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Research project title

Machine learning driven decision support for the operation of process systems

Education level

Master or doctorate

Director/co-director

Director: Moncef Chioua

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November 1, 2021

Areas of expertise

Chemical engineering

Artificial intelligence

Industry 4.0

Unit(s) and department(s)

Department of Chemical Engineering

Conditions

The student must fulfill the conditions required for enrollment in graduate studies at Polytechnique Montreal in Chemical Engineering and have a sufficient level of English to carry out his/her research and write publications.

To apply, please send me an e-mail including a self-introduction, resume, transcripts and other supporting materials. Particular knowledge/expertise in one or more aspects of the project will be appreciated.

Detailed description

Process industries including chemicals, oil and gas industries, pharmaceutics, mining, metals and pulp and paper play an important role in the Canadian economy. An unplanned shutdown of a large plant can cost several hundred thousand dollars.

Large amounts of process data of different type are collected during process operation and stored in process historians. Today, this valuable resource is not fully exploited because of the lack of dedicated tools and methods to extract reliable information from it. Detecting unintended deviations from normal operation or identifying the root cause of abnormal behavior becomes difficult with the ever-increasing amount and complexity of stored data.

Modern machine learning methods have the potential to support building robust and accurate process models able to predict the process behaviour and to diagnose abnormal process situations.

I am looking for a MSc or a PhD Candidate interested in working on the development of novel algorithms and computational tools to support the operation of process systems.

The work will be done in collaboration with industrial partners which will provide the selected candidate an opportunity to work on real-life case studies, to discuss with industrial practitioners and to benefit from the experience of industrial researchers in creating and deploying new technology.

Financing possibility

Funding available, the student is also expected to contribute to funding application.

Moncef Chioua

Assistant Professor

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