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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 Mechanistic and Cautionary Case Study on the Use of Alternating Potential in Electrochemical Reactions 2020 Wills Alfie G., Poole Darren L., Alder Catherine M., Reid Marc ChemElectroChem 7 2771-2776 B1 Reaction monitoring, D1 Kinetic modelling DOI
A reinforcement learning-based hybrid modeling framework for bioprocess kinetics identification 2023 Mowbray Max R., Wu Chufan, Rogers Alexander W., Rio-Chanona Ehecatl A. Del, Zhang Dongda Biotechnology and Bioengineering 120 154-168 D1 Kinetic modelling 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
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
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
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
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
Dynamic modelling of the killing mechanism of action by virus-infected yeasts 2019 Sheppard Sean, Dikicioglu Duygu Journal of The Royal Society Interface 16 20190064 B3 Biological process analysis, D1 Kinetic modelling 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
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
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
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
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
Formal model of Parkinson’s disease neurons unveils possible causality links in the pathophysiology of the disease 2020 Nadal Morgane, Schierle Gabriele S. Kaminski, Dikicioglu Duygu D1 Kinetic modelling, B3 Biological process analysis DOI
Handling variability and incompleteness of biological data by flexible nets: a case study for Wilson disease 2018 Júlvez Jorge, Dikicioglu Duygu, Oliver Stephen G. npj Systems Biology and Applications 4 B3 Biological process analysis, D1 Kinetic modelling 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
Improved method for kinetic studies in microreactors using flow manipulation and non-invasive Raman spectrometry 2011 Mozharov S, Nordon A, Littlejohn D, Wiles C, Watts P, Dallin P and Girkin JM Journal of the American Chemical Society 133 3601-3608 A1. Non-invasive Raman spectrometry, B1 Reaction monitoring, B4 Microreactors and flow chemistry, D1 Kinetic modelling 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
Investigating ‘greyness’ of hybrid model for bioprocess predictive modelling 2023 Rogers Alexander W., Song Ziqi, Ramon Fernando Vega, Jing Keju, Zhang Dongda Biochemical Engineering Journal 190 108761 D1 Kinetic modelling 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
Kinetic and hybrid modeling for yeast astaxanthin production under uncertainty 2021 Vega-Ramon Fernando, Zhu Xianfeng, Savage Thomas R., Petsagkourakis Panagiotis, Jing Keju, Zhang Dongda Biotechnology and Bioengineering 118 4854-4866 B1 Reaction monitoring, D1 Kinetic modelling DOI
Kinetic modeling and process analysis for Desmodesmus sp. lutein photo-production 2017 del Rio-Chanona Ehecatl Antonio, Ahmed Nur rashid, Zhang Dongda, Lu Yinghua, Jing Keju AIChE Journal 63 2546-2554 D1 Kinetic modelling 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, C1 Multivariate data analysis 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
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
Multivariate kinetic hard-modelling of spectroscopic data: A comparison of the esterification of butanol by acetic anhydride on different scales and with different instruments 2008 Puxty, Neuhold Y-M, Ehly M, Gemperline PJ, Nordon A, Littlejohn D, Basford JK, De Cecco M and Hunderbuhler K Chem. Eng. Sci., 63 (19) 4800-4809 B1 Reaction monitoring, D1 Kinetic modelling 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
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
Nonlinear wave modeling and dynamic analysis of internal thermally coupled distillation columns 2012 Liu X, Zhou Y, Cong L, Zhang J. AIChE Journal Vol 58 No 4 1146-1156 D1 Kinetic modelling, E2 Process control 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
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
Overproduction of L-tryptophan via simultaneous feed of glucose and anthranilic acid from recombinantEscherichia coliW3110: Kinetic modeling and process scale-up 2018 Jing Keju, Tang Yuanwei, Yao Chuanyi, del Rio-Chanona Ehecatl A., Ling Xueping, Zhang Dongda Biotechnology and Bioengineering 115 371-381 D1 Kinetic modelling 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
Photocatalytic Production of Bisabolene from Green Microalgae Mutant: Process Analysis and Kinetic Modeling 2018 Harun Irina, Del Rio-Chanona Ehecatl Antonio, Wagner Jonathan L., Lauersen Kyle J., Zhang Dongda, Hellgardt Klaus Industrial & Engineering Chemistry Research 57 10336-10344 D1 Kinetic modelling 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
Quality by digital design in action: a workflow for crystallisation and isolation 2025 Houson Ian, Siddique Humera, Chong Magdalene W.S., Robertson Murray, Turner Alice J., Nordon Alison, Osman Amal, Galindo Amparo, Dunn Andrew S., Johnston Blair, Benyahia Brahim, Brown Cameron J., Mustoe Chantal L., Price Chris J., Reilly Chris D., Adjiman Claire, Jackson George, Prasad Elke, Halbert Gavin, Feilden Helen, Sefcik Jan, McGinty John, Robertson John, Smith Kenneth, Al-Attili Mais, McGowan Mark, Siddique Mariam, Pathan Momina, Rajoub Nazer, Hamilton Niki, Feeney Rachel, Brown Scott, Urwin Stephanie J., Bernet Thomas, Pickles Thomas, Li Wei, Florence Alastair J. International Journal of Pharmaceutics 686 126343 D2 Multi-block, predictive and multi-scale modelling methods, E2 Process control 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
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
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
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
Scale-up of batch kinetic models 2007 Ehly M, Gemperline PJ, Nordon A, Littlejohn D, Basford JK and De Cecco M Anal Chim Acta 595 80-88 B1 Reaction monitoring, D1 Kinetic modelling Download 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
Ship fuel consumption monitoring and fault detection via partial least squares and control charts of navigation data. Transportation Research Part D: Transport and Environment. 2019 Capezza C, Coleman, SY, Lepore A, Palumbo B, Vitiello L. in press C. Multivariate Data Analysis, D. Process Modelling
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
The development of an industrial-scale fed-batch fermentation simulation 2015 Goldrick Stephen, Stefan Andrei, Lovett David, Montague Gary, Lennox Barry Journal of Biotechnology 193 70-82 D1 Kinetic modelling 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
Trialkylammonium salt degradation: implications for methylation and cross-coupling 2021 Washington Jack B., Assante Michele, Yan Chunhui, McKinney David, Juba Vanessa, Leach Andrew G., Baillie Sharon E., Reid Marc Chemical Science 12 6949-6963 B1 Reaction monitoring, D1 Kinetic modelling 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