424) and outputs of selected information (422) during operation thereof.