| Distributed model predictive control for on-connected microgrid power management Y Zheng, S Li, R Tan IEEE Transactions on Control Systems Technology 26 (3), 1028-1039, 2017 | 161 | 2017 |
| A heterogeneous benchmark dataset for data analytics: Multiphase flow facility case study A Stief, R Tan, Y Cao, JR Ottewill, NF Thornhill, J Baranowski Journal of Process Control 79, 41-55, 2019 | 77 | 2019 |
| Approaches to robust process identification: A review and tutorial of probabilistic methods H Kodamana, B Huang, R Ranjan, Y Zhao, R Tan, N Sammaknejad Journal of Process Control 66, 68-83, 2018 | 67 | 2018 |
| Developing industrial cps: A multi-disciplinary challenge MW Hoffmann, S Malakuti, S Grüner, S Finster, J Gebhardt, R Tan, ... Sensors 21 (6), 1991, 2021 | 59 | 2021 |
| Nonstationary discrete convolution kernel for multimodal process monitoring R Tan, JR Ottewill, NF Thornhill IEEE Transactions on Neural Networks and Learning Systems 31 (9), 3670-3681, 2019 | 34 | 2019 |
| An on-line framework for monitoring nonlinear processes with multiple operating modes R Tan, T Cong, JR Ottewill, J Baranowski, NF Thornhill Journal of Process Control 89, 119-130, 2020 | 29 | 2020 |
| Monitoring statistics and tuning of kernel principal component analysis with radial basis function kernels R Tan, JR Ottewill, NF Thornhill IEEE Access 8, 198328-198342, 2020 | 24 | 2020 |
| Anomaly detection and mode identification in multimode processes using the field Kalman filter T Cong, R Tan, JR Ottewill, NF Thornhill, J Baranowski IEEE Transactions on Control Systems Technology 29 (5), 2192-2205, 2020 | 23 | 2020 |
| Deviation contribution plots of multivariate statistics R Tan, Y Cao IEEE Transactions on Industrial Informatics 15 (2), 833-841, 2018 | 20 | 2018 |
| Data analytics approach for online produced fluid flow rate estimation in SAGD process S Sedghi, R Tan, B Huang Computers & Chemical Engineering 136, 106766, 2020 | 13 | 2020 |
| Multi-layer contribution propagation analysis for fault diagnosis RM Tan, Y Cao International Journal of Automation and Computing 16 (1), 40-51, 2019 | 12 | 2019 |
| Statistical monitoring of processes with multiple operating modes R Tan, T Cong, NF Thornhill, JR Ottewill, J Baranowski IFAC-PapersOnLine 52 (1), 635-642, 2019 | 11 | 2019 |
| Process and alarm data integration under a two-stage Bayesian framework for fault diagnostics A Stief, JR Ottewill, R Tan, Y Cao IFAC-PapersOnLine 51 (24), 1220-1226, 2018 | 11 | 2018 |
| Active learning application for recognizing steps in chemical batch production A Ahmad, C Song, R Tan, M Gärtler, B Klöpper 2022 IEEE 27th International Conference on Emerging Technologies and Factory …, 2022 | 8 | 2022 |
| PRONTO heterogeneous benchmark dataset A Stief, R Tan, Y Cao, JR Ottewill Zenodo, 2019 | 8 | 2019 |
| Analytics of heterogeneous process data: Multiphase flow facility case study A Stief, R Tan, Y Cao, JR Ottewill IFAC-PapersOnLine 51 (18), 363-368, 2018 | 8 | 2018 |
| A benchmark model to generate batch process data for machine learning testing and comparison MLC Vicente, JFO Granjo, R Tan, FD Bähner Computer Aided Chemical Engineering 51, 217-222, 2022 | 7 | 2022 |
| Robust soft sensor development using multi-rate measurements O Wu, H Kodamana, NM Jan, R Tan, B Huang IFAC-PapersOnLine 50 (1), 10190-10195, 2017 | 7 | 2017 |
| Towards a benchmark dataset for large language models in the context of process automation T Tizaoui, R Tan Digital Chemical Engineering 13, 100186, 2024 | 5 | 2024 |
| Nonlinear dynamic process monitoring: The case study of a multiphase flow facility R Tan, RT Samuel, Y Cao Computer Aided Chemical Engineering 40, 1495-1500, 2017 | 5 | 2017 |
