Search Results (5)

Despite the operational phase being the most cost-intensive in a building’s lifecycle, Facility Management (FM) resource optimization continues to face challenges due to fragmented and low-structured data. Building Information Modeling (BIM) offers a centralized data environment, but interoperability gaps persist between design-oriented BIM models and operational Computerized Maintenance Management Systems (CMMSs). This paper presents a scalable, standards-based methodology for BIM-CMMS integration based on the extension of Industry Foundation Classes (IFCs) and the enrichment of FM data. The proposed Python-based application leverages the open-source IfcOpenShell library to inject custom, FM-specific Property Sets (Psets), including asset condition, criticality, and maintenance schedules, directly into IFC entities. The approach transforms standard IFC files into data-rich Asset Information Models (AIMs) without relying on proprietary middleware. The methodology was validated through two residential building case studies. IFC models were successfully checked through the buildingSMART validation service, providing full interoperability across multiple IFC-compatible platforms. Integration with OpenMAINT automatically generates a complete asset database, minimizing manual data entry and reducing inconsistencies. The results confirm the feasibility of a repeatable open-standard workflow. The future development is the definition of a functional/cognitive DT, with the scope of improving the lifecycle BIM model quality and enhancing the efficiency of facility operations. Full article

To address the practical needs for data sharing and exchange in the bridge engineering domain, this study creatively fills the definitional gap of IFC entities for steel bridges. In response to the deficiencies arising from the absence of domain-layer entity information in the IFC standard architecture, an extension strategy is proposed that integrates new entity definitions with customized property sets to enrich and formalize the steel bridge domain. On this basis, a foundational data framework for steel bridge structures is established, encompassing extended definitions for spatial structural units, assemblies, components, and parts. The customized property sets further expand the entity attributes related to the design and fabrication stages, thereby developing an IFC-based manufacturing information model for steel bridges. Furthermore, a parametric BIM modeling approach for steel bridges is introduced on the 3DEXPERIENCE platform, employing IfcOpenShell to inject semantic information and export models in standard IFC format. The proposed IFC extension and modeling methodology is demonstrated through its application to the Chengdu Q7 North Pedestrian Bridge project, confirming its practical value in enhancing the completeness and transferability of steel bridge BIM model information from the design phase through to fabrication. Full article

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. Full article

Building information modelling (BIM) is an appreciated technology in the field of architecture and construction management. Collaboration of information in BIM has not been fully utilized in the structural engineering stream as many engineers keep on working with previous prevailing design approaches. Failure to adequately facilitate automation in design could lead to structural defects, construction rework, or even structural clashes, with major financial implications. Given the inherent complexity of large-scale construction projects, the ‘manual design and detailing’ of structure is a challenging task and prone to human errors. Against this backdrop, this study developed a 4D building information management approach to facilitate automated structural models for professionals designing all the elements required in reinforced concrete (RC) structures like slabs, beams, and columns. The main contribution of this study is to obtain structural models directly from architecture models automatically, which reduces effort and possible errors in the previous prevailing approaches. The framework enables execution of all the model design works automatically through coding. This is achieved by executing a script which is beneficial for integrated project delivery (IPD). The 3D structural model in BIM software presented in this study extracts and transfers the geometrical data and links these data in Industry Foundation Classes (IFC) files using integration facilitated by Python 3.6 and IFCopenshell. The developed automated programme framework offers a cost-effective and accurate methodology to address the limitations and inefficiencies of traditional methods of structural modelling, which had been carried out manually. The authors have developed a novel tool to extract structural models from architectural models without proprietary software, greatly benefiting BIM managers by enhancing 3D BIM models. This advancement toward Open BIM, crucial for the architecture, engineering, and construction (AEC) industry’s future, is accessible to educators and beginners and highlights BIM’s effectiveness in improving structural analysis and productivity. The core finding of this study is to generate a structural model from an architecture model by automating the script with Python integration of IFC and IFCopenshell. The merits of the developed framework are reduced clashes, more economical structural modelling, and fully automated smart work as functions of the IPD. Full article

Building information modelling (BIM) is a revolution in the architectural, engineering, and construction (AEC) industry. In the AEC industry, several interesting innovations are being introduced every day. Most of the code compliance work, which is time-consuming and quite multifaceted, is now performed manually. The number of unwanted errors is increasing, and any suspension of the project is led by the structural code-checking system, and is a tiresome process. Subsequently, the BIM-based model is presented to automate the structural stability design of buildings. The Industry Foundation Classes (IFC) specification is introduced in this work, and is used to automate the building design processes to achieve design correctness and efficiency. The IFC-based interoperability framework is presented to automate the design of structural elements of RC buildings. Consequently, a deep multi-perception-based generalized adaptive framework (DMPBGAF) is presented for the automated code compliance checking process. The concepts and relationships in the building code were automatically matched to their equivalent concepts. A building code was checked against the Indian seismic code IS 13920, and when shear wall data were presented in this IFC file, it exchanged the data with the custom engine. It is possible to eliminate the unwanted issues based on the automated code compliance system with BIM. This goal can be accomplished by using a coding rule-based engine to compile the BIM model and store the design code of the specific country with its clauses. After generating the Python file to code all of the prepared checks, the python file in the form of functions was obtained from the IfcOpenShell library. Finally, a rule engine was developed for interpretation of the checks; the three model IFC files were tested on this, and it gave satisfactory results. The FreeCAD software was employed in this research for the IFC-based BIM model to automate the design. The shear wall data were presented in the first IFC model; all of the code checks were passed based on this modelled design, and when given to the rule engine, it gave a 100% compliance report. Insufficiently reinforced shear wall data contained in the other two IFC files were purposely created to fail some of the code checks. This method significantly reduces the time by eliminating the duplication of efforts. From the viewpoint of accuracy and reliability, the proposed method is more accurate and results in enhanced reliability as compared to manual design methods. Full article