An edge computing device is provided that includes a plurality of input electrodes that are communicatively coupled to one or more communication channels of a programmable logic controller that implements control logic to control a controlled device. The edge computing device furthers include a processor configured to, at a training time, receive signals via the plurality of input electrodes, detect inputs to the one or more communication channels and outputs from the one or more communication channels of the programmable logic controller, generate a set of training data based on the detected inputs and outputs of the programmable logic controller, and train an artificial intelligence model using the generated set of training data. The processor is further configured to, at a run-time, emulate the control logic of the programmable logic controller using the trained artificial intelligence model.

A method of operating an intelligent programmable logic controller (PLC) as part of a production process within an automation system includes the intelligent PLC receiving automation system data and a semantic context model comprising a plurality of ontologies providing formal specifications of conceptual entities associated with the automation system. The intelligent PLC creates one or more semantic annotations for the automation system data using the semantic context model. These semantic annotations are stored along with the automation system data in a non-volatile storage medium included in the intelligent PLC.

An edge computing device is provided that includes a plurality of input electrodes that are communicatively coupled to one or more communication channels of a programmable logic controller that implements control logic to control a controlled device. The edge computing device furthers include a processor configured to, at a training time, receive signals via the plurality of input electrodes, detect inputs to the one or more communication channels and outputs from the one or more communication channels of the programmable logic controller, generate a set of training data based on the detected inputs and outputs of the programmable logic controller, and train an artificial intelligence model using the generated set of training data. The processor is further configured to, at a run-time, emulate the control logic of the programmable logic controller using the trained artificial intelligence model.

The invention relates to methods and systems for automating equipment. The claimed method comprises steps in which: an expert system (ES) receives a set of information regarding equipment connected to a PLC; the ES checks the received set of information; a set of functions is determined by the ES for each connected type of equipment; the ES generates a set of commands executable by the PLC and corresponding to the functions of the connected equipment using pre-programmed algorithms for generating program commands; the ES generates interactive prompts for connecting devices to the PLC; information containing at least the above-mentioned set of commands is transmitted to the PLC; at least one device is connected to the PLC and execution of at least one command corresponding to at least one function of the above-mentioned device is activated.

In the case of the method and the device described here for automated parameterisation of at least one IO-Link device (300-310) connected, via an IO-Link connection (315-325) using communication technology, to a device (330) having IO-Link Master functionalities for a predetermined intended use (410) of at least one IO-Link device (300-310) by means of a configuration assistant (400), it is in particular provided that on the basis of the intended use (410) by means of an expert system (430) which is based on an artificial neural network and/or is rule-based, by means of which information (435) relevant for the parameterisation is automatically determined by means of user (445) inputs (440) guided by a configuration assistant (400) serving as a front end for the expert system (430), and a parameter set (455) suitable for the preferably application-related intended use (410) is automatically created for the parameterisation from the determined information (435) relevant for the parameterisation.

A method of operating an intelligent programmable logic controller (PLC) as part of a production process within an automation system includes the intelligent PLC receiving automation system data and a semantic context model comprising a plurality of ontologies providing formal specifications of conceptual entities associated with the automation system. The intelligent PLC creates one or more semantic annotations for the automation system data using the semantic context model. These semantic annotations are stored along with the automation system data in a non-volatile storage medium included in the intelligent PLC.