‘Digital twinning for manufacturing process of advanced ceramics by combining machine learning and finite element solutions’ – Jingzhe Pan, University of Leicester

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Jingzhe Pan from the University of Leicester discusses the development of a digital twin strategy to improve the manufacturing process of advanced ceramics. He explores the challenges of the present manufacturing process, the need for accurate data, and the integration of machine learning with finite element models to refine the mathematical model used in manufacturing.

Jingzhe also highlights the innovative two-step training approach that utilizes mathematical theory and manufacturing data. The work, part of a larger project funded by UKRI, aims to enhance the control of the manufacturing process, ultimately improving product quality.

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