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Impact of Autonomous Solutions on Electric Earthmoving Design Using Machine Learning: Case Study

Published online by Cambridge University Press:  26 May 2022

A. Abdelmassih ,
R. Faddoul  and
F. Geara
A. Abdelmassih*
Affiliation:
Ecole Superieur d’Ingenieurs de Beyrouth (ESIB), USJ, Beirut, Lebanon
R. Faddoul
Affiliation:
Ecole Superieur d’Ingenieurs de Beyrouth (ESIB), USJ, Beirut, Lebanon
F. Geara
Affiliation:
Ecole Superieur d’Ingenieurs de Beyrouth (ESIB), USJ, Beirut, Lebanon
*
anthony.abdelmassih@net.usj.edu.lb

Abstract

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The increased development in automated driving systems (ADS) has opened up significant opportunities to revolutionize mobility and to set the path for technologies, such as electrification. The proposed methodology is a simulation model backed by a multi-objective optimization algorithm. This research investigates the adoption of future technologies in earthmoving application and explores its implications on the design of future machine concepts in terms of equipment size. The shift from “elephant to ants” in the machine selection, resulted in improved feasibility.

Keywords

conceptual designproduct developmentautonomous vehicleselectromobilitymachine learning
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1491 - 1500
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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