At the end of a building’s lifecycle, there are several limitations to the decision-making process (DMP). There is a lack of data available from the building’s history, the difficulty in assessing the condition of a building and the variety of stakeholders’ needs that have to be satisfied. The purpose of this paper is to answer the question: how would end-of-life (EOL) DMP change when buildings will have been digitally built? The answer will be illustrated through a conceptual framework.
A qualitative analysis of the existing literature has been performed to identify the elements within building information modelling (BIM) and advanced digital technologies that could be of support to the DMP. The findings have been collected and summarised in a conceptual framework that has been validated and enhanced through online interviews with industry experts.
The enhanced framework has identified that BIM technology would bring the benefit of providing the initial digital data source, from which machine learning and data analytics would then extract the relevant data needed to measure accurately the criteria during the analysis of the EOL options put on the table.
The findings of this research could contribute to developing the software modules making the bridge between BIM and machine learning technologies, to implement them in the EOL DMP.
