The advancement of paradigms such as Industry 4.0 and cyber physical systems herald increased productivity and efficiency for manufacturing businesses through increased capture and communication of data, information and knowledge. However, interpreting the raw data captured by sensing devices into useful information for decision making can be challenging as it often contains errors and uncertainty. This paper specifically investigates the challenges of analysing and interpreting data recorded using Radio Frequency IDentification (RFID) portals to monitor the movements of Returnable Transit Items (RTI), such as racks and stillage, within an automotive manufacturing environment. Data was collected over a yearlong pilot study using an RFID portal system installed across two automotive facilities to trace the movement of RTIs between the sites. Based upon the results key sources of errors and uncertainty have been identified and a data management framework is proposed to alleviate these errors.
Funding
The EPSRC Grant award No. EP/K014137/1 supported this work financially
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
ADVANCES IN MANUFACTURING TECHNOLOGY XXX
Volume
3
Pages
343 - 348
Citation
GOODALL, P.A. ...et al., 2016. A data management system for identifying the traceability of returnable transit items using radio frequency identification portals. IN: Goh, Y.M. and Case, K. (eds). Advances in Manufacturing Technology XXX, Proceedings of the 14th International Conference on Manufacturing Research (ICMR 2016), Loughborough University, Loughborough, UK, September 2016, pp. 343 - 348
Publisher
IOS Press
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/
Publication date
2016
Notes
The final publication is available at IOS Press through http://dx.doi.org/10.3233/978-1-61499-668-2-343