A simulation of an end-of-life reverse supply chain for electric vehicle batteries

Melissa Venegas, Andrew Greasley*, Aristides Matopoulos

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication

Abstract

The purpose of this study is to investigate the operation of an integrated end-of-life supply chain network in which authorised treatment facilities (ATFs), remanufacturers, and recyclers offer to Electric Vehicle (EV) manufacturers the end of life (EOL) management of batteries within the UK. A simulation model has been constructed in order to measure the process efficiency, labour costs and transport costs of this reverse supply chain network for different resource (capacity) configurations. Although current demand for the management of the end-of-life (EOL) for the batteries is low there is a prediction of a rapid increase in demand as Electric Vehicle sales increase and the EV batteries within these vehicles reach their end of life. It is intended that the simulation will provide an indication of the potential capacity requirements through the supply chain that are required to deal with this future demand.

Original languageEnglish
Title of host publicationProceedings of the 33rd European Modeling & Simulation Symposium, EMSS 2021
EditorsMichael Affenzeller, Agostino G. Bruzzone, Emilio Jimenez, Francesco Longo, Antonella Petrillo
Pages315-319
ISBN (Electronic)9788885741577
DOIs
Publication statusPublished - 17 Sept 2021
Event33rd European Modeling and Simulation Symposium -
Duration: 15 Sept 202117 Sept 2021

Publication series

NameThe European Modeling and Simulation Symposium
ISSN (Electronic)2724-0029

Conference

Conference33rd European Modeling and Simulation Symposium
Period15/09/2117/09/21

Bibliographical note

Copyright © 2021 The Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords

  • discrete-event simulation
  • electric vehicle batteries
  • reverse supply chain

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