Testing and applying machine learning techniques in monitoring and detecting anomalies in membrane cell electrolyzers at R2

In this project we aim to develop a computer software system that is capable of predicting anomalies in membrane cell electrolyzers before they arise. It will closely monitor the electrolyzers’ operating condition and identify the hints that suggest that a failure is coming down the line. We will then notify the plant operators, so they can plan the preventive replacement of the soon-to-break equipment without causing damages. This system will be part of the services offered by the partner organization and will help them maintain their leadership as market experts and innovators.

Faculty Supervisor:

Soumaya Yacout

Student:

Daniel Buades Marcos

Partner:

R2 Financial Technologies

Discipline:

Engineering - other

Sector:

Manufacturing

University:

École Polytechnique de Montréal

Program:

Accelerate

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