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Accepting PhD Students
Life Extension of High Value Engineering Asset Based on Smart Condition Monitoring Manufacturers need to increase the availability of their engineering asset, in order to reduce unscheduled downtime and maximise the asset utilisation. This requires techniques managing maintenance and extending the asset’s life. Condition monitoring offers a predictive approach to asset maintenance, ensuring optimum asset performance while keeping downtime to a minimum. This PhD project will develop a system solution to predict the machine failure effectively and efficiently. You need to have a first class or upper second class honours degree or equivalent qualification in Mechatronics, Electronics Engineering, Computer Science to apply for this post. Knowledge/experience of condition monitoring, signal processing, data analysis, programming on Matlab or other professional software are preferred. Please contact Dr Yuchun Xu (email@example.com) with your CV for more details.