Аннотация
Digital twins and machine learning, two contemporary information technology, have opened up new possibilities for the digital display, visualization, and monitoring of industrial processes. This research suggests utilizing machine learning, visualization, and monitoring approaches to analyze the use of digital twins in industrial process control. This novel method integrates real-time performance data and machine learning for monitoring, visualization, and prediction. In particular, trends and preferences are found and future situations are predicted by machine learning approaches. A variety of situations are created and assessed with the use of digital twins, and information is gathered to train machine learning algorithms on actual data.