TY - JOUR
T1 - IoT for predictive assets monitoring and maintenance
T2 - An implementation strategy for the UK rail industry
AU - Gbadamosi, Abdul-Quayyum
AU - Oyedele, Lukumon O.
AU - Delgado, Juan Manuel Davila
AU - Kusimo, Habeeb
AU - Akanbi, Lukman
AU - Olawale, Oladimeji
AU - Muhammed-yakubu, Naimah
N1 - Funding information: This work has been funded by the Department for Transport (DfT) fund through the Innovate UK, Project number 104242.
PY - 2021/2/1
Y1 - 2021/2/1
N2 - 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.
AB - 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.
KW - Augmented reality
KW - Internet of things
KW - Predictive maintenance
KW - Rail assets
KW - Remote inspection
UR - http://www.scopus.com/inward/record.url?scp=85097719595&partnerID=8YFLogxK
U2 - 10.1016/j.autcon.2020.103486
DO - 10.1016/j.autcon.2020.103486
M3 - Article
AN - SCOPUS:85097719595
SN - 0926-5805
VL - 122
JO - Automation in Construction
JF - Automation in Construction
M1 - 103486
ER -
