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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
An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation 2021 Savage Thomas R., Almeida-Trasvina Fernando, del-Rio Chanona Ehecatl A., Smith Robin, Zhang Dondga AIChE Journal D2 Multi-block, predictive and multi-scale modelling methods DOI
Artifical intelligence techniques applied as estimator in chemical process systems - A literature survey 2015 Ali J M, Hussain M A, Tade M O and Zhang J. Expert Systems with Applications Vol 42 No 14 5915-5913 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Batch to batch iterative learning control using updated models based on a moving window of historical data 2012 Jewaratnam J, Zhang J, Hussain A and Morris J Procedia Engineering Vol 42 232-240 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Batch-to-batch control of fed-batch processes using control-affine feedforward neural network 2008 Xiong Z, Xu Y, Zhang J and Dong J Neural Computing & Applications 17 425-432 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Biomass composition: the “elephant in the room” of metabolic modelling 2015 Dikicioglu Duygu, Kirdar Betul, Oliver Stephen G. Metabolomics 11 1690-1701 B3 Biological process analysis, D2 Multi-block, predictive and multi-scale modelling methods DOI
Comparison of Individual and Integrated Inline Raman, Near-Infrared, and Mid-Infrared Spectroscopic Models to Predict the Viscosity of Micellar Liquids 2020 Haroon Kiran, Arafeh Ali, Cunliffe Stephanie, Martin Philip, Rodgers Thomas, Mendoza Cesar, Baker Michael Applied Spectroscopy 74 819-831 A5. ATR-MIR spectrometry, A3. Transmission NIR spectrometry/Raman spectrometry, D2 Multi-block, predictive and multi-scale modelling methods DOI
Deep learning-based surrogate modeling and optimization for microalgal biofuel production and photobioreactor design 2019 Rio-Chanona Ehecatl Antonio, Wagner Jonathan L., Ali Haider, Fiorelli Fabio, Zhang Dongda, Hellgardt Klaus AIChE Journal 65 915-923 D2 Multi-block, predictive and multi-scale modelling methods DOI
Digital process design to define and deliver pharmaceutical particle attributes 2023 Urwin Stephanie J., Chong Magdalene W.S., Li Wei, McGinty John, Mehta Bhavik, Ottoboni Sara, Pathan Momina, Prasad Elke, Robertson Murray, McGowan Mark, al-Attili Mais, Gramadnikova Ekaterina, Siddique Mariam, Houson Ian, Feilden Helen, Benyahia Brahim, Brown Cameron J., Halbert Gavin W., Johnston Blair, Nordon Alison, Price Chris J., Reilly Chris D., Sefcik Jan, Florence Alastair J. Chemical Engineering Research and Design 196 726-749 D2 Multi-block, predictive and multi-scale modelling methods DOI
Effect of particle size distribution on spatially and angularly resolved diffuse reflectance measurement 2018 Chen Yi-Chieh, Tiernan-Vandermotten Sarra, Lue Leo, Ferreira Carla Sofia, Sefcik Jan, Thannadil Suresh European Pharamaceutical Review 23 34-37 A2 Particle size effects in Raman and NIR, C1 Multivariate data analysis, D2 Multi-block, predictive and multi-scale modelling methods DOI
Energy efficiency optimisation for distillation column using artificial neural network models 2016 Osuolale F, Zhang J. Energy Vol 106 562-578 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Enhanced Predictive Modelling Using Multi Block Methods 2009 Jeong JJ, Zhang J and Morris AJ 19th Symposium on Computer Aided Process Engineering - ESCAPE 19 D2 Multi-block, predictive and multi-scale modelling methods DOI
Extension of the yeast metabolic model to include iron metabolism and its use to estimate global levels of iron-recruiting enzyme abundance from cofactor requirements 2019 Dikicioglu Duygu, Oliver Stephen G. Biotechnology and Bioengineering 116 610-621 D2 Multi-block, predictive and multi-scale modelling methods, B3 Biological process analysis DOI
Flux Balance Analysis of a Genome-Scale Yeast Model Constrained by Exometabolomic Data Allows Metabolic System Identification of Genetically Different Strains 2007 Cakir T., Efe C., Dikicioglu D., Hortacsu A., Kirdar B., Oliver S.G. Biotechnology Progress 23 320-326 D2 Multi-block, predictive and multi-scale modelling methods, B3 Biological process analysis 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
Inferential estimation of kerosene dry point in refineries with varying crudes 2012 Zhou C, Liu Q, Huang D X, Zhang J. Journal of Process Control Vol 22 No 6 1122-1126 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Integration of Metabolic Modeling and Phenotypic Data in Evaluation and Improvement of Ethanol Production Using Respiration-Deficient Mutants of Saccharomyces cerevisiae 2008 Dikicioglu Duygu, Pir Pinar, Onsan Z. Ilsen, Ulgen Kutlu O., Kirdar Betul, Oliver Stephen G. Applied and Environmental Microbiology 74 5809-5816 D2 Multi-block, predictive and multi-scale modelling methods, B3 Biological process analysis DOI
Iterative learning control of a crystallisation process using batch wise updated linearised models identified using PLS 2009 Zhang J, Nguyan J and Morris AJ Computer Aided Chemical Engineering 26, Proceedings of the 19th European Symposium on Computer Aided Process Engineering 387-392 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Machine learning and metabolic modelling assisted implementation of a novel process analytical technology in cell and gene therapy manufacturing 2023 Williams Thomas, Kalinka Kevin, Sanches Rui, Blanchard-Emmerson Greg, Watts Samuel, Davies Lee, Knevelman Carol, McCloskey Laura, Jones Peter, Mitrophanous Kyriacos, Miskin James, Dikicioglu Duygu Scientific Reports 13 B2 Monitoring of drying and powder blending, D2 Multi-block, predictive and multi-scale modelling methods DOI
