Monitoring of blind rivets installations: contributions from the manufacturing chain and time-series imaging

Date

2025-10-01

Director

Publisher

Elsevier
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

  • European Commission/Horizon 2020 Framework Programme/958303/ openaire
Impacto
OpenAlexGoogle Scholar
cited by count

Abstract

Fastening is a crucial operation in the aircraft manufacturing cycle, and the demand for automated solutions has grown in recent years. Blind rivets are particularly suitable for automation due to their ease of use. However, fastening with blind rivets requires indirect evaluation of the formed head for in-line quality monitoring. This study presents two approaches to address this problem. Firstly, an analysis of the drilling-riveting chain assesses the impact of the previous operation on riveting outcomes. Secondly, time-dependent signals from the riveting process are coded into images and analysed using deep learning techniques. Despite some limitations, both methods for monitoring blind riveting have demonstrated high precision and accuracy values above 0.9, with 1 indicating perfect precision or accuracy, suggesting that they can reliably predict the quality of rivet installations.

Description

Keywords

Blind riveting, Manufacturing chain analysis, Quality monitoring, Time-series imaging

Department

Ingeniería / Ingeniaritza

Faculty/School

Degree

Doctorate program

item.page.cita

Penalva, M., Gil Del Val, A., Martín, A., Villanueva, P., Uralde, V., Veiga, F. (2025). Monitoring of blind rivets installations: contributions from the manufacturing chain and time-series imaging. Measurement: Journal of the International Measurement Confederation, 254. https://doi.org/10.1016/j.measurement.2025.117950.

item.page.rights

© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license.

Licencia

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