A Cost-Based Interior Design Decision Support System for Large-Scale Housing Projects

Abstract

We proposed an interior design decision support system that enables clients to participate in the early phases of the interior design for a housing project. This allows them to select objects (e.g., colours, patterns, material) for the interior design based on the unit measure of costs with input from various A/E/C experts. This also allows the interior designer and cost estimator to check the costs accordingly. The proposed system was implemented using the BPH and IDOL. In an example study, interior design objects and default costs were proposed while examining the fixed and variable cost options. This study examined how client decisions made during the early design phases and based on restrictions in the interior design can affect a project. An analysis of the results confirmed that our interior design decision support system leads to client satisfaction with the interior design, while enabling clients to manage project costs by providing a cost baseline. Overall, this increases the accuracy of early estimates made during the project concept phase. Cost and time are both very key indicators for assessing project performance. In the earlier phases of large-scale housing projects, the review of construction costs is important (Kim et al., 2004). It is not appropriate to state that high-cost interiors designs are good and low-cost ones are not. However, making interior designs or design changes without any consideration of the cost is a source of serious problems for the interior designer and other project participants, especially the owner/developer. Moreover, despite considerable information on costs for alternative proposals selected by interior designers, existing procedures have many problems as seen in a review and feedback of these alternatives. To address these problems, we investigated various alternative proposals for surfaces (floor, wall and ceiling) and non-surfaces (furniture, windows and doors) on a unit plan basis for large-scale housing development projects, and provided an interior information model. The model was validated through an example study to show how it could be used in the decision-making process by various participants in a construction project. The proposed model is useful in providing a total interior cost review and cost baseline for the developer/owner, a means for cost-based decision making by interior designers, and the interior material information required by builders. Future studies will focus on the automation of quantity surveying and graphics to reinforce the use of Internet-based decision support systems. In future studies, further subdivision of the design objects characteristics will be necessary, as well as the development of a system that enables clients to make interior design decisions by changing layers, a subject outside the scope of the present study. Additional work is also required to enable interior designers to use the information provided by vendors and suppliers directly, and to provide the information for the procurement phase without any additional processing.

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