Abstract
Asset management aims at realizing value from assets, meeting stakeholders needs and expectations by balancing financial, environmental, and social costs, risks, quality of service and performance of assets. Asset managers need to know the assets they manage, so that organizational knowledge and decision-making are improved, and the global value generated by the asset portfolio is maximized. Therefore, asset management is a data-intensive activity, and asset managers need tools and processes to efficiently collect, assemble, manage, analyze, and use asset data. In this regard, Industry 4.0-driven approaches, such as the Digital Twin (DT), promise to contribute to asset management decision-making and realize value from asset data. However, organizations that may consider DT application face different interpretations on the concept and varying expectations regarding its potential impacts. Based on the contributions of diverse information sources, this work aims to identify opportunities and challenges arising from its use and discuss them in the context of road and rail infrastructure asset management.
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Acknowledgements
This research was supported by Infraestruturas de Portugal, S.A. and the Shift2Rail Joint Undertaking funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101012456 (IN2TRACK-3). The authors are also grateful for the Foundation for Science and Technology's support through funding UIDB/04625/2020 from the research unit CERIS. Additionally, this work was financially supported by: Base Funding - UIDB/04708/2020 of the CONSTRUCT - Instituto de I&D em Estruturas e Construções - funded by national funds through the FCT/MCTES (PIDDAC).
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Vieira, J., Patrício, H., Poças Martins, J., Gomes Morgado, J., Almeida, N. (2023). The Potential Value of Digital Twin in Rail and Road Infrastructure Asset Management. In: Crespo Márquez, A., Gómez Fernández, J.F., González-Prida Díaz, V., Amadi-Echendu, J. (eds) 16th WCEAM Proceedings. WCEAM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-25448-2_42
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