A First Approach to a Semantic Process Model for Enabling an Information Flow for Reuse of Building Materials

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Abstract

As climate change intensifies and materials become scarcer, there is increasing pressure on the construction industry to find more sustainable solutions for controlled deconstruction and the recovery of building components as a future source of secondary building products. The technical implementation for a robot-assisted deconstruction process of concrete elements is already being investigated. At present, however, there is no continuous flow of information between the data of existing buildings, from which components are removed, and new buildings, into which recovered components are integrated. For the testing process and the approval of the components for reuse, it is crucial to know where the elements come from, how they have been constructed and in which context they are to be reused afterwards. The establishment of a semantic process model to extend the Building Information Model (BIM) is the basis for connecting the information from the different buildings and intermediate inspection processes to enable the approval of the components. Based on existing achievements, a semantic process model was conceptualised, which enables a linking of the information of the building component along the entire process chain. The process model not only connects the information of the existing building and the new building, but also enables the representation of the intermediate process, for example the testing and transport of the component. It can also be connected with the control system of the cutting robot, hence tool position data can be generated out of the process model. A holistic tracking of the component history, the testing and transport process up to the reinstallation in a new building is feasible.

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Jung, V., Heuer, C., & Brell-Cokcan, S. (2024). A First Approach to a Semantic Process Model for Enabling an Information Flow for Reuse of Building Materials. In Lecture Notes in Civil Engineering (Vol. 390 LNCE, pp. 23–32). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-44021-2_3

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