Modeling of a Digital Twin of an Automated Production Process

The article discusses the methodology for modeling a digital twin of an automated production process. The basis of the methodology is the method of intellectual analysis and information processing, which involves identifying patterns in the features, characteristics and parameters of the production process, forming classifiers for them according to various criteria in order to determine and predict the behavior of the process. The proposed digital twin modeling technique allows us to take into account hidden connections between the characteristics of the production process and their combinations, which increases the accuracy of forecasting changes in process behavior and, as a result, increases the efficiency of its management. As an example, the use of the proposed approaches for modeling a digital twin of automated assembly operations is considered.