Abstract
Construction industry faces many challenges as socio-economical needs evolve and Building Information Modeling (BIM) disrupts practices. BIM processes and solutions are mainly suited for the design stage of a project and experts are currently working to bridge the gap with the construction stage. Improving on BIM practices could be done by creating a more industrialized way of handling construction operations by learning from other industrial fields. This could help to manage quality, delay, and cost more precisely, while considering new indicators (e.g.: GHG emissions). BIM could be improved by developing a construction stage specific data structure inspired by Product Lifecycle Management (PLM) systems. This requires to dynamically manage data for different stakeholders before and during the operations. This paper presents a conceptual data framework to develop a BIM-based decision support system to plan and manage construction operations. A 4D digital mock-up is gradually enriched to support construction processes studies resulting in a As Planned view of the building. Process engineering work is carried through iterative loops and supported by knowledge-based indicators. A cross-disciplinary workflow allows the use of new production methods (e.g.: off-site modular construction). An As Built view of the mock-up is concurrently created as operations advance and changes occur, feeding back the knowledge-based indicators.
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Blampain, F., Bricogne, M., Eynard, B., Bricogne, C., Pinon, S. (2024). Industrialization of Site Operations Planning and Management: A BIM-Based Decision Support System. In: Danjou, C., Harik, R., Nyffenegger, F., Rivest, L., Bouras, A. (eds) Product Lifecycle Management. Leveraging Digital Twins, Circular Economy, and Knowledge Management for Sustainable Innovation. PLM 2023. IFIP Advances in Information and Communication Technology, vol 701. Springer, Cham. https://doi.org/10.1007/978-3-031-62578-7_24
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