Method for creating a recipe for a process-related process plant based on at least one service, wherein the at least one service is a representation, in terms of automation technology, of concrete physical embodiments of process-related operations of the process-related process plant, where in order to create the recipe, a substitute object assigned to the service is used for each individual service, the substitute object has a parameterization, via which, when merging the created recipe and a topology of the process-related process plant, the concrete physical embodiments of the process-related operations of the process-related process plant can be incorporated into the recipe, and where the substitute object(s) is/are realized in a programmable logic controller of a control system of the process-related process plant or in a batch system of the control system of the process-related process plant.

A method for automatic identification of important batch events for a batch execution alignment algorithm, including receiving historical batch data of a batch process, wherein the historical batch data comprises a plurality of batch executions, and wherein each of the plurality of batch executions comprises a plurality of batch events, indicating a specific event of the batch process, and at least one time series of a process variable, indicating a development of the process variable during the batch process; determining a distance between the at least one time series of the plurality of the batch executions for each of the plurality of batch events; and identifying at least one important batch event for a batch execution alignment algorithm with a smallest distance using the determined distances.

A non-transitory tangible, computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations including receiving data associated with one or more industrial devices of an industrial system, and retrieving one or more pre-processing files and one or more training datasets files associated with a model from a database, wherein the one or more pre-processing files are configured to transform the data, and wherein the one or more training dataset files are representative of one or more operational characteristics of the one or more industrial devices over time. The instructions cause the processing circuitry to perform operations including receiving one or more inputs to modify one or more parameters of the model via a user interface presented via an electronic display, and generating the model based on the training dataset files and the one or more inputs.

A non-transitory tangible, computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations including receiving a set of data associated with industrial devices of an industrial system, and retrieving pre-processing files and training datasets files associated with the industrial devices from a database, wherein the pre-processing files are configured to transform the data for generating a model representative of the industrial devices, and wherein the training dataset files are representative of operational characteristics of the industrial devices over time. The instructions cause the processing circuitry to perform operations including generating a set of prediction data representative of expected operations of the industrial devices based on the set of data and the model, determining commands for adjusting operational settings of the industrial devices based on the set of prediction data, and sending the commands to the industrial devices.

A non-transitory tangible, computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations including receiving data associated with industrial equipment, pre-processing the data using pre-processing files associated with a modeling technique to generate pre-processed data, generating training dataset files based on the pre-processed data, and generating a model representative of expected operations of the industrial equipment based on the training dataset files. The instructions cause the processing circuitry to perform operations including storing an association between the training dataset files with the modeling technique, the industrial equipment, or both in a database, receiving a request to generate an additional model representative of additional expected operations of additional industrial equipment, receiving additional data associated with the additional industrial equipment, retrieving the training dataset files based on the additional data, and generating the additional model based on the training dataset files and the additional data.