Siemens Aktiengesellschaft

Johannes Frank

Ingo Thon

Josep Soler Garrido

Heiko Claussen

Andreas Macher

Norman Drews

Renè Fischer

A method of communicating with a microservice in an industrial facility. The method is implemented by a controller and includes obtaining one or more data structure types, wherein the data structure types are generated based on an API definition associated with the microservice, generating one or more variables based on the obtained data structure types, wherein the variables are associated with one or more function blocks of the controller, and transmitting data associated with the variables to the microservice via a proxy component. The controller transmits the data associated with the variables in a serialized binary format associated with the variables to the proxy component. The proxy component is configured to translate to translate the data from the serialized binary data to a first serialization format and transmit the data in the first serialization format to the microservice.

Method of communicating with a microservice in an industrial facility

An extension device for one or more automation devices in an industrial system is provided. Industrial data processing units capable of performing data processing based on one or more artificial neural networks are provided. To enable and/or accelerate one or more computations in an industrial system, thereby simplifying integration of artificial intelligence into the industrial system, and to simplify data exchange between an extension device capable of processing data using artificial intelligence and an automation device, one or more results of the one or more computations are obtained. The results indicate one or more states of the industrial system. The one or more results are provided via a process state model shared with the automation device to monitor and/or control the industrial system.

Extension device for an automation device

A method includes determining an artificial intelligence function in an engineering framework system. An inference path is defined for generation of an AI model by a computation graph. An AI function and the inference path are converted into a processing format. The converted AI function is sent and exported to an extraction and extension module of an AI workbench module. The extended computation graph of the inference path is transmitted from the extraction and extension module to an AI framework module. The method includes communicating of a communication adapter with the processing module continuously by using a supporting communication protocol for receiving training data as input for the AI function and forwarding the training data to the AI framework module. Learned parameters of the AI model are transferred from an API interface of the AI framework module to the communication adapter for updating the AI model.

Growing community of inventors

Munich, Germany

Johannes Frank