Research degree: PhD programme
Start date: 2021
Open Research and Contributor ID (ORCID): 0000-0002-6865-1315
Research summary
Project title: Machine Remaining Useful Life Prediction Using AI and IoT
The prediction of the machine remaining useful life is a very challenging tasks due to the complexity of the external factors that may affect the calculation metrics. Its applications are wide and in several fields such as renewable energies manufacturing, aerospace, and aviation. In this study, I am mainly concerned with developing/ optimizing deep learning/ neural networks technique that would facilitate the run-to-failure training data of the machinery and accurately represent the substantial features and calculate the remaining useful life. Initial results outperforms methods presented in International Standard Organization (ISO) such as in ISO281 which is the standard concerned with the calculation of rotating machinery remaining useful life estimation.
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Research Supervisor: Ahmed Onsy
Student: Ahmed Ayman Abdelaal
