Dr Yongjing Wang BEng(1st), PhD, CEng, MIET, FHEA

Dr Yongjing Wang

Department of Mechanical Engineering
Assistant Professor

Contact details

Email
y.wang@bham.ac.uk
Twitter
@YonjingWang
View my research portal
Address
University of Birmingham
Edgbaston
Birmingham
B15 2TT

Yongjing is an academic engineer and a lecturer at the School of Engineering, the University of Birmingham, UK.

Yongjing’s work focuses on the development of the next generation robotics and automation technologies and their applications to complex industrial processes. In particular, he has been promoting the use of robots in remanufacturing and recycling.

His work has contributed to EPSRC, EC, Royal society, Innovate UK and industry funded projects and he is building a new team at Birmingham.

Yongjing is a Chartered Engineer and a Fellow of the Higher Education Academy.

Link to Personal Site

Qualifications

  • Fellow of the Higher Education Academy, 2019
  • Chartered Engineer, 2019
  • PhD, Mechanical Engineering, University of Birmingham, 2016
  • BEng (1st Hons), Electronic and Electrical Engineering, University of Birmingham, 2013
  • BEng, Automation Science and Technology, Harbin Institute of Technology (China), 2013
  • Member of Institute of Technology, 2013

Publications

Recent publications

Article

Liu, Q, Deng, W, Pham, DT, Hu, J, Wang, Y & Zhou, Z 2023, 'A Two-Stage Screw Detection Framework for Automatic Disassembly Using a Reflection Feature Regression Model', Micromachines, vol. 14, no. 5, 946. https://doi.org/10.3390/mi14050946

Su, S, Pham, DT, Ji, C, Wang, Y, Huang, J, Zhou, W & Wang, H 2023, 'Design of a compliant device for peg-hole separation in robotic disassembly', The International Journal of Advanced Manufacturing Technology, vol. 124, no. 9, pp. 3011-3019. https://doi.org/10.1007/s00170-022-10573-w

Yun, G, Cole, T, Zhang, Y, Zheng, J, Sun, S, Ou-yang, Y, Shu, J, Lu, H, Zhang, Q, Wang, Y, Pham, D, Hasan, T, Li, W, Zhang, S & Tang, S-Y 2023, 'Electro-mechano responsive elastomers with self-tunable conductivity and stiffness', Science Advances, vol. 9, no. 4, eadf1141. https://doi.org/10.1126/sciadv.adf1141

Qu, M, Wang, YW & Pham, D 2023, 'Robotic Disassembly Task Training and Skill Transfer Using Reinforcement Learning', IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/TII.2023.3242831

Liu, Q, Lu, H, Zhang, X, Zhang, Y, Wang, Y, Li, Z & Duan, M 2022, 'A method to improve position accuracy for the dual-drive feed machines by state-dependent friction compensation', Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 236, no. 9, pp. 1247-1267. https://doi.org/10.1177/09544054221076233

Ye, F, Perrett, J, Zhang, L, Laili, Y & Wang, Y 2022, 'A self-evolving system for robotic disassembly sequence planning under uncertain interference conditions', Robotics and Computer-Integrated Manufacturing, vol. 78, 102392. https://doi.org/10.1016/j.rcim.2022.102392

Huang, J, Pham, DT, Li, R, Qu, M, Wang, Y, Kerin, M, Su, S, Ji, C, Mahomed, O, Khalil, R, Stockton, D, Xu, W, Liu, Q & Zhou, Z 2021, 'An experimental human-robot collaborative disassembly cell', Computers and Industrial Engineering, vol. 155, 107189. https://doi.org/10.1016/j.cie.2021.107189

Laili, Y, Ye, F, Wang, Y & Zhang, L 2021, 'Interference probability matrix for disassembly sequence planning under uncertain interference', Journal of Manufacturing Systems, vol. 60, pp. 214-225. https://doi.org/10.1016/j.jmsy.2021.05.014

Chapter (peer-reviewed)

Lan, F, Castellani, M, Wang, Y & Zheng, S 2022, Global Optimisation for Point Cloud Registration with the Bees Algorithm. in DT Pham & N Hartono (eds), Intelligent Manufacturing and Production Optimisation – The Bees Algorithm Approach. Springer Series in Advanced Manufacturing, Springer Nature, pp. 129-144. https://doi.org/10.1007/978-3-031-14537-7_8

Chapter

Laili, Y, Wang, Y, Fang, Y & Pham, DT 2021, Component and subassembly detection. in Optimisation of Robotic Disassembly for Remanufacturing. 1 edn, Springer Series in Advanced Manufacturing, Springer, Cham, pp. 47-58. https://doi.org/10.1007/978-3-030-81799-2_4

Laili, Y, Wang, Y, Fang, Y & Pham, DT 2021, Evolutionary optimisation for robotic disassembly sequence planning and line balancing. in Optimisation of Robotic Disassembly for Remanufacturing. 1 edn, Springer Series in Advanced Manufacturing, Springer, Cham, pp. 85-110. https://doi.org/10.1007/978-3-030-81799-2_7

Laili, Y, Wang, Y, Fang, Y & Pham, DT 2021, Introduction to remanufacturing. in Optimisation of Robotic Disassembly for Remanufacturing. 1 edn, Springer Series in Advanced Manufacturing, Springer, Cham, pp. 1-6. https://doi.org/10.1007/978-3-030-81799-2_1

Laili, Y, Wang, Y, Fang, Y & Pham, DT 2021, Modelling of robotic disassembly line balancing. in Optimisation of Robotic Disassembly for Remanufacturing. 1 edn, Springer Series in Advanced Manufacturing, Springer, Cham, pp. 71-83. https://doi.org/10.1007/978-3-030-81799-2_6

Laili, Y, Wang, Y, Fang, Y & Pham, DT 2021, Modelling of robotic disassembly sequence planning. in Optimisation of Robotic Disassembly for Remanufacturing. 1 edn, Springer Series in Advanced Manufacturing, Springer, Cham, pp. 59-69. https://doi.org/10.1007/978-3-030-81799-2_5

Conference contribution

Goli, F, Wang, Y & Saadat, M 2022, Perspective of self-learning robotics for disassembly automation. in 2022 27th International Conference on Automation and Computing (ICAC)., 9911085, International Conference on Automation and Computing (ICAC), IEEE, pp. 1-6, 27th International Conference on Automation and Computing, ICAC 2022, Bristol, United Kingdom, 1/09/22. https://doi.org/10.1109/ICAC55051.2022.9911085

View all publications in research portal