Digitisation in the construction industry continues to advance and, together with the increasing dissemination and further development of hardware and software, is steadily opening up further opportunities for innovative ways of working. Building Information Modelling (BIM) is currently becoming the standard for new construction but has not yet been optimised for use in existing buildings. Therefore, the Institute of Building Materials Research (ibac) is researching new methods and possibilities for BIM-based building preservation. In this paper, the automated creation and analysis of point clouds as well as the implementation of further information from in situ diagnosis and monitoring systems in BIM-Models are presented. On a practical example, the different steps of a subsequent digitisation of an existing building are demonstrated considering new possibilities as autonomous robots and the intelligent utilisation of sensors and diagnostics tools. The goal is a decision support tool, which is independent from proprietary software, adaptive to different types of buildings and open for various interfaces. Current results show that quantifying point clouds and making BIM-models usable beyond the planning and execution phase for new buildings are essential steps for the digitisation of building maintenance. The proposed digital workflow holds great potential for effective building diagnoses and efficient service life management.
The durability of concrete structures is essential for reliable infrastructure. Although many deterioration models are available, they are rarely applied in situ. For existing structures in need of repair or durability assessment, this is also the case for Building Information Modeling (BIM). However, both BIM and durability modeling hold great potential to both minimize expended resources and maximize the reliability of structures. At the Institute for Building Materials Research (ibac) at RWTH Aachen University, a novel approach to the calibration of deterioration models using Bayesian inference iteratively in a BIM model enriched with machine-readable diagnosis data to achieve a predictive decision support tool is being developed. This paper demonstrates the digital workflow, validates the proposed approach, and expresses the added value for the planning of repair measures.
Building Information Modeling (BIM) is increasingly establishing a model-based work process in the construction industry. Though it can be considered the standard for the planning of new buildings, the use cases for existing buildings are still limited. Nonetheless, BIM models provide promising possibilities which are increasingly being researched in different fields of application. At the Institute for Building Materials Research (ibac) at RWTH Aachen University, a novel approach for maintenance and repair of reinforced concrete is being developed, using BIM models enriched with machine-readable diagnosis data. This paper proposes a digital workflow and highlights the added value for planning repair measures. Using BIM in maintenance and repair can accelerate the planning process and decrease the required material consumption for the execution.
Digitalization in the construction industry continues to advance and, together with the increasing dissemination and further development of hardware and software, is steadily opening up further opportunities for innovative ways of working. Building Information Modeling (BIM) is currently becoming the standard for new construction, but has not yet been optimized for use in existing buildings. Therefore, the Institute of Building Materials Research at RWTH Aachen University (ibac) is researching new methods and possibilities for BIM-based building preservation. In this paper, the vision of digitalized building preservation, the state of research so far and the planned further steps are presented. It highlights what information needs to be available in the BIM model for digitalized maintenance planning, and shows how this data can be implemented in a way that is machine-readable and suitable for automated evaluation. The goal is the digital availability and linking of all inspection results, so that various operations such as lifetime prognoses or calculation of concrete removal can be performed in the BIM model. The findings to date show that making BIM models usable beyond the planning and execution phase is an essential step for the digitalization of building maintenance and holds great potential for effective building diagnoses and efficient service life management.
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