Developing an AI enabled platform for the next generation of maintainers PhD
This exciting PhD focuses on the next generation of maintainers who will have greater access to information, go through less training and need to maintain more complex assets over typically a longer life cycle for assets such as ships and planes.
The expectation is that new skills will be required for all technicians in basic control systems, electrical engineering and computing competencies. Skills such as interpreting fault messages, data fusion and data extraction represent a relatively new and specialised strand of abilities that are already being required.
As examples, advances in mobile devices, sensors and augmented reality will drive a need for technicians to be trained in how to navigate and troubleshoot the various user interfaces. It may also lead to a lower skill class for basic maintenance procedures. Growth in modular component design is expected to give rise to a plug-and play mentality.
The aim of the PhD is to develop an artificial intelligence (AI) based platform that focuses on assisting the next generation maintainer. The AI platform is expected to support a range of scenarios that the future maintainer will be involved in such as:
• First responder – front line, plug‐and‐play, reactive work
• Equipment Care technician – roving position, focus on inspections and preventative/ proactive work (IT enabled with augmented reality and real‐time support)
• Diagnostician and data analyst – Primarily office‐based performing the diagnostics and inputs to planning (supports the above 2 streams)
The project will need to encompass lots of concepts and technologies; Internet of Things (IoT), big data analytics, AI, and Virtual / Augmented Reality. Consideration should be given to these concepts, and the scalability of these to enhance the productivity of the next generation maintainer. The project should consider the information or data that needs to be collected within the context of maintenance e.g. what data, where from, who for, what for?
The AI platform will enable sustained support to the maintainer in different areas such as a) diagnostics, b) preventative and proactive work, c) reactive and minor repair work, and d) fabrication and specialist repairs. Each of these areas has quite distinct skills sets and behaviour’s associated with them, thus the AI platform would help to deskill these, and assist the maintainer. As an example, the AI platform would enable full use of the emerging technologies and embedded sensors given the diverse needs of maintainers.
1. Conduct literature review to identify best practice in AI;
2. Identify suitable data infrastructure in the AI platform;
3. Construct an AI platform for the future maintainer decision making requirements;
4. Establish a set of common principles or approaches for future development of AI for future maintainers;
Type of opportunity
At Cranfield, the candidate will be based at the Through-life Engineering Services Centre, which hosts cutting-edge simulation and visualisation facilities. The student will have access to high-end computers for simulating the complex nature of maintenance. There will be relevant visits to various sites of BAE Systems throughout the PhD to develop and demonstrate the research.
Sponsored by EPSRC and BAE Systems, this studentship will provide a bursary between £18,000-£20,000 (tax free) plus fees* for three years.
Candidates should have a minimum of an upper second (2.1) honours degree (or equivalent) preferably in Computer Science/ Mechanical Engineering / Industrial Engineering / Mathematics / Operations Research but candidates in other degrees related to Engineering or related quantitative fields would be considered. Candidates with an MSc degree in these disciplines will be desirable.
How to apply
To find out more, head to https://www.cranfield.ac.uk/research/phd/developing-an-ai-enabled-platform-for-the-next-generation-of-maintainers
If you are eligible to apply for this studentship, please complete the online application form by clicking on ’Visit Website’.
For further information please contact:
Name: Dr. John Erkoyuncu
Email: [email protected]
T: (0)1234 75 4717