Razor Host

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A. Process Analytical Techniques B. Process Monitoring (on-line, in-line, non-invasive) C. Multivariate Data Analysis D. Process Modelling E. Process Control

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D1 Kinetic modelling D2 Multi-block, predictive and multi-scale modelling methods D3 Performance monitoring

title year authors journal volume pages Categories Actions
A comparative investigation of the combined effects of pre processing, wavelength selection and regression methods on near-infrared calibration model performance 2017 Wan Jian, Chen Yi-Chieh, Morris A Julian, Thennadil N Suresh Appl. Spectrosc. On-Line 30/03/17 C1 Multivariate data analysis, D3 Performance monitoring DOI
A comparative investigation of the combined effects of pre-processing, wavelength selection and regression methods on near infrared calibration model performance, 2017 Wan J., Chen, Y.-C., Morris, J. A. and Thennadil, S. N Applied Spectroscopy Jul:71 (7) 1432-1446 C1 Multivariate data analysis, D3 Performance monitoring DOI
A heuristic approach to handling missing data in biologics manufacturing databases 2019 Mante, J., Gangadharan, N., Sewell, D. J., Turner, R., Field, R., Oliver, S. G., . . . Dikicioglu, D. Bioprocesses and Biosystems Engineering 42 (4) 657-663 B3 Biological process analysis, D3 Performance monitoring DOI
A MATLAB toolbox for data pre-processing and multivariate statistical process control 2019 Yi G, Herdsman C, Morris J Chemometrics and Intelligent Laboratory Systems 194 103863 C1 Multivariate data analysis, D3 Performance monitoring, E1 Multivariate statistical process control DOI
A novel approach to identify optimal and flexible operational spaces for product quality control 2025 Kay Sam, Zhu Mengjia, Lane Amanda, Shaw Jane, Martin Philip, Zhang Dongda Chemical Engineering Science 309 121429 E2 Process control, D3 Performance monitoring DOI
A soft sensor based on pH for real-time monitoring of mRNA medicine production 2026 Ahmed Mahdi, Hamed Shady, Cardoso Ricardo, Kenyon Charley, Pohare Manoj, Maamra Mabrouka, Dickman Mark, Cordiner Joan, Kis Zoltán Digital Discovery D2 Multi-block, predictive and multi-scale modelling methods, B3 Biological process analysis, D3 Performance monitoring, B1 Reaction monitoring, D1 Kinetic modelling, B4 Microreactors and flow chemistry DOI
A Transferable Psychological Evaluation of Virtual Reality Applied to Safety Training in Chemical Manufacturing 2021 Poyade Matthieu, Eaglesham Claire, Trench Jordan, Reid Marc ACS Chemical Health & Safety 28 55-65 D3 Performance monitoring DOI
CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology 2017 Cankorur-Cetinkaya Ayca, Dias Joao M. L., Kludas Jana, Slater Nigel K. H., Rousu Juho, Oliver Stephen G., Dikicioglu Duygu Microbiology 163 829-839 B3 Biological process analysis, D3 Performance monitoring DOI
Constructing a Symbolic Regression-Based Interpretable Soft Sensor for Industrial Data Analytics and Product Quality Control 2024 Kay Harry, Kay Sam, Mowbray Max, Lane Amanda, Mendoza Cesar, Martin Philip, Zhang Dongda Industrial & Engineering Chemistry Research 63 4083-4092 D3 Performance monitoring, E2 Process control DOI
Disturbance Attenuation in Fault Detection of Gas Turbine Engines: A Discrete Robust Observer Design 2009 Dai X, Gao Z, Breikin T and Wang H IEEE T. Syst. Man Cybernet. Part C 39(2) 234-239 D3 Performance monitoring DOI
Entropy Optimization Filtering for Fault Isolation of nonlinear Non-Gaussian Stochastic Systems 2009 Guo L, Yin L, Wang H and Chai TY IEEE T. Automat. Cont. 54: 804-810 D3 Performance monitoring DOI
Fault detection in dynamic processes using a simplified monitoring-specific CVA state space modelling approach 2012 Stubbs S, Zhang J, Morris J. Computers & Chemical Engineering Vol 41 77-87 D3 Performance monitoring, E1 Multivariate statistical process control DOI
Fault detection of dynamic processes using a simplified monitoring-specific CVA state space approach 2009 Stubbs S, Zhang J and Morris AJ Eur. Sym. Comput. Aided Process Eng. ESCAPE 19 D3 Performance monitoring DOI
