This is an exciting opportunity to study a PhD degree in the area of AI-Optimised Maintenance Paradigm for Aircraft Systems. The research would focus on leveraging Artificial Intelligence algorithms for optimising maintenance systems for the next generation unmanned and more-electric aircraft (UAV/MEA) configurations. Read more Read less

The maintenance regime prevalent in the aircraft industry revolves around MSG-3 (Maintenance Steering Group-3) - based on reliability centred maintenance. MSG decision logic process develops a scheduled maintenance program to ensure safety and reliability for the equipment at the lowest possible cost. Current MSG analysis is time and cost-intensive and prone to missed preventive and predictive routines. There are several artificial intelligence-based enhancers, which if optimally designed, will provide singularity and enable optimised decision based supported advisories. With the next generation more unmanned and more-electric aircrafts (UAV/MEA), the maintenance paradigm will change significantly and would require intelligent adaptation of MSG-3 with AI.


This research project aims at designing and developing an AI-optimised maintenance paradigm that would adapt the existing MSG3 to the next generation of UAV/MEA configuration. AI-Optimised maintenance system should be able to generate and prioritise maintenance according to the modes of failure in a dynamic real-time environment. Also, it should support managerial decision-making with respect to inventory policy, diagnostics, or the setting up of adaptive and appropriate preventive maintenance strategies and schedules. Hybrid methods such as ANFIS (Adaptive Neuro-Fuzzy Inference System) could be one of the choices to leverage in the development of the maintenance system. 


Cranfield is a unique learning environment with world-class programmes, unrivalled facilities and close links with business, industry and governments, all combining to attract the best students and teaching staff from around the world. In 2014, 81% of research at Cranfield was rated as world-leading or internationally excellent in the Research Excellence Framework (REF).


The Integrated Vehicle Health Management (IVHM) Centre is in its 12th year of operation. Founded by Boeing and a number of aerospace partners (BAE Systems, Rolls-Royce, Meggitt and Thales) in 2008, it has grown to perform work in sectors such as transport, aerospace, and manufacturing. The Centre integrates a multidisciplinary research effort to develop cost-effective component and system health management technologies capable of supporting ground and on-board applications of high-value, high-complexity systems.


IVHM Centre is a member of Digital Aviation Research and Technology Centre (DARTeC), which focuses its researchon aircraft maintenance, connected systems, unmanned traffic management, seamless journey, distributed airport/airspace management, and conscious aircraft. Research England, Thales, Saab, Aveillant IVHM Centre and Boxarr are some of the prominent members of DARTec. IVHM Centre also works in close collaboration with Aerospace Integration Research Centre (AIRC), founded in partnership with Airbus and Rolls-Royce. The potential PhD candidate will have access to the facilities held by AIRC and DARTeC in addition to having interactive sessions with experts at AIRC and DARTeC.  


The successful culmination of this project envisages the availability of an efficient and intelligent maintenance system that determines the precise timing of all applicable maintenance actions to ensure aircraft will be available when needed throughout their operational service life. Also, the AI-Optimised maintenance system would serve as a benchmark for other high-end platforms such as ships, autonomous vehicles as well as the maintenance, repair and overhaul (MRO) organisations in optimising their operations.


The project will provide active collaboration and exchange of ideas and knowledge with key stakeholders within different centres of the Cranfield University and industrial partners in the aircraft industry. The paraphernalia of AI and Machine Learning based applications within IVHM centre and across other research centres would be helpful for the potential researcher in acquiring essential knowledge and building skills (e.g., AI algorithms’ formulation) required for this specific research project.


The IVHM Centre encourages and supports ample opportunities for disseminating individual research through reputed journals and presenting papers in high profile and well-known IEEE conferences within the UK and across the globe. More significantly, you will have the opportunity to present your research work during quarterly technical reviews to the wider research community from within the university and the industrial partners. It also provides a networking platform for promising researchers to lay the foundations of their professional relationship with key representatives from various companies.         


Upon successful completion of the project, the potential candidate will be able to carry out research activities independently and more vigorously. This research will be formative for the potential candidate in building his/her analytical logic and algorithm craftsmanship. The understanding of the essence and application of futuristic AI-optimised maintenance system in aircraft would broaden the employability scope appreciably.     

At a glance

  • Application deadline30 Apr 2021
  • Award type(s)PhD
  • Start dateAs soon as possible
  • Duration of award3 years
  • EligibilityUK, EU, Rest of World
  • Reference numberSATM174

Entry requirements

Graduate and post-graduate students with a degree in engineering, data science, or any other related physical sciences subject, and Researchers and Engineers with a background/interest in maintenance management systems, PhD candidates must have software programming skills and familiarity with AI and Machine Learning methods. Above all, research aspirants with an innovative approach, high motivation and willingness to learn are welcomed. 


This is a self-funded opportunity. 

About the sponsor

This is a self-funded opportunity.

Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.

How to apply

For further information please contact:

Name: Suresh Perinpanayagam
T: (0) 1234 750111 Ext: 2377       

If you are eligible to apply for this studentship, please complete the online application form.