At present, there are insufficient design decision making tools to support effective construction waste minimisation evaluation and implementation throughout all design stages. A limited but growing body of recent literature suggests that building information modelling has the potential to assist architects to minimise design waste on their projects. The research reported in this paper is the first attempt to develop a design decision making framework for improving construction waste minimisation performance through building information modelling. The potential use of building information modelling to drive out construction waste in building design was investigated through a questionnaire survey and follow-up interview with the top 100 architectural practices in the United Kingdom. An industry-reviewed 'building information modelling-aided construction waste minimisation framework' was developed based on the results of the literature review, questionnaire data, and interview data. The Framework is intended to act as an integrated platform for designing out waste decision making, by providing informed building information modelling-driven guidance to address waste causes throughout design stages.
Funding
The research and this paper would not be possible without the research funding from the School of Civil and Building Engineering, Loughborough University, England.
History
School
Architecture, Building and Civil Engineering
Published in
Automation in Construction
Volume
59
Pages
1 - 23
Citation
LIU, Z. ... et al, 2015. A BIM-aided construction waste minimisation framework. Automation in Construction, 59, pp.1-23
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Acceptance date
2015-07-20
Publication date
2015-08-14
Notes
This paper was accepted for publication in the journal Automation in Construction and the definitive published version is available at http://dx.doi.org/10.1016/j.autcon.2015.07.020