Goodall_1-s2.0-S1755581720300791-main.pdf (3.13 MB)
Download file

The potential of industry 4.0 cyber physical system to improve quality assurance: An automotive case study for wash monitoring of returnable transit items

Download (3.13 MB)
journal contribution
posted on 04.03.2021, 15:39 authored by Aaron Neal, Richard Sharpe, Kate Van-Lopik, James Tribe, Paul GoodallPaul Goodall, Heinz Lugo-Sanudo, Diana Segura-VelandiaDiana Segura-Velandia, Paul ConwayPaul Conway, Lisa JacksonLisa Jackson, Thomas Jackson, Andrew WestAndrew West
The aim of the research outlined in this paper is to demonstrate the implementation of a Cyber-Physical System (CPS) within the Automotive Industry for the monitoring and control of Returnable Transit Items (RTIs) toward improved quality assurance and process compliance. The socio-technical issues encountered during the realworld implementation are discussed to inform future design Automotive RTI’s are utilised in the transportation of both components and subsequently assembled products at the beginning and end of life stages. The implemented system utilises passive Ultra-High Frequency (UHF) Radio Frequency IDentification (RFID) tags for the identification of metal RTIs via associated plastic separators, whilst a distributed network of RFID portals was integrated within the RTI working environment to capture and characterise their movements. The requirements, design process and resulting architecture are presented alongside the results and lessons learnt from an implementation within the automotive industry. Through the integration of business processes, analytics and tacit domain knowledge, a real-time model of the state of RTIs was developed to support decision making by a range of stakeholders. This research contributes to the knowledge of CPSs requirements identification, design, deployment and the challenges faced within real world asset monitoring and traceability within the automotive industry. Areas for future research to support the next generation of RTI traceability, monitoring and control systems are presented.

Funding

Adaptive Informatics for Intelligent Manufacturing (AI2M)

Engineering and Physical Sciences Research Council

Find out more...

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

CIRP Journal of Manufacturing Science and Technology

Volume

32

Pages

461-475

Publisher

Elsevier

Version

VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

10/07/2020

Publication date

2021-02-16

Copyright date

2021

ISSN

1755-5817

Language

en

Depositor

Mrs Kate Van Lopik. Deposit date: 11 December 2020