Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

This Engage project aims to establish a new collaboration between Acerta Analytics Solutions and the researchx000D
team supported by Dr. Michael Fowler. The two parties have not engaged before in any form of collaborationx000D
to date. Advances in computing technology enable new forms of data analysis. Acerta offers analyticsx000D
solutions to identify warranty issues of manufactured goods at the end of life. This means that Acerta'sx000D
algorithms analyze data collected from the manufactured good before it leaves the factory and based on the datax000D
determines whether the good should be shipped to the customer or whether it will likely have a warranty issuex000D
and thus should be inspected in the factory prior to shipping. Currently, Acerta is applied to products usingx000D
gearboxes, engines, and bearings in vehicles. Acerta is extending its product line to also offer analytics forx000D
batteries. To extend the product line to batteries, Acerta needs to tune its algorithms and products to providex000D
meaningful estimates of the quality of a battery system at the end of life. This requires answering the followingx000D
questions (among others): (1) what is the state of the charge, (2) what is the health of the cells, and (3) what isx000D
the expected state of degradation over the next years. Since Acerta uses machine learning mixed with domainx000D
knowledge, it needs domain expertise on feature engineering (i.e., determining what sensor values should bex000D
provided) and feature processing (i.e., use features to extract information gain).