IEEE Computational Intelligence Society Distinguished Lecture
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|Date:||Thursday 21 December 2017|
|Venue:||EN101, Level 1, EN Building, Hawthorn Campus|
Applications of Computational Intelligence in Condition-Based Maintenance
Condition-based maintenance (CBM) is an important tool for running a plant or factory in an optimal manner. Better operations will lead to lower production cost and lower use of resources. Data-driven approaches which do not rely on the domain knowledge are popular in solving CBM problems. This talk will provide an overview of computational intelligence in the application of CBM such as robust prognostic and automated surface inspection.
As one of the key enablers of condition-based maintenance, prognostic involves the core task of determining the remaining useful life of a system. This talk will discuss the use of deep learning ensembles to improve the prediction accuracy of remaining useful life estimation. A case study involving the estimation of remaining useful life for turbofan engines will also be presented.
About the speaker
Prof. TAN Kay Chen received the B.Eng. degree (First Class Hons.) and the Ph.D. degree from the University of Glasgow, U.K., in 1994 and 1997, respectively. He is currently a Professor with the Department of Computer Science, City University of Hong Kong, Hong Kong. He has published over 130 journal papers and over 130 papers in conference proceedings, and co-authored six books.
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Contact Information: Kai Qin
Email: firstname.lastname@example.org Tel: 03 9214 3766