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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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, are at the forefront of this evolution. These technologies enable intelligent functionalities in edge devices, facilitating applications in autonomous vehicles, robotics, and Internet of Things (IoT) systems
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the subject area and continues to expand its research horizons. It plays a pivotal role in the £65 million Digital Aviation Research and Technology Centre (DARTeC), leading advancements in aircraft electrification
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opportunity in composites materials for space application research in the Composites and Advanced Materials Centre and the Centre for Defence Engineering at Cranfield university. The focus of this PhD will be
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such as Boeing, Rolls-Royce, BAE Systems, Meggitt, and Thales. The IVHM Centre is globally recognized for defining the subject area and continues to expand its research horizons. It plays a pivotal role in
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policymakers. Entry requirements Applicants should hold or expect to achieve an equivalent of a first or second-class UK honours degree in materials science, physics, engineering, or a related discipline. The
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Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has
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. Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial problems
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this research is that it should be possible to significantly improve the performance of extreme learning and assure safe and reliable maintenance operation by integrating this prior knowledge into the learning