"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.
CPACT at Newcastle is integrated with the Industrial Statistics Research Unit (ISRU) through Mr Matthew Linsley (Director of ISRU)and Dr Shirley Coleman in the School of Mathematics and Statistics with links into the School of Chemical Engineering and Advanced Materials, Professor Julian Morris and Dr Jie Zhang. The R&D and technology translation through Knowledge Transfer Partnerships within the School of Chemical Engineering and Advanced Materials focuses on Process Analytical Technologies (PAT), analytical and process data fusion, intelligent process performance monitoring and process diagnostics, neural network modelling and batch-to-batch process optimisation and control. Within ISRU the technology translation covers applications of statistics in business, industry and health; investigating patterns in multivariate data; Lean Six Sigma; Statistical Process Control; data mining, Design of Experiments, big data analytics and modelling and prediction.
Professor Julian Morris and Dr Jie Zhang (Chemical Engineering and Advanced Materials); Dr Shirley Coleman and Mr Matthew Linsley (ISRU)
General Contact Information
CPACT Contact Information
Please note that this contact information is for CPACT related enquiries only.
Professor Julian Morris
Newcastle upon Tyne
Mr Matthew Linsley
|Position:||Director of ISRU|
|Address:||ISRU, School of Maths and Stats
Newcastle upon Tyne
Dr Moritz Von Stosch
|Position:||Lecturer in Chemical Engineering|
CPACT Related Research Interests
CPACT Related research and technology transfer interests
- Process Performance Monitoring and Multivariate Statistical Process Control
- Process Fault Detection and Diagnosis
- Dynamic process performance monitoring
- Model-based performance monitoring
- The integration (data fusion) of spectral and process data
- Predictive modelling with Sellafield Ltd and National Nuclear Laboratory
- Software-sensors; inferential estimation and control
- Modelling and control of batch processes and Iterative learning control of batch processes, Batch process control, Batch-to-Batch control, optimal control of batch processes, genetic algorithms, intelligent control systems.
- Hybrid modelling of chemical process by combining first principle models with data based models (egneural network and PLS models)
- Design of Experiments
- Lean Six Sigma
- Data Mining