Framework for remaining useful life prediction of casting roller in continuous casting machine based on digital twin

Casting roller is equipped with high maintenance frequency and interchangeability in continuous casting machine, viewed as key part during its operation and maintenance. To improve the level of casting roller operation & maintenance management and prolong its service life, a novel framework for remaining useful life prediction of casting roller in continuous casting machine based on digital twin is proposed. First, systematic overview of the proposed framework is described in detail. Second, monitoring and traceability for casting roller are designed based on 3D twin model. Then, multiple failure modes of casting roller are analyzed and its performance degradation is evaluated. After that, the process of remaining useful life prediction based on deep learning together with twin data is given. Finally, a prototype system is developed and implemented, and the results verify the effectiveness and feasibility of proposed framework.