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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
at scale? Digital twins offer a promising foundation, but to truly support engineering decisions, they need to go beyond simulation and begin to interpret and reason about the systems they represent
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-box techniques in the industry is still high. One of the main reasons is that the performance of such techniques highly depends on a large amount of good-quality data. Unfortunately, the availability
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all doctoral candidates to thrive and achieve their full potential. At Cranfield, we value our diverse staff and student community and maintain a culture where everyone can work and study together
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integrated with human expertise, leading to enhanced system performance and sustainability. The project aims to create a foundation for systems that can evolve autonomously while benefiting from continuous
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. This stems from the two main styles of AI development over the last two decades. 'First Wave AI' is used to describe the rules/logic based AI used heavily in the 1990's and 2000's and still in wide use today
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A funded PhD studentship is available within the Autonomous and Cyber Physical Systems Centre at Cranfield University, Bedfordshire, UK. As aerospace platforms go through their service life, gradual
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. The student will have the opportunity to work with experts in the data analytics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University
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conditions. However, these changes are more often reported under quasi-static loads. The use of imaging is quite effective to determine the changes in elastic and thermal properties of materials; but still