Advancing Smart Construction Through BIM-Enabled Automation in Reinforced Concrete Slab Design

Abstract

Building information modeling (BIM) has proven to be a valuable technology in the fields of architecture, construction management, and maintenance management. However, its full implementation in structural engineering remains unfulfilled due to the persistent use of outdated design methods. Insufficient automation in the design process could lead to structural defects, construction rework, and structural clashes, each of which can have significant financial implications. Given the inherent complexity of large-scale construction projects, manual structural design and detailing are challenging tasks and are prone to human errors. This paper presents a novel BIM framework that leverages BIM, Industry Foundation Classes (IFC), Python scripting, the IfcOpenShell library, and Octave programming to automate the design of reinforced concrete (RC) slabs, benefiting design professionals and contractors by integrating automated processes into project workflows. The framework achieved a 40% reduction in design time and a 25% decrease in human errors, as demonstrated through case studies. In this study, a 3D structural model in BIM software is firstly created, extracting slab geometrical data that are linked to Microsoft (MS) Excel/.csv and Octave spreadsheets via Python and IfcOpenShell. Midspan and end span moment coefficients and floor perimeter data following Indian standards are then gathered in Octave, and this information is further processed with Python scripts. Octave programming is used to determine the most accurate, reliable, and economical design for the slab and its detailing. This design information is then pushed back to BIM software via FreeCAD using Python coding, which can be used to develop bar bending scheduling and 2D drawings of the reinforcement details. The proposed framework is validated through case studies, demonstrating its effectiveness in reducing design time, minimizing human errors, and improving overall project efficiency. The core finding of this research is an automated approach that offers a cost-effective and accurate solution to the limitations of traditional RC slab design, addressing structural errors and reducing rework through seamless BIM integration. This research presents a novel contribution to the integration of structural design, construction processes, and operational aspects within BIM. The findings highlight the potential for further advancements in BIM adoption, particularly in addressing the lag in structural engineering applications compared to architecture.