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

• Published in: Automation in construction 2021-02, Vol.122, p.103486, Article 103486
• Main Authors: Gbadamosi, Abdul-Quayyum, Oyedele, Lukumon O., Delgado, Juan Manuel Davila, Kusimo, Habeeb, Akanbi, Lukman, Olawale, Oladimeji, Muhammed-yakubu, Naimah
• Format: Article
• Language: English
• Subjects: Audio data; Augmented reality; Concept mapping; Condition monitoring; Data collection; Data management; Inspection; Internet of Things; Predictive maintenance; Rail assets; Remote inspection; Remote sensors
• ISSN: 0926-5805; 1872-7891
• DOI: 10.1016/j.autcon.2020.103486

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. •Problem areas in rail asset management were assessed.•Opportunities and technological enablers for IoT were discussed by experts.•Core priority areas for IoT implementation in rail asset maintenance were identified.•An implementation strategy was proposed.•Potential practical implications were discussed.