IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry

Abdul-Quayyum Gbadamosi, Lukumon O. Oyedele*, Juan Manuel Davila Delgado, Habeeb Kusimo, Lukman Akanbi, Oladimeji Olawale, Naimah Muhammed-yakubu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

With about 100% increase in rail service usage over the last 20 years, it is pertinent that rail infrastructure continues to function at an optimal level to avoid service disruptions, cancellations or delays due to unforeseen asset breakdown. In an endeavour to propose a strategy for the implementation of Internet of Things (IoT) in rail asset maintenance, a qualitative methodology was adopted through a series of focus-group workshops to identify the priority areas and enabling digital technologies for IoT implementation. The methods of data collection included audio recording, note-taking, and concept mapping. The audio records were transcribed and used for thematic analysis, while the concept maps were integrated for conceptual modelling and analysis. This paper presents an implementation strategy for IoT for rail assets maintenance with focus on priority areas such as real-time condition monitoring using IoT sensors, predictive maintenance, remote inspection, and integrated asset data management platform.

Original languageEnglish
Article number103486
JournalAutomation in Construction
Volume122
Early online date4 Dec 2020
DOIs
Publication statusPublished - 1 Feb 2021
Externally publishedYes

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