| In-process tool condition forecasting based on a deep learning method H Sun, J Zhang, R Mo, X Zhang Robotics and Computer-Integrated Manufacturing 64, 101924, 2020 | 113 | 2020 |
| A hybrid approach to cutting tool remaining useful life prediction based on the Wiener process H Sun, D Cao, Z Zhao, X Kang IEEE Transactions on Reliability 67 (3), 1294-1303, 2018 | 100 | 2018 |
| e2-MES: an e-service-driven networked manufacturing platform for extended enterprises PY Jiang, GH Zhou, G Zhao, YF Zhang, HB Sun International Journal of Computer Integrated Manufacturing 20 (2-3), 127-142, 2007 | 43 | 2007 |
| Enhancing cutting tool sustainability based on remaining useful life prediction H Sun, Y Liu, J Pan, J Zhang, W Ji Journal of cleaner production 244, 118794, 2020 | 41 | 2020 |
| Evaluation method of product–service performance H Sun, Z Wang, Y Zhang, Z Chang, R Mo, Y Liu International Journal of Computer Integrated Manufacturing 25 (2), 150-157, 2012 | 41 | 2012 |
| Online machining chatter forecast based on improved local mean decomposition H Sun, X Zhang, J Wang The International Journal of Advanced Manufacturing Technology 84, 1045-1056, 2016 | 38 | 2016 |
| Flexible calibration of phase-to-height conversion in fringe projection profilometry J Lu, R Mo, H Sun, Z Chang Applied Optics 55 (23), 6381-6388, 2016 | 36 | 2016 |
| Non-linear Wiener process–based cutting tool remaining useful life prediction considering measurement variability H Sun, J Pan, J Zhang, D Cao The International Journal of Advanced Manufacturing Technology 107 (11 …, 2020 | 34 | 2020 |
| Invalid phase values removal method for absolute phase recovery J Lu, R Mo, H Sun, Z Chang, X Zhao Applied Optics 55 (2), 387-394, 2016 | 34 | 2016 |
| Modeling of orthogonal cutting process of A2024-T351 with an improved SPH method W Niu, R Mo, GR Liu, H Sun, X Dong, G Wang The International Journal of Advanced Manufacturing Technology 95, 905-919, 2018 | 27 | 2018 |
| Digital twin model for cutting tools in machining process H Sun, J Pan, J Zhang, R Mo Computer Integrated Manufacturing Systems 25 (6), 1474-1480, 2019 | 22 | 2019 |
| In-process tool condition monitoring based on convolution neural network DL Cao, HB Sun, JD Zhang, R Mo Computer Integrated Manufacturing Systems 26 (1), 74-80, 2020 | 20 | 2020 |
| Chatter detection in milling based on singular spectrum analysis Y Mei, R Mo, H Sun, K Bu The International Journal of Advanced Manufacturing Technology 95, 3475-3486, 2018 | 20 | 2018 |
| In-process cutting tool remaining useful life evaluation based on operational reliability assessment H Sun, X Zhang, W Niu The International Journal of Advanced Manufacturing Technology 86, 841-851, 2016 | 19 | 2016 |
| Digital twin-driven aero-engine assembly technology H SUN, J YAN, X WEI, Z CHANG China Mechanical Engineering 31 (07), 833, 2020 | 18 | 2020 |
| Configuring use-oriented aero-engine overhaul service with multi-objective optimization for environmental sustainability H Sun, Y Liu, T Sakao, Z Wang Journal of cleaner production 162, S94-S106, 2017 | 18 | 2017 |
| An approach to in-process surface texture condition monitoring H Sun, D Gao, Z Zhao, X Tang Robotics and Computer-Integrated Manufacturing 48, 254-262, 2017 | 17 | 2017 |
| An adaptive repair surface modeling approach for worn blades F Hou, N Wan, Z Chang, Z Chen, H Sun The International Journal of Advanced Manufacturing Technology 94, 523-532, 2018 | 16 | 2018 |
| A study of computing accuracy of calibrating cutting force coefficients and run-out parameters in flat-end milling D Zhang, R Mo, Z Chang, H Sun, C Li The International Journal of Advanced Manufacturing Technology 84, 621-630, 2016 | 16 | 2016 |
| Simplified absolute phase retrieval of dual-frequency fringe patterns in fringe projection profilometry J Lu, R Mo, H Sun, Z Chang, X Zhao Optics Communications 364, 101-109, 2016 | 16 | 2016 |
Xianzhi ZhangUniversity of HuddersfieldVerified email at hud.ac.uk
