As one of our LISMS group members, Zexuan Zhu successfully finished his PhD study. His supervisors were Professor Xun Xu and Assistant Professor Ray Zhong.
His research topic was “Development of a Cyber-Physical Machine Tool: Paving the Way for Industry 4.0“.
Dr. Zexuan’s research primarily focuses on developing and validating a Digital Twin–enabled Cyber-Physical Machine Tool (CPMT) framework that integrates augmented-reality (AR) human–machine interfaces and machine learning (ML) to meet rising manufacturing complexity, customization, and demands for efficiency and quality. Its primary objective is to create a Digital Twin–driven component manufacturing workflow that supports intuitive operator interaction, real-time monitoring and control, augmented machining simulation, and in-process optimization. Additionally, Dr. Zexuan aims to embed ML for predictive analytics, anomaly detection, adaptive interfaces, and real-time optimization; implement an AR application using Microsoft HoloLens for visualizing Digital Twin data during machining; and demonstrate feasibility and benefits through a 5-axis CNC blisk case study on thin-walled parts. The anticipated outcome is improved efficiency, reduced errors, and real-time optimization capability, offering practical solutions aligned with Industry 4.0.
Dr. Zexuan publications during his doctoral studies are as follows.
Journal
- Zhu, Zexuan, et al. “Digital Twin-driven machining process for thin-walled part manufacturing.” Journal of Manufacturing Systems 59 (2021): 453-466.
- Zhu, Z., & Xu, X. (2020). User-centered information provision of cyber-physical machine tools. Procedia CIRP, 93, 1546-1551.
Conference
- Hu, Y., Donald, C., Giacaman, N., & Zhu, Z. (2020, March). Towards automated analysis of cognitive presence in MOOC discussions: a manual classification study. In Proceedings of the tenth international conference on learning analytics & knowledge (pp. 135-140).
- Zhu, Z., Liu, C., & Xu, X. (2019). Visualisation of the digital twin data in manufacturing by using augmented reality. Procedia Cirp, 81, 898-903.
- Liu, C., Hong, X., Zhu, Z., & Xu, X. (2018). Machine tool digital twin: Modelling methodology and applications.
BOOK
- Zhu, Z., Xi, X., Xu, X., & Cai, Y. (2021). Digital Twin-driven machining process for thin-walled part manufacturing. Journal of Manufacturing Systems, 59, 453-466.
- Aheleroff, S., Polzer, J., Huang, H., Zhu, Z., Tomzik, D., Lu, Y., … & Xu, X. (2020). Smart manufacturing based on digital twin technologies. In Industry 4.0 (pp. 77-122). CRC Press.
Congratulations on Dr. Zexuan Zhu! And we wish you all the best in your future endeavours.