Visual Analytics for Tire Engineers

SCHEME: AFR PPP

CALL: 2019

DOMAIN: IS - Information and Communication Technologies

FIRST NAME: Vasile

LAST NAME: CIORNA

INDUSTRY PARTNERSHIP / PPP: Yes

INDUSTRY / PPP PARTNER: University of Bordeaux, Luxembourg Institute of Science and Technology

HOST INSTITUTION: Goodyear

KEYWORDS: Data Visualization, Tire Development, Performance Analysis, Visual Encodings, Model Prediction Analysis, Interpretable Machine Learning

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Submitted Abstract

Tire development is a long, iterative and costly process that requires execution of multiple regulation and performance related measurements in order to achieve the specification. An important amount of data is generated based on these tests.Current research in visual analytics is interested in state-of-the-art data visualizations that allow domain experts to better understand, summarize and create knowledge based on data. In this context, the goals of this projects are: 1) create new, interactive visualizations for highly-multidimensional datasets in the frame of tire development; 2) develop scalable surrogate models for complex predictive models and create interactive visualizations for them; 3) create a scenario builder allowing to test in real time these surrogate models and encapsulating virtual scenarios into a visual analytics story.The 3 goals of the project will result into visual analytics tools that will be used for optimization purposes of the current tire development process.

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