CT3596- Directed Research Projects

Faculty: Jyoti Trivedi

Construction schedule Planning has a key role for construction management as an intermediary between master schedules and site production. Its effective implementation can improve construction management and production control for a specific time period, while considering site performance, work sequencing, and matching tasks to resources. Complex projects contain many interrelated work performed by many different trades and resources, and can potentially have many design changes during construction. Building Information Models (BIM) have potential for improving look-ahead planning processes by relating construction information to the building model, but it is hard to structure and use many disparate forms of information for look-ahead planning. In this study, we present a generic information management approach for aggregating data necessary for visualisation, 4D look-ahead planning and 5D cost assessment using BIM. This includes an information management approach for BIM entities, tasks and work sequence for scopes of work, available resource data, cost data and site progress information integrated with BIM. The necessary information is integrated in a unified platform ready for look-ahead planning. We present a building test case to demonstrate the approach. As now AI is shaping the future of project management by merging human ingenuity with AI and power BI advancements that are proven to support project success and empower the focus towards value driven project work.Results of this research will help planning participants effectively implement AI based 4D look-ahead planning and forecast cost data considering detailed process, cost, and resource data within a BIM-Power BI dashboard. This will also provide opportunities to automate analysis for look-ahead planning integrated with BIM and resources.