Analysis and application of manufacturing data driven by digital twins

Abstract This article introduces the importance of data processing to the production process and the application of data in the digital twin workshop. Then the overall process of data processing is introduced. First, several typical data acquisition methods are listed, feed the collected data to the digital twin model, and then extract the model data for integration and convert it into the same XML text format. Perform data cleaning and data analysis on it, and then use the DBN in deep learning to extract and classify the data to complete the real-time matching and transmission of production information to employees. Finally, the future development direction of the data analysis will be briefly summarized.