Intelligent data analytics to optimise energy utilisation in industrial processing
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This Resilient Decarbonised Fuel Energy Systems PhD project will investigate the use of sensor measurements and machine learning to predict and optimise either the energy production or energy utilisation for a range of industrial relevant case studies. The PhD project will be sponsored by the industrial partner Intelligent Plant, who focus on the analysis and visualisation of industrial data. Although the project will focus on different case studies. The aim is to determine suitable data collection and analysis strategies that can be applied to a variety of different industrial systems. The first and second case studies will focus on energy production systems and the third and fourth on the energy efficiency of industrial processes. An objective of this project is to develop appropriate data analysis and visualisation methods, which contribute to the UK's, net zero ambition
| University of Nottingham | LEAD_ORG |
| Intelligent Plant | STUDENT_PP_ORG |
| Nicholas Watson | SUPER_PER |
| Khivishta Boodhoo | STUDENT_PER |
Subjects by relevance
- Energy production (process industry)
- Energy efficiency
- Industry
- Visualisation
- Optimisation
- Energy
- Machine learning
- Measurement
- Case study
- Power plants
Extracted key phrases
- Resilient Decarbonised Fuel Energy Systems phd project
- Industrial relevant case study
- Different industrial system
- Intelligent data analytic
- Energy utilisation
- Energy production system
- Industrial processing
- Industrial partner Intelligent Plant
- Industrial datum
- Energy efficiency
- Different case study
- Second case study
- Appropriate datum analysis
- Suitable datum collection
- Analysis strategy