Fault localization in batch processes through progressive principal component analysis modeling 2011 Hong JJ, Zhang J, Morris J Ind Eng Chem Res Vol 50 (13) 8153-8162 D3 Performance monitoring, E1 Multivariate statistical process control DOI
Hybrid modeling as a QbD/PAT tool in Process Development: An industrial E.Coli case study 2016 von Stosch M, Hamelink J M, Oliveira R. Journal of Bioprocess and Biosystems Engineering 39 (5) 773-784 D2 Multi-block, predictive and multi-scale modelling methods, D3 Performance monitoring DOI
Integrating feature attribution and symbolic regression for automatic model structure identification and strategic sampling 2025 Rogers Alexander W., Lane Amanda, Mendoza Cesar, Watson Simon, Kowalski Adam, Martin Philip, Zhang Dongda Computers & Chemical Engineering 197 109036 D3 Performance monitoring, D2 Multi-block, predictive and multi-scale modelling methods DOI
Integrating knowledge-guided symbolic regression and model-based design of experiments to automate process flow diagram development 2024 Rogers Alexander W., Lane Amanda, Mendoza Cesar, Watson Simon, Kowalski Adam, Martin Philip, Zhang Dongda Chemical Engineering Science 300 120580 D2 Multi-block, predictive and multi-scale modelling methods, D3 Performance monitoring DOI
Multiway interval partial least squares for batch process performance 2013 Stubbs S, Zhang J, Morris J. Ind Eng Chem Res Vol 52 (35) 12399-12407 D3 Performance monitoring, E1 Multivariate statistical process control DOI
Nonlinear multiscale modelling for fault detection and identification 2008 Choi SW, Morris J and Lee I-B Chemical Engineering Science 62 (22) 6191-6198 D2 Multi-block, predictive and multi-scale modelling methods, D3 Performance monitoring DOI
On-line multivariate statistical monitoring of batch processes using Gaussian mixture model 2010 Chen T, Zhang J. Computers & Chemical Engineering Vol 34 500-507 D3 Performance monitoring, E1 Multivariate statistical process control DOI
Penalized reconstruction-based multivariate contribution analysis for fault isolation 2013 He B, Zhang J, Chen T and Yang X Ind Eng Chem Res Vol 52 (23) 7784-7794 D3 Performance monitoring, E1 Multivariate statistical process control DOI
Progressive multi-block modelling for enhanced fault isolation in batch processes 2014 Hong JJ, Zhang J, Morris J Journal of Process Control 24(1) 13-26 D2 Multi-block, predictive and multi-scale modelling methods, D3 Performance monitoring DOI
Randomized Kernel Principal Component Analysis for Modeling and Monitoring of Nonlinear Industrial Processes with Massive Data 2019 Zhou Z, Du N, Xu J, Li Z, Wang P, Zhang J Industrial and Engineering Chemistry Research 58 10410-10417 E1 Multivariate statistical process control, D3 Performance monitoring DOI
Reconstruction-based multivariate contribution analysis for fault isolation: A branch and bound approach 2012 He B, Ynag X, Chen T, Zhang J Journal of Process Control Vol 22 1228-1236 D3 Performance monitoring, E1 Multivariate statistical process control DOI
Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses 2025 Espinel-Ríos Sebastián, Avalos José L., del Rio Chanona Ehecatl Antonio, Zhang Dongda Computers & Chemical Engineering 202 109297 E2 Process control, D3 Performance monitoring DOI
Reinforcement Learning for Robust Dynamic Metabolic Control 2026 Espinel-Ríos Sebastián, Walser River, Zhang Dongda Biotechnology and Bioengineering 123 79-91 E2 Process control, D3 Performance monitoring DOI
Towards intensifying Design of Experiements in upstream bioprocess development: An industrial E. coli feasibility study 2016 von Stosch M, Hamelink J M, Oliveira R. Biotechnology Progress D2 Multi-block, predictive and multi-scale modelling methods, D3 Performance monitoring DOI
Zero assignment for robust H_2/ H_infinity fault detection filter design 2009 Dai X, Gao Z, Breikin T and Wang H IEEE T. Sig. Pro. Sys. 57 1363-1372 D3 Performance monitoring DOI