Applying a life cycle approach in designing flexible housing

Abstract

In designing a house it is usual to be focused on the current needs of clients and users. However, soon those initial needs will change for reasons such as family growth, aging and changing lifestyle. Various solutions for this issue have been suggested by architects. ‘Flexible Housing’ is a type of dwelling design that has the ability for a house to adjust to the changing needs of its occupants. Although all the qualitative research indicates that this type of dwelling is an economic and sustainable solution, there is little quantitative data to support that argument. The real financial benefit of Flexible Housing will only be recognisable when, rather than the routine design approach, based primarily on immediately available expenditure, life cycle costing is taken into account.

The term Life Cycle Costing (LCC) is used to describe a process in which all costs relating to a property over its whole life cycle would be systemically calculated and evaluated. LCC is a significant task in a life cycle approach to buildings. This research aimed to indicate the financial advantage of Flexible Housing through designing a flexible house applying a life cycle approach.

To achieve the purpose of this research, first, a literature review was undertaken to determine the main features of a flexible house. Among varying techniques that have been applied by architects to achieve flexibility, ‘slack space’ was chosen for the present research project. This concept allows for adding flexibility to design by preparing some unprogrammed spaces to be occupied by users to address their new needs in the future. These phases will be done through a Building Information Modelling-based design process, using its features especially in cost estimation and documentation. Building Information Modelling (BIM) is a recent approach in the architecture, engineering and construction (AEC) industry. Applying BIM potentials in the design process could help the architect to make better architectural decisions at the outset where there are enough quantitative data to support the financial analysis of the design.