Critical review of data-driven decision-making in bridge operation and maintenance

Abstract

Bridges are critical infrastructure, and effective operation and maintenance (O&M) is essential for ensuring the good condition of bridges. Owing to the increasing complexity of modern bridges and the availability of information technologies (e.g. sensors, laser scanners, and ultrasonic radar) for the collection of massive data, bridge O&M and decision-making gradually shift toward a data-driven manner. However, both the bridge industry and the academia still do not have a common understanding of the latest progress, challenges, and trends of data-driven bridge O&M decision-making. Thus, through a critical review of 485 articles, this paper investigates current data-driven bridge O&M decision-making in detail, including mainstream data types, issues related to data management, and typical application areas using these data. Challenges to implement data-driven bridge O&M decision-making are identified, such as lack of standard data needs, lack of data integration, and lack of standard procedures. Future research opportunities to address the challenges are proposed. This paper can help bridge O&M teams by identifying suitable data and applications to make informed decisions that align well with their needs meanwhile serve as a basis for future research efforts in this area.

KEYWORDS:

• Data collection
• data-driven bridge maintenance
• data management
• data sharing
• data storage
• decision-making
• structure evaluation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the Australian Research Council (ARC) project, grant number #DP170104613.