Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance

N. A. Stevens; M. Lydon; S. E. Taylor; G. Hamill; A. H. Marshall; K. E.J. Campbell; T. Neeson; A. O'Connor

doi:10.1201/9780429279119-569

Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance

N. A. Stevens, M. Lydon, S. E. Taylor, G. Hamill, A. H. Marshall, K. E.J. Campbell, T. Neeson, A. O'Connor

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In recent years there has been a rapid deterioration in the condition of bridges in the UK. In one year 2017-2018 the cost of bridge maintenance backlog increased by 34% to £6.7bn. Climate change and increasing traffic have undoubtedly contributed to this rapid growth. However, consultation with bridge owners has confirmed outdated management and maintenance methods are also attributing to the deterioration of our road networks. This research looks specifically at the development of a new bridge management system (BMS) using the Northern Ireland (NI) road network as a research platform. The proposed BMS will adopt a multi-objective decision making at the object and network level, incorporating bridge performance goals influenced by technical, environmental, economic and social factors. This paper will outline the initial investigations carried out to develop the data strategy for the development of the BMS and present some preliminary analysis of the data in the current BMS.

Original language	English
Title of host publication	Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020
Editors	Hiroshi Yokota, Dan M. Frangopol
Publisher	CRC Press/Balkema
Pages	4151-4158
Number of pages	8
ISBN (Electronic)	9780367232788
DOIs	https://doi.org/10.1201/9780429279119-569
Publication status	Published - Apr 2021
Event	10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020 - Sapporo, Japan Duration: 11 Apr 2021 → 15 Apr 2021

Publication series

Name	Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020

Conference

Conference	10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020
Country/Territory	Japan
City	Sapporo
Period	11/04/2021 → 15/04/2021

Bibliographical note

Funding Information:
The authors would like to acknowledge the support received by the Royal Academy of Engineering under the Research Fellowship scheme. The Department for Infrastructure are gratefully acknowledged for their financial support and the provision of access to the complete bridge management records and permitting the analysis and findings to be used in this paper.

Publisher Copyright:
© 2021 Taylor & Francis Group, London

ASJC Scopus subject areas

Civil and Structural Engineering
Safety, Risk, Reliability and Quality

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1201/9780429279119-569

Cite this

Stevens, N. A., Lydon, M., Taylor, S. E., Hamill, G., Marshall, A. H., Campbell, K. E. J., Neeson, T., & O'Connor, A. (2021). Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance. In H. Yokota, & D. M. Frangopol (Eds.), Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020 (pp. 4151-4158). (Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020). CRC Press/Balkema. https://doi.org/10.1201/9780429279119-569

Stevens, N. A. ; Lydon, M. ; Taylor, S. E. et al. / Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020. editor / Hiroshi Yokota ; Dan M. Frangopol. CRC Press/Balkema, 2021. pp. 4151-4158 (Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020).

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title = "Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance",

abstract = "In recent years there has been a rapid deterioration in the condition of bridges in the UK. In one year 2017-2018 the cost of bridge maintenance backlog increased by 34% to £6.7bn. Climate change and increasing traffic have undoubtedly contributed to this rapid growth. However, consultation with bridge owners has confirmed outdated management and maintenance methods are also attributing to the deterioration of our road networks. This research looks specifically at the development of a new bridge management system (BMS) using the Northern Ireland (NI) road network as a research platform. The proposed BMS will adopt a multi-objective decision making at the object and network level, incorporating bridge performance goals influenced by technical, environmental, economic and social factors. This paper will outline the initial investigations carried out to develop the data strategy for the development of the BMS and present some preliminary analysis of the data in the current BMS.",

author = "Stevens, {N. A.} and M. Lydon and Taylor, {S. E.} and G. Hamill and Marshall, {A. H.} and Campbell, {K. E.J.} and T. Neeson and A. O'Connor",

note = "Funding Information: The authors would like to acknowledge the support received by the Royal Academy of Engineering under the Research Fellowship scheme. The Department for Infrastructure are gratefully acknowledged for their financial support and the provision of access to the complete bridge management records and permitting the analysis and findings to be used in this paper. Publisher Copyright: {\textcopyright} 2021 Taylor & Francis Group, London; 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020 ; Conference date: 11-04-2021 Through 15-04-2021",

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Stevens, NA , Lydon, M , Taylor, SE , Hamill, G , Marshall, AH , Campbell, KEJ , Neeson, T & O'Connor, A 2021, Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance. in H Yokota & DM Frangopol (eds), Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020, CRC Press/Balkema, pp. 4151-4158, 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020, Sapporo, Japan, 11/04/2021. https://doi.org/10.1201/9780429279119-569

Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance. / Stevens, N. A.; Lydon, M.; Taylor, S. E. et al.

Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020. ed. / Hiroshi Yokota; Dan M. Frangopol. CRC Press/Balkema, 2021. p. 4151-4158 (Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Campbell, K. E.J.

AU - Neeson, T.

AU - O'Connor, A.

N1 - Funding Information: The authors would like to acknowledge the support received by the Royal Academy of Engineering under the Research Fellowship scheme. The Department for Infrastructure are gratefully acknowledged for their financial support and the provision of access to the complete bridge management records and permitting the analysis and findings to be used in this paper. Publisher Copyright: © 2021 Taylor & Francis Group, London

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Stevens NA , Lydon M , Taylor SE , Hamill G , Marshall AH , Campbell KEJ et al. Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance. In Yokota H, Frangopol DM, editors, Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020. CRC Press/Balkema. 2021. p. 4151-4158. (Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020). doi: 10.1201/9780429279119-569

Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

UN SDGs

Access to Document

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