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PhD in Advanced digital twin applications for future maintenance optimisation

Project Description

This PhD is co-funded by the EPSRC Industrial CASE 2018 and BAE Systems. The PhD involves applied research within the context of defence marine industry and it will involve multi-disciplinary work in information systems, systems engineering, forecasting, modelling and simulation, maintenance, through-life engineering, software engineering. The research will extend the work on digital twins by developing algorithms that collects, analysis and distributes information for optimised efficiency and effectiveness in delivering through-life support solutions for complex engineered products such as ships and submarines.

The development of computer modelling, simulations and connectivity between products and a digital twin (DT) introduces new and unique opportunities to elicit value for service and support through optimised decision making. The opportunities, risks and requirements of a digital twin are not fully understood in research literature, which makes this proposal relevant for further academic research. The key challenge and most significant benefit of the DT is realised by the combination, integration and analysis of data sources from across the product lifecycle and across difference levels from component to system of systems.

A Digital Twin (DT) could be used for predicting how a physical product behaves and performs in the future in a range of alternative scenarios and environments. The research fundamental for this PhD centres on developing the algorithms that will allow creation of the digital representation of the physical asset for a large variety of dynamic scenarios (e.g. operating conditions, maintenance interventions) within a maintenance context. The DT could be used to determine when and where failure or damage is likely to occur, and when to perform maintenance. Any unanticipated failures or damage found will be added to the integrated DT so that the model continually reflects the current state of the actual platform or engine.

The Through-life Engineering Services (TES) Centre focuses on developing knowledge, technology and process demonstrators to provide the capability for the concept design of high-value engineering systems based on design and manufacturing for through-life engineering services. The TES Centre has critical mass of researchers in augmented reality, digital twins, degradation assessment and artificial intelligence. The TES Centre has currently several research contracts in the areas related to the post and providing excellent reputation at the national and the international level.

A major focus of this PhD will be on developing a role for the use of a DT at the commodity level for planning maintenance, repair, overhaul and update (MROU). This will aim to support with defining what maintenance intervention needs to be conducted in the front end to be able to meet the vision for MROU with the aim of improving the through-life costs and performance. This PhD aims to develop algorithms to operate a digital twin that fully integrates the computational representation of a commodity through rapid simulation and visualisation within a maintenance context. The academic contribution is in developing an Artificial Intelligence (AI) enabled digital twin that allows data integration and simulation for scientifically evaluating varied maintenance interventions.

The student will have funding to attend international conferences and go on training where relevant. The student will gain skills in: applied research, digital twins, software engineering, modelling, simulation, maintenance, through-life engineering, degradation assessment, project management, and presentation skills.

Funding Notes

To be eligible for this funding, applicants must be a UK national. The funding amount is between £17k-£20k p/a tax free.

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