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Visualizing architectural inter-relationships and uncertainties between constituent systems within a systems of systems

Project Description

This studentship is a terrific opportunity to research exciting new aerospace digitalisation techniques that will support Industry-4.0 concepts, including digital-twin and next generation interactive visualization. This will involve developing new systems of systems engineering techniques with interactive visual analytics techniques to aid systems trade-off and optimisation of performance objectives for future aircraft design and manufacture. The research will involve working with world-leading academics and industry experts. On successful completion of the PhD there are excellent career prospects.

Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
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Full Project Detail:

This PhD is concerned with undertaking novel research into new digital techniques that will help understand the complex relationships that exist within the context of a systems of systems (SoS). New model-based systems engineering (MBSE) methodologies are required to facilitate interactive parameter trade-off/optimisation between the constituent systems to achieve key performance objectives. An important aspect of the research is development of techniques to deal with uncertainties in the key design parameters and how these are visualised in conjunction with respect to the overall SoS architecture.

Proof of concept demonstrators that address the visualization of parameter dependencies/ uncertainties will be developed and used to show how the use of digital technologies can provide improved traceability of the evolving SoS architecture at the level of the detailed constituent system or surrogate model levels.

Key themes:
• Research and develop new MBSE methodologies that represent parameter uncertainty
• Develop novel visualization techniques that highlight critical inter-parameter dependencies
• Create the visualization framework that can be applied to MBSE
• Creation of visualization tool that allows interactive visualization of parameter trade-off
• To investigate how to determine validity of the techniques at different levels of granularity – from constituent system to surrogate model level.
• Application of technique to Airbus defined USE case to confirm applicability

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Entry requirements:

Applicants should have, or expect to achieve, at least a 2:1 Honours or a relevant Master’s degree (or equivalent) in any of the following: computer science, data science, systems engineering, human-computer interaction, software engineering, or a related engineering subject.

How to apply:

Interested candidates are welcome to contact Professor Kalawsky to find out more. However, all applications should be made online at Under programme name, select ‘Mechanical and Manufacturing Engineering’

Please quote reference number: RSK2019

Funding Notes

This PhD project is sponsored through a highly prestigious EPSRC I-Case award with an enhanced annual stipend of £18k/year for 4 years, plus tuition fees with a generous annual allowance to cover attendance at international conferences and an industrial placement with Airbus. Due to funding limitations the award is only eligible for UK fee status candidates.

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