I have a strong understanding of ATR Concepts—Activity, Time, and Resources—which form the foundation of project management. I recognize the importance of delivering project scope within the allocated budget and time, while maintaining the desired quality, using the assigned resources such as staff and tools. To enhance efficiency and minimize errors, I have consistently leveraged automation to reduce the time taken for certain tasks when compared to traditional workflows.

For instance, during the Østlig Ringvej (Eastern Ring Road) Concept Design Project in Denmark, the BIM deliverables required the inclusion of specific parameters known as IFC Property Sets, as outlined in the project's BIM Execution Plan (BEP) and asset referencing systems. These Property Sets included four major groups—Identity Data, Asset Referencing System Data, LCA Data, and Geometry Data—with a mix of mandatory and obligatory parameters. While mandatory parameters required valid values for all element types, obligatory parameters were applicable only in specific cases.

For example, the Sub-material Ratio parameter, which denotes the reinforcement ratio for structural concrete elements, is measured in kg/m³. However, this parameter was not applicable to ballast concrete, which merely acts as a fill between the road pavement’s soffit and the tunnel bottom slab’s top face. Validating these parameters traditionally using model authoring software such as Revit, Civil 3D, and OpenRoads Designer was a time-consuming task, requiring model-by-model checks that did not always generate a standardized or easily comparable output without relying on external tools or intermediary steps.

To address this inefficiency, I developed a Python script that leveraged Artificial Intelligence (AI) to analyze the IFC Exports of BIM models and extract the Property Set parameters as individual CSV files. The script then appended all these CSV files and created a consolidated Excel Spreadsheet that allowed for easy analysis. I added custom logic to compare individual and concatenated parameters (combinations of multiple parameters), highlighting any discrepancies in red whenever the parameter values failed to comply with predefined regular expressions. This enabled users to quickly identify issues with the model’s parameter values.

I further enhanced the functionality by allowing users to provide a list of parameters to include in the checks, making the tool adaptable for different disciplines and projects with varying parameter validation requirements. Recognizing that some of my colleagues were less tech-savvy and did not have Python or IDEs such as Visual Studio Code installed on their workstations, I created a GUI (Graphical User Interface) version of the Python script. This standalone application, built using openly available libraries such as NumPy, IfcOpenShell, tkinter, OpenPyXL, and CSV, allowed my colleagues to run the tool with ease, without requiring any coding knowledge or setup.

This initiative demonstrated my commercial awareness by effectively reducing manual effort, minimizing errors, and enhancing the profitability of the project by harnessing automation. By recognizing time as a limited and essential resource, I developed solutions that not only improved project efficiency but also ensured the consistent quality of deliverables. Through this effort, I reinforced my ability to apply innovative technologies to enhance project outcomes and support my team in achieving excellence.