Li_Robotic disassembly for increased recovery of SIM from EVs_Jie Li 2017.pdf (5.6 MB)
Download file

Robotic disassembly for increased recovery of strategically important materials from electrical vehicles

Download (5.6 MB)
journal contribution
posted on 16.11.2017, 09:16 by Jie Li, Michael Barwood, Shahin RahimifardShahin Rahimifard
© 2017 Elsevier Ltd. The rapid growth of market share of Electrical Vehicles (EVs) and their increasing amount of electric and electronic components have introduced difficult challenges for future recycling of such vehicles. End of Life Vehicles (ELVs), together with Waste Electric and Electronic Equipment (WEEE), are renowned as an important source of secondary raw materials. In addition, a significant proportion of the hidden value at the End-of-Life (EoL) of the EVs is embedded in the light fractions containing complex material mixtures, i.e. the management of electronic components that has been rarely considered in the scientific literature. The purpose of this paper is to fill this gap through the use of an innovative disassembly approach to identify the profitability of recycling such electronic components. The novel approach, based on the utilisation of a robotic system, disassembles and extracts Strategically Important Materials (SIMs) from EV components, thereby improving the concentration of these materials prior to final recycling and refining processes. This paper presents the challenges in the robotic disassembly of Electrical and Electronic (E & E) components. A case study has also been included to demonstrate that an average 95% of the materials and their associated recovery value could be achieved.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Robotics and Computer-Integrated Manufacturing

Volume

50

Pages

203 - 212

Citation

LI, J., BARWOOD, M. and RAHIMIFARD, S., 2018. Robotic disassembly for increased recovery of strategically important materials from electrical vehicles. Robotics and Computer-Integrated Manufacturing, 50, pp. 203-212.

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

20/09/2017

Publication date

2017-10-04

Notes

This paper was accepted for publication in the journal Robotics and Computer-Integrated Manufacturing and the definitive published version is available at https://doi.org/10.1016/j.rcim.2017.09.013

ISSN

0736-5845

Language

en