An indicator for superfluous iteration in offsite building design processes

Abstract

Enhancement of iteration management in the design phase is important for successful offsite building projects. Design iteration has two aspects. Although iteration is necessary to deal with design requirements when solving complex problems (i.e. increasing quality through iteration), it has also been identified in numerous studies to be one of the main causes of design errors and time and cost overruns (i.e. superfluous iteration), as it increases scheduling and design complexity. Current building project management tools do not provide a means to control the reduction of superfluous iteration. One problem is that existing research has difficulty precisely relating the effects of specific management actions to superfluous iteration. The idea of this study is to develop an indicator, the sequence deviation quotient (SDQ), which reflects the amount of superfluous design iteration in a project. It can be thought of as a tool supporting project managers to make systematic and continuous (from project to project) design process improvement. A premise is that the impact of varying project conditions on the process structure of design processes, i.e. the precedence relationships between the design activities, is only small. In this paper, we provide a definition of superfluous iteration. We tested the feasibility of the SDQ by subjecting it to project variation and input perturbation by means of a Monte Carlo simulation. The simulations are based on the data from a real offsite design building process, the designing of a 1100 m² residential building in Sweden.

Keywords:

• design changes
• design process simulation
• design structure matrix
• iteration
• project performance indicator

Acknowledgements

The work was performed at the competence centre of Lean Wood Engineering funded by Vinnova and the EU Regional development fund project TräIN, both acknowledged. The authors also gratefully acknowledge the companies who participated in the MIKS project for providing us with data. Finally, we want to thank the unknown reviewers for their valuable comments and constructive critique.