Hussein Asharf Adil Said, Student, Basic Department of Big Data Analytics and Video Analysis Methods, Ural Federal University named after the first President of Russia B.N. Yeltsin
Balungu Daniel Musafiri, Postgraduate student, Assistant Basic Department of Big Data Analytics and Video Analysis Methods, Ural Federal University named after the first President of Russia B.N. Yeltsin
Abstract
This article describes the process of building a digital twin of material flows for long-range production using a domestic DATA-TRACK solution and the object relations method (ORT). First, a digital model of the site is created: accounting objects are determined, product movement trajectories are modeled, and virtual sensors are installed (such as the speed of transportation, the position of the workpiece). Then, through the Swagger interface, entities and their attributes are formed, such as the temperature in the furnace, set by float data types, and linked to the product processing process. The monitoring process is automated using the Nuclio serverless architecture: a special Python function monitors changes in the status of the accounting object. When the workpiece enters the furnace, a trigger is triggered (HTTP hook in conjunction with the FBP pipeline of the DATA-TRACK platform), which initiates the execution of the function. It requests the current values of the temperature parameter through the API and updates the corresponding indicator of the accounting object through internal DATA-TRACK REST requests. In addition, the same function generates metrics in the Prometheus format (workpiece_id, temperature), which are immediately displayed in the Grafana toolbar. Due to this, the operator continuously sees the dynamics of temperature changes in the furnace and promptly takes measures when the values exceed the permissible limits.
KEYWORDS: digital twin, material flow, long rolling production, DATA-TRACK, ORT, production automation.
Download article DEVELOPMENT OF A DIGITAL TWIN FOR MATERIAL FLOW BASED ON THE EXAMPLE OF A LONG ROLLING PRODUCTION USING THE DATA-TRACK PLATFORM
