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Last Updated: 10-2020
The ability to exploit knowledge is essential for meeting business objectives, continuous improvement, and avoiding the repetition of past mistakes. However, within the AEC (Architecture, Engineering, and Construction) industry, the ability to learn from past experiences and projects is found difficult to be achieved. A significant number of construction planners are unable to use scheduling data for past projects. As a result, the overall scheduling process is primarily based on intuition and personal experiences, rather than well-founded figures. Closely intertwined is the current lack of systematic feedback towards the planner, which prevents the continuous improvement of the construction schedule. Building Information Modelling (BIM) can become the basis of information and knowledge distribution. When the elements of the BIM model are used as the foundation of creating a construction schedule, a so-called BIM-based schedule can be created.
This study focuses on the capture, storage, analysis, and reuse of BIM-based as-planned and as-built scheduling data for the estimation of task duration. The objective of this research is to develop a system that is reliable, accurate, accessible, and effectively usable for the estimation of task durations. To enable reliable and accurate estimations, this study proposes to enrich task data with information on factors that influence task duration. For this proof of concept, a relational database model is developed in SQL that allows storing BIM-based scheduling data. Subsequently, mainly key queries from different use case perspectives (planners, project managers, and portfolio managers) are tested on a fictitious case project related to the pre-construction phase, construction phase, and post-completion phase. As a result, the developed system enables to store and utilize BIM-based scheduling data to estimate task duration, although mostly at a fundamental database and process level without user interfaces.