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Quantification of Uncertainty for Maintenance in Complex Engineering Systems

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  • Full or part time
    Dr J Ahmet Erkoyuncu
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Start Date: ASAP
Eligibility: UK/ EU (part funded with additional conditions apply from EPSRC)
Duration of award: 3 years
Ref: CRAN1137
Dr. John Ahmet Erkoyuncu – Lecturer in Service Simulation and Visualisation
Professor Rajkumar Roy – Director of Manufacturing

Sponsored by Dstl and EPSRC, this studentship will provide a bursary of £19,000 p.a. (tax free) plus fees* for three years

This exciting PhD project aims to develop uncertainty quantification approaches for equipment maintenance. During the in-service phase of complex engineering systems (CES) in the defence context, the equipment is expected to carry out the intended functions whilst sustaining reliability. There is an increasing trend to develop performance based targets such as equipment availability to manage the in-service phase of CES. This promotes further challenges with how to reduce cost, and manage performance over the life cycle due to uncertainties.

This PhD will focus on how technical/engineering uncertainties and the wider enterprise related uncertainties associated to the supply chain, logistics solutions and requirements definition can be quantified. The PhD will aim to offer techniques to quantify uncertainty in a scientific manner for various scenarios where the data is potentially incomplete, inconsistent, inaccessible, and relies on expert opinion. Uncertainty prevents the ability to estimate the equipment operational availability and cost of maintaining equipment with confidence. Thus, there is a need for uncertainty quantification approaches, which sets the focus for this PhD project. The project is co-sponsored by Dstl and the UK MoD, which will enable applied research to be conducted.

Uncertainty is the stochastic behaviour of any physical phenomenon that causes the indefiniteness of outcomes, which means the expected and actual outcomes are typically not the same. The technical uncertainties for maintenance may include: degradation, no-fault found, obsolescence, and failure. On the other hand, the enterprise related uncertainties may include: enterprise resilience, requirements, supply chain integration, and organisational re-structuring. In this PhD there are multiple challenges of interest:

• How can we aggregate the overall impact of uncertainties e.g. across multiple elements, systems, organisations?
• Expert opinion driven uncertainty quantification; where there is a lack of standardised way to quantify uncertainty and the experiences of individuals play a key role in determining the potential impact on cost and availability.

As part of the PhD there will be a range of training offerings for the student, including:
• Manufacturing Department – Doctoral Training Programme
• Operations Excellence Institute – Visualisation programme
• A range of MOOC based training offerings will be offered
• Visits to other uncertainty quantification related researchers e.g. University of Bath, Loughborough University, and University of Liverpool

The student will be based at Cranfield University in the Through-Life Engineering Services Centre, which is part of the Manufacturing Department. The student will use the Operations Excellence Institute for simulation studies and the latest computing facilities. The student working on this project will build on previous research that has been completed in the Centre and the student will work within a team of researchers.

As part of working in this industrially sponsored project, the student will work in close collaboration with Dstl, Ministry of Defence UK and the wider Defence industry including organisations such as BAE Systems, Rolls-Royce and BABCOCK International. He/she will need to present their research findings regularly to the project team.

Entry requirements:
Applicants should have a first or second class UK honours degree or equivalent in a related discipline, such as mathematics, or engineering. The ideal candidate should have some understanding in the area of simulation, numerical modelling and industrial service delivery. The candidate should be self-motivated, have good communication skills for regular interaction with other stakeholders, with an interest for industrial research.

How to apply:
For further information please contact: Dr. John Ahmet Erkoyuncu, E: [email protected] T: (0) 1234 75 2747
If you are eligible to apply for this research studentship, please complete the online application form.
For further information contact us today:
School of Aerospace, Transport and Manufacturing
T: 44 (0)1234 758008
E: [email protected]

Funding Notes

* Applicants must be a UK national. We require that applicants are under no restrictions regarding how long they can stay in the UK i.e. have no visa restrictions or applicant has “settled status” and has been “ordinarily resident” in the UK for 3 years prior to start of studies and has not been residing in the UK wholly or mainly for the purpose of full-time education. (This does not apply to UK or EU nationals). Due to funding restrictions all EU nationals are eligible to receive a fees-only award if they do not have “settled status” in the UK.

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