About the Project
Supervisor: Dr Huajie Yi
This project aims to develop data-driven asset criticality ranking and maintenance optimisation methods. By integrating machine learning with operational, condition-monitoring, and environmental data, it investigates multi-stress degradation, predicts asset failure risks, and prioritises critical assets to improve maintenance efficiency and power system reliability.
Effective asset management in electrical power systems is essential for ensuring operational reliability, minimising downtime, and optimising maintenance costs. However, traditional maintenance strategies often overlook the combined effects of environmental and operational stresses on asset degradation, limiting the accuracy of asset risk assessment and maintenance prioritisation.
This project aims to develop a data-driven framework for asset condition assessment, failure risk prediction, criticality ranking, and maintenance optimisation. Particular attention will be given to understanding how multiple stress factors influence asset health and long-term reliability.
The research will combine laboratory-based experiments with the analysis of available datasets, published research findings, and relevant environmental and operational information. Experimental investigations will provide insights into degradation mechanisms, while data analysis and modelling will support the assessment of asset performance and failure risks.
Expected outcomes include improved understanding of asset degradation mechanisms, more accurate risk assessment, systematic asset criticality ranking, and optimised maintenance strategies, supporting proactive decision-making and enhanced power system reliability.
You'll join an interdisciplinary and diverse academic team in the Electrical Power Engineering research group that will support you in expanding your transferrable skills, such as critical review of the literature, academic writing and publishing, as well as collaborating with your team members and organising activities. You'll acquire hands-on experience with testing facilities and operate state-of-the-art equipment in the Tony Davies High Voltage Lab (TDHVL) as part of your experimental research.
Entry requirements
A UK 2:1 honours degree, or its international equivalent, in electrical or electronic engineering.
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
You need to:
- choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- search for programme PhD Electronic & Electrical Engineering (7092)
- add name of the supervisor in section 2 of the application
Applications should include:
- research proposal
- your CV (resumé)
- 2 academic references
- degree transcripts and certificates to date
- English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, doctoralcollege-admissions@soton.ac.uk.
Project leader
For an initial conversation, H.Yi@soton.ac.uk.
The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.