The MaSe decision support system: Development of an integrated information system for the selection of environmentally preferable materials and products in the building process

New building regulations and increased focus on building related environmental burdens have created a need for guidance to design more sustainable buildings. The main objective in this thesis is to develop a decision support system, to guide decision-makers to a better selection of building materials and products, based on environmental prioritisation. The system is focused on building materials and products, but the structure of the system can be adapted to other types of decision problems.

Key decision makers with respect to material and product selection are the client, the architects, the technical consultants, and the contractors when they decide on specific brands. The user of the MaSe system first identifies the materials acceptable in the specific project, based on the technical requirements. These pre-selected materials are then scored and ranked through the procedures in the MaSe system. The alternative ranking is then the basis for the selection of construction elements, materials or products.

The MaSe system includes environmental aspects under the headlines Resources, Ecology and Human health. The results from each sub area are weighted into one index, referred to as the Environmental index. Each material is characterised with this index and a judgement. All costs related to the production, use and disposal of a material are included in the MaSe system evaluation.

The MaSe system is suited for use in the relevant phases of the building process. It is possible to use the system on different levels and with different input, from client priorities to details of the different products studied by the contractor. Economy is included in the system, and this one important aspect that separates the MaSe system from many of the existing systems. Many different products and materials can be handled within the system as long as the functional unit (FU) of the data are carefully defined.