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Last Updated: 5-2022


When refurbishing office buildings, the decision makers play a key role in the refurbishment
design. Office refurbishments are conducted for numerous reasons, but the general
trend is to improve the buildings energy usage and thus environmental impact. The
refurbishment process itself also has impact on the environment via e.g.: new building
materials, waste, transport, and energy usage and thus, it is required to focus on a sustainable
refurbishment design.
In the refurbishment process there is a lack of insight in the decision makers’ feels and
needs, this insight is required when creating a suitable sustainable refurbishment design.
On the other hand, the quantification of the environmental impact of a refurbishment
design remains difficult since current solutions do not link Building Information Models
(BIM) to Life Cycle Assessment (LCA) data.
This thesis introduces two web-based tools CNET-DA and BEE. CNET-DA allows
designers to gain insight into the feels and needs of decision makers by letting them
indicate their preferences for a set of choice alternatives. CNET-DA has not been implemented
before and therefore also insight is gained in the user experience of using the
developed CNET-DA web-tool. The BIM based Environmental Evaluation (BEE) tool
allows designers to calculate the environmental impact of a refurbishment project expressed
in a costs index. This tool uses a BIM model (IFC file) as input and connects
it to a database with LCA data. The user can modify the material specifications in the
tool and the environmental costs are adjusted in real-time. A graphical representation
(3D view) of the BIM allows for easy component selection.
Both developed tools are implemented in a case study of an ABN-Amro refurbishment
project. Results of the case study showed decision makers not always choose the best
suitable alternative. Furthermore, important decision attributes were identified, and the
environmental impact calculations showed significant environmental savings on evaluated
building components. Experts using the CNET-DA tool would like to see further future
case studies with the decision assistant. In the end, the study contributes to the refurbishment
design and decision-making process in the effort to reduce the environmental
impact of the refurbishment process.

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