MBA-GUI: A chemometric graphical user interface for multi-block data visualisation, regression, classification, variable selection and automated pre-processing 2020 Mishra Puneet, Roger Jean Michel, Rutledge Douglas N., Biancolillo Alessandra, Marini Federico, Nordon Alison, Jouan-Rimbaud-Bouveresse Delphine Chemometrics and Intelligent Laboratory Systems 205 104139 D2 Multi-block, predictive and multi-scale modelling methods DOI
MBA-GUI: A chemometric graphical user interface for multi-block data visualisation, regression, classification, variable selection and automated pre-processing 2020 Mishra Puneet, Roger Jean Michel, Rutledge Douglas N., Biancolillo Alessandra, Marini Federico, Nordon Alison, Jouan-Rimbaud-Bouveresse Delphine Chemometrics and Intelligent Laboratory Systems 205 104139 D2 Multi-block, predictive and multi-scale modelling methods, C1 Multivariate data analysis DOI
Metabolic modeling to identify engineering targets forKomagataella phaffii: The effect of biomass composition on gene target identification 2017 Cankorur-Cetinkaya Ayca, Dikicioglu Duygu, Oliver Stephen G. Biotechnology and Bioengineering 114 2605-2615 D2 Multi-block, predictive and multi-scale modelling methods, B3 Biological process analysis DOI
Modelling and control of reactive polymer composite moulding using bootstrap aggregated neural network models 2011 Zhang J, Pantelelis N G. Chemical Product and Process Modeling Vol 6 (2) Article 5 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Modelling of a post combustion CO2 capture process using neural networks 2015 Li F, Zhang J, Oko E and Wang M Fuel 151 156-163 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Multi-scale Multiblock Batch Monitoring:Sensor and Process Drift and Degradation 2015 Alawi A, Zhang J and Morris J, Org. Process Res. Dev. 19 (1) 145-157 B1 Reaction monitoring, D2 Multi-block, predictive and multi-scale modelling methods DOI
Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant 2015 Oko E, Wang M and Zhang J. Fuel 151 139-145 D2 Multi-block, predictive and multi-scale modelling methods, E2 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
Nonlinear process modelling using echo state networks optimised by covariance matrix adaption evolutionary strategy 2020 Liu K, Zhang J Computers & Chemical Engineering 135 106730 D2 Multi-block, predictive and multi-scale modelling methods DOI
Optimal control of fed-batch processess using particle swarm optimisation with staked neural network models 2009 Herrara F, Zhang J Computers & Chemical Engineering Vol 33, No 10 1593-1601 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model 2008 Xiong Z, Zhang J and Dong J Chinese Journal of Chemical Engineering 16 235-240 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Predicting molten steel endpoint temperature using a feature-weighted model optimized by mutual learning cuckoo search 2019 Yang Q, Zhang J, Yi Z Applied Soft Computing Journal 83 105675 D2 Multi-block, predictive and multi-scale modelling methods DOI
Prediction of absorption and stripping factors in natural gas processing industries using feed forward artificial neural network 2016 Ahmad Z, Zhang J, Kashiwao T and Bahadori A. Petroleum Science and Technology Vol 34 No 2 105-113 D2 Multi-block, predictive and multi-scale modelling methods 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
Recent trends in multi-block data analysis in chemometrics for multi-source data integration 2021 Mishra Puneet, Roger Jean-Michel, Jouan-Rimbaud-Bouveresse Delphine, Biancolillo Alessandra, Marini Federico, Nordon Alison, Rutledge Douglas N. TrAC Trends in Analytical Chemistry 137 116206 D2 Multi-block, predictive and multi-scale modelling methods, C1 Multivariate data analysis DOI
Reliable optimal control of a fed-batch fermentation process using ant colony optimisation and bootstrap aggregated neural network models 2014 Zhang J, Feng M Appl. Metaheuristics Process. Eng. 183-200 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Reliable optimisation control of a reactive polymer composite moulding process using ant colony optimisation and bootstrap aggregated neural networks 2013 Mohammed K R, Zhang J. Neural computing & Applications Vol 23 1891-1898 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control DOI
Selective Combination of Multiple Neural Networks for Improving Model Prediction in Nonlinear Systems Modelling through Forward Selection and Backward Elimination 2008 Ahmad Z and Zhang J Neurocomputing 72 (4-6) 1198-1204 D2 Multi-block, predictive and multi-scale modelling methods DOI
Spatially and angularly resolved spectroscopy for in-situ estimation of concentration and particle size in colloidal suspensions 2017 Chen Yi-Chieh, Foo David, Dehanov Nicolau, Thennadil Suresh N Analytical and Bioanalytical Chemistry 409 6975-6988 A1. Non-invasive Raman spectrometry, C1 Multivariate data analysis, D2 Multi-block, predictive and multi-scale modelling methods DOI
Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo-production systems 2021 Anye Cho Bovinille, Carvalho Servia Miguel Ángel, del Río Chanona Ehecatl Antonio, Smith Robin, Zhang Dongda Biotechnology and Bioengineering 118 1932-1942 D2 Multi-block, predictive and multi-scale modelling methods 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