"The UK process manufacturing industries need focused research and development that will enhance their production facilities, increase their use of existing plant assets, provide assured production consistency, minimise energy use and eliminate environmental impact. As founder members of CPACT, we believe the Centre creates a synergy which brings together university researchers with industrial engineers and scientists in chemical and process engineering, analytical sciences, mathematics and statistics.
The R&D and technology translation through Knowledge transfer partnerships at CPACT Newcastle focuses on PAT and advanced chemometrics, analytical and process data fusion, intelligent process performance monitoring and process diagnostics, neural network modelling and batch-to-batch process optimisation and control.
Professor Julian Morris and Dr Jie Zhang
General Contact Information
| WWW: | http://www.ncl.ac.uk/ceam/staff/profile/julian.morris |
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CPACT Contact Information
Please note that this contact information is for CPACT related enquiries only.
Professor Julian Morris
| Address: | CPACT (Newcastle) Merz Court University of Newcastle Newcastle NE1 7RU |
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| Email: | julian.morris@ncl.ac.uk |
CPACT Related Research Interests
Julian Morris and Jie Zhang
On-going R&D at Newcastle
- Process Performance Monitoring and Multivariate Statistical Process Control:
- Dynamic process performance monitoring
- Model-based performance monitoring
- The integration of spectral and process data
- Intensified Processing and Digital Bioproduction – a new large European project researching bio-intensified bio-polymer and bio-surfactant production
- Rapid Prototyping in Biopharmaceuticals for Fermentation Process Development, Optimisation and Production, with Strathclyde Biosciences (Brain McNeil), miniaturised sensors (David Littlejohn), UCL Biochemical Engineering (Frank Baganz) and Newcastle (Julian Morris) – industrial consortium being put together if anyone is interested
- PAT and the extraction of maximum information from messy spectroscopic data (Dr Zengping Chen)
- Advanced Chemometrics for the extraction and elucidation of chemical and biological information from spectroscopic measurements contaminated by spectral variations, instrument variations and variations caused by fluctuations in both external process variables and physical properties of the materials being measured (Dr Zengping Chen)
- Knowledge Transfer Partnership with The National Nuclear Laboratory (NNL) and the British Nuclear Fuels Group on Predictive Modelling and Performance Monitoring
- Knowledge Transfer Partnership with GSK of Process Analytics (Strathclyde and Newcastle)
- Advanced Data Mining – Commercialisation of an advanced multivariate data mining toolbox with AJM Consulting (MS2)
- Neural networks for process modelling and control
- Data based nonlinear process modelling
- Soft-sensor and inferential estimation
- Modelling and control of batch processes
- Iterative learning control of batch processes
- Batch to batch control based on recursively updated nonlinear PLS models
- Reliable optimisation incorporating model prediction confidence bounds
- Inferential feedback control
- Monitoring of processes with multiple operation modes using principal angle and multiple PCA/PLS models
- Hybrid modelling of chemical process by combining simplified first principle models with neural network models.
- Recursive nonlinear PLS
- Process monitoring using nonlinear principal component analysis