The construction industry's ongoing shift towards digitalization is leading to a higher adoption of Building Information Modeling (BIM) in various construction projects, including those related to infrastructure. The connection between predictive maintenance data, which includes the condition state and planned interventions for these railway assets, and their integration into digital workflows is explored. Firstly, the establishment of digital data integration at the asset level is addressed. Emphasis is placed on exploring data representation through visualization to facilitate seamless incorporation of BIM into the workflows of bridge asset managers. Furthermore, the creation of a unified data source at the network level is provided. This involves the consolidation of data from bridge and track assets within a single view, with a specific focus on identifying synergies and associations. The final aspect of this thesis centers on enhancing the utilization of digital models in subsequent project phases, particularly during the construction phase. It places a special emphasis on the utilization of 4D BIM models, discussing various strategies while addressing concerns related to data exchange. In summary, the integration of digital workflows, with a specific focus on BIM, has the potential to significantly enhance the decision-making processes of asset managers.
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The construction industry's ongoing shift towards digitalization is leading to a higher adoption of Building Information Modeling (BIM) in various construction projects, including those related to infrastructure. The connection between predictive maintenance data, which includes the condition state and planned interventions for these railway assets, and their integration into digital workflows is explored. Firstly, the establishment of digital data integration at the asset level is addressed. Em...
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