PhD Research Studentships
Distributed Prognostics for Self-Healing Production Systems
University of Nottingham -Department of Mechanical, Materials & Manufacturing Engineering
Faculty of Engineering – Division of Manufacturing
This is one of the premier engineering departments in the UK. It has an international reputation for research, and was ranked joint 4th in Unit 28 in the 2008 Research Assessment Exercise (RAE). Mechanical Engineering at Nottingham was rated 6th in the Guardian and 11th in The Times in recent university league tables.
Applications are invited for fully funded PhD studentships at The University of Nottingham in a number of areas. The research projects will benefit from a close collaboration with large companies such as Ford UK, Electrolux Italy, Fiat, and a number of other industrial and research partners across Europe.
The motivation is to enable future production systems to be able to adjust themselves in response to disturbances, effectively becoming self-healing. The aim will be to investigate Bayesian models for prognosis of eminent faults and expected performance deterioration in production systems and link this to the most appropriate corrective actions. The focus will be on developing models which can be distributed and embedded into intelligent devices used to build complex manufacturing systems. Each device will monitor its own behaviour and will have embedded strategies to maintain its own operational performance. Devices will need to be able to adapt their behaviour and learn from experience understand the context in which they operate. To support this, methods for Bayesian model learning and model creation from manufacturing system design information will be explored.
Students should have research interests in one or more of the following areas:
- Diagnostics and prognostics
- Bayesian theory
- Machine learning
- Model adaptive control
All students should have, or expect to obtain, a first-class or good 2:1 honours degree or MSc in engineering, operations management, computer science, applied mathematics or a related subject. Good communication skills and the ability to work as part of a team as well as independently are essential.
Experience with software tools such as Matlab and experience with programming languages such as Java or C# would be beneficial.
The studentship covers fees at the home student rate and a tax-free maintenance allowance up to £15,000 per annum (for UK/EU students only). Funding opportunities for non UK/EU students are also available through the Dean of Engineering Scholarship program of the University of Nottingham (http://www.nottingham.ac.uk/internationalstudents/scholarshipsfeesfinance/scholarships/scholarshipdetails/research-dean-engineering.aspx).
Informal enquiries may be addressed to Dr N Lohse, email: Niels.Lohse@Nottingham.ac.uk.
Application forms and notes of guidance can be obtained online, via the 'Apply’ button below, and select the “Engineering Faculty” in the online application system. Please quote ref. ENG/689.
This studentship will remain open until filled.