Caetano, I.; Pinto, D.; Amândio, M.; Silva, J.; Sanhudo, L.; Azenha, M.; El Sibaii, M.; Granja, J.; Patrício, H.; Ganhão, F. and Poças Martins, J. (2026) Algorithmic workflow for digitising inspection data in railway tunnel maintenance. Built Environment Project and Asset Management, pp. 1-18. ISSN 2044-124X
Abstract
Purpose – This study addresses the lack of structured, data-driven approaches to infrastructure asset management, demonstrating how integrating building information modelling (BIM) and digital twin methodologies can enhance the maintenance and lifecycle management of railway tunnels. Design/methodology/approach – A structured data-to-BIM workflow was co-developed with Infraestruturas de Portugal (IP), using inspection and monitoring data from 79 railway tunnels. The workflow includes automated data acquisition and systematisation, algorithmic generation of structured, data-rich BIM models, and a centralised digital twin platform for lifecycle monitoring. Findings – Implementation enabled real-time data manipulation, predictive maintenance and improved decision-making. Key outputs include standardised data exchange protocols, product data templates, BIM object classes for tunnel components and digital twinning algorithms. Benefits observed include improved collaboration, automatic anomaly detection and enhanced visualisation of tunnel condition. Research limitations/implications – Further research is needed to improve the algorithm's performance, minimise manual interventions and validate the workflow's scalability across diverse asset typologies and operational contexts. Originality/value – The research presents a framework for integrating digital twins into infrastructure asset management, demonstrating the operational value of computational methods in transforming conventional maintenance and lifecycle management workflows and supporting data-driven decision-making.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | built environment digitalisation; data interoperability; data-to-BIM methodology; infrastructure asset management; predictive maintenance; tunnel digital twinning |
| Index terms: | data exchange, monitoring, digital twin, lifecycle, data-driven decision-making, Portugal, collaboration, data acquisition, workflow, methodology, real-time data, digitalization, predictive maintenance, built environment, infrastructure asset management, decision-making, visualization, tunnel, platform, data interoperability, implementation, building information modelling, inspection |
| Subjects: | digital engineering, control systems, data exchange, research methods, digital design, management, contractual arrangements, project delivery, information systems, decision analysis, design practice, asset management, infrastructure and transport systems, quality assurance, maintenance engineering, data collection methods, data management, Geography, digital technology |
| Topics: | Research Practice, Site Management, Procurement, Project Management, Organizational Design, Engineering Principles, Risk Management, Quality Management, Design Practice, Urban Studies, Geographical Context, Digital Applications, Business Strategy |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here