Digital Twin Software for a Continuous Caster

Under continuation from work performed under the AIST Digital Transformation Grant for an enhanced digital twin solution for continuous casting, additional features are being developed to both supplement and expand past the drive roll calibration data presented at AISTech 2022. Some of the topics that are being road mapped and trialed are things like event tracking along the casting length, bridging detection, inclusion of plant database access, and beginning use of continuous data points, rather than the mostly discrete data sets that have been previously used. Some of these topics will be elaborated based on overall progress prior to AISTech 2023.

Kyle Toth | Purdue University Northwest
 

Aleeha Zafar | Purdue University Northwest
 

Xibin Zhou | Purdue University Northwest
 

Rayhan Zaman | Purdue University Northwest
 

Nicholas Gregurich | Cleveland-Cliffs Burns Harbor
 

Lidia Yakovleva | Cleveland-Cliffs Burns Harbor
 

Chenn Zhou | Purdue University Northwest