| Title: |
Improving the decision-making and planning of future railway bridge interventions through digitalisation |
| Authors: |
Chuo, Steven; id_orcid:0 000-0002-7500-7659; Mehranfar, Hamed; Adey, Bryan T. |
| Source: |
Structure and Infrastructure Engineering |
| Publisher Information: |
Taylor & Francis |
| Publication Year: |
2026 |
| Collection: |
ETH Zürich Research Collection |
| Subject Terms: |
Bridge management; Building information model; Decision-making; Digitalisation; Infrastructure maintenance; Intervention planning; Predictive algorithm |
| Description: |
Railway bridge managers estimate the intervention requirements years in advance, which include their associated costs, required track possession times to execute interventions, and failure risks. They communicate this information to multiple stakeholders involved in the intervention planning process using reports and tables. As it is difficult for stakeholders to process all the information in short periods of time this process can lead to misinterpretations, which in turn can lead to multiple iterations and discussions. With the rise of predictive algorithms and building information models (BIMs) to predict, plan, and manage future interventions, there is now an opportunity to use these tools to improve the efficiency of the planning process. This work presents a methodology to do this, i.e., to demonstrate how predictive algorithms can be connected to BIM to facilitate discussions of the multiple stakeholders involved in the intervention planning process, and how the process can be improved. The methodology is demonstrated on a 25 km railway network in Switzerland consisting of 30 bridges. ; ISSN:1744-8980 ; ISSN:1573-2479 |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/application/pdf |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/wos/001665790200001; https://hdl.handle.net/20.500.11850/793526 |
| DOI: |
10.3929/ethz-c-000793526 |
| Availability: |
https://hdl.handle.net/20.500.11850/793526; https://doi.org/10.3929/ethz-c-000793526 |
| Rights: |
info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ ; Creative Commons Attribution 4.0 International |
| Accession Number: |
edsbas.44152F0B |
| Database: |
BASE |