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fitting for reduced order electrochemical models. Early detection of thermal anomalies in battery packs. Physics-based models and state of health estimation in lithium-sulfur batteries. Collecting data and
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impacts, interest in river health has grown, pushing monitoring programmes increasingly into the spotlight. At the same time, advancements in sensor technology and deployment mean that much larger ranges
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in collaboration with industry leaders such as Boeing, Rolls-Royce
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. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in collaboration with industry leaders such as Boeing, Rolls-Royce, BAE Systems, Meggitt
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resources, and design facilities, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in
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to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
amounts of maintenance and operational data, from sensor streams to technical logs, yet much of it remains unstructured, fragmented, and underused. Hidden within these records are insights that could help
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack