Survey of the use of data in UK bridge asset management

• Published in: Proceedings of the Institution of Civil Engineers. Bridge engineering 2020-12, Vol.173 (4), p.1-37
• Main Authors: Bennetts, John, Vardanega, Paul J., Taylor, Colin A., Denton, Steve R.
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Asset management; Bridges; Condition monitoring; Data collection; Inspection; Structural health monitoring
• ISSN: 1478-4637; 1751-7664
• DOI: 10.1680/jbren.18.00050

Considerable amounts of data are collected on the UK's stock of bridges. Much of this data is collected to inform the planning and scope of maintenance activities. This paper reports on the results of a series of semi-structured interviews with 17 individuals involved in UK bridge asset management and data-collection activities to explore how such data is used in practice. A wide spectrum of organisations and industrial sectors was represented in this dataset. Hierarchical process modelling was used to characterise the UK's bridge management system and define the processes and sub-processes involved in the management of bridges. Key quotations are used from the interviews to reveal the state of data collection and use in UK bridge infrastructure from the perspective of those directly involved. The study concludes that there is significant variation within the industry regarding the use of visual inspection data and that formal structural health monitoring remains relatively rare. Furthermore, there is a need to develop a new unifying paradigm that will frame the efficient and effective application of emerging artificial intelligence and data science enabled (i.e. ‘smart’) condition-monitoring techniques to bridge management.