Identifying Uncertainties Toward Sustainable Projects

Abstract Building Information Modeling (BIM) is an evolutionary idea designed to ensure performance is evaluated continuously over the whole life of a given asset. Over the last decade significant emphasis has been placed on the design and management of construction projects by using the 7 layers, or dimensions (D), of BIM (3D Modeling, 4D Time, 5D Cost, 6D Procurement and 7D Sustainability). Moreover, it has been argued that the 7th dimension (7D) that is related to sustainability could impact the other six dimensions of the BIM concept. Sustainability indicates the relationship between economic, social and environmental considerations. The relative sustainability of any building will in part be dependent on the nature of these three considerations over its whole life. However, economic, social and environmental characteristics are likely to be subject to change over time, the precise nature of which cannot be predicted. Consequently, any such changes can introduce vulnerabilities in terms of performance. Hence, the hypothesis of this research is that the pre-identification of economic, social or environmental uncertainties within a BIM platform could help reduce performance vulnerabilities during the project management life cycle. This necessarily includes consideration of the post-occupancy phase. Therefore this study aims to explore uncertainties within the 7D of BIM that could influence and impact the other six dimensions of BIM and vice versa. The study uses secondary data to establish which social, economic and environmental data have to be mined using advanced techniques and technologies to identify key uncertainties that could help project stakeholders to make early, efficient decisions. In other words, project stakeholders could pre-identify those uncertainties in order to avoid vulnerable results during the project management life cycle (from the design phase to the post-occupancy phase) during the application of BIM philosophies.