/Conceptualize and implement an early warning system on real time process data using smart analytics, machine learning etc.

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)

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