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Conceptualize and implement an early warning system on real time process data using smart analytics, machine learning etc.
Leuven | More than two weeks ago
In order to predict and prevent out of spec situations of its facilities, Imec wants to implement an efficient early warning system that runs on real time process data. We want to predict out of spec situations and want to detect anomalies between the process parameters. The scope of the thesis: to define and evaluate the concepts and to implement them in the form of a proof of concept.
In order to predict and prevent out of spec situations of its facilities, Imec wants to implement an efficient early warning system that runs on real time process data. We want to predict out of spec situations and want to detect anomalies between the process parameters. The scope of the thesis: to define and evaluate the concepts and to implement them in the form of a proof of concept.
Type of project: Thesis
Duration: TBD
Required degree: Master of Engineering Technology, Master of Engineering Science
Required background: Computer Science
Supervising scientist(s): For further information or for application, please contact: Tom Van de Peer (Tom.VandePeer@imec.be)