Chong Chen

Articles

• Chen, C., Fu, H., Zheng, Y., Tao, F. and Liu, Y. 2023. The advance of digital twin for predictive maintenance: The role and function of machine learning. Journal of Manufacturing Systems 71, pp. 581-594. (10.1016/j.jmsy.2023.10.010)
• Chen, C., Wu, D. and Liu, Y. 2022. Recent advances of AI for engineering service and maintenance. Autonomous Intelligent Systems 2(1), article number: 19. (10.1007/s43684-022-00038-y)
• Chen, C., Liu, Y., Sun, X., Cairano-Gilfedder, C. D. and Titmus, S. 2021. An integrated deep learning-based approach for automobile maintenance prediction with GIS data. Reliability Engineering and System Safety 216, article number: 107919. (10.1016/j.ress.2021.107919)
• Chen, C., Liu, Y., Wang, S., Di Cairano-Gilfedder, C., Sun, X., Titmus, S. and Syntetos, A. A. 2020. Predictive maintenance using cox proportional hazard deep learning. Advanced Engineering Informatics 44, article number: 101054. (10.1016/j.aei.2020.101054)
• Chen, C., Liu, Y., Kumar, M., Qin, J. and Ren, Y. 2019. Energy consumption modelling using deep learning embedded semi-supervised learning. Computers and Industrial Engineering 135, pp. 757-765. (10.1016/j.cie.2019.06.052)
• Chen, C., Liu, Y., Sun, X., Cairano-Gilfedder, C. and Titmus, S. 2019. Automobile maintenance prediction using deep learning with GIS data. Procedia CIRP 81, pp. -. (10.1016/j.procir.2019.03.077)
• Chen, C., Liu, Y., Kumar, M. and Qin, J. 2018. Energy consumption modelling using deep learning technique — a case study of EAF. Procedia CIRP 72, pp. 1063-1068. (10.1016/j.procir.2018.03.095)

Conferences

• You, Y., Chen, C., Hu, F., Liu, Y. and Ji, Z. 2022. Advances of digital twins for predictive maintenance. Presented at: 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2021), Linz, Austria, 17-19 November 2021, Vol. 200. Procedia Computer Science, Vol 200: pp. 1471-1480., (10.1016/j.procs.2022.01.348)
• Chen, C., Liu, Y., Sun, X., Di Cairano-Gilfedder, C. and Titmus, S. 2020. Automobile maintenance modelling using gcForest. Presented at: 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE), Virtual, 20-24 August 20202020 IEEE 16th International Conference on Automation Science and Engineering (CASE). IEEE pp. 600-605., (10.1109/CASE48305.2020.9216745)
• Chen, C., Liu, Y., Sun, X., Wang, S., Di Cairano-Gilfedder, C., Titmus, S. and Syntetos, A. 2018. Reliability analysis using deep learning. Presented at: ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Quebec City, Canada, 26-29 August 2018ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference Volume 1B: 38th Computers and Information in Engineering Conference Quebec City, Quebec, Canada, August 26–29, 2018. ASME pp. V01BT02A040., (10.1115/DETC2018-86172)

Thesis

• Chen, C. 2020. Deep learning for automobile predictive maintenance under Industry 4.0. PhD Thesis, Cardiff University.