A graph-based approach for unpacking construction sequence analysis to evaluate schedules
View / Open Files
Publication Date
2022-04Journal Title
Advanced Engineering Informatics: the science of supporting knowledge-intensive activities
ISSN
1474-0346
Publisher
Elsevier
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Hong, Y., Xie, H., & Brilakis, I. (2022). A graph-based approach for unpacking construction sequence analysis to evaluate schedules. Advanced Engineering Informatics: the science of supporting knowledge-intensive activities https://doi.org/10.1016/j.aei.2022.101625
Abstract
Construction schedules can mitigate delay risks and are essential to project success. Yet, creating a quality construction schedule is often the outcome of experienced schedulers, and what makes it harder is the fact that historic information including decision reasoning was not documented and disseminated for future use. This study proposes a graph-based method to find the most time-efficient construction sequence from historic projects to improve scheduling productivity and accuracy. The proposed method captured the textual, numerical, and graphical features of construction schedules, and was validated on 353 construction schedules obtained from a Tier-1 contractor in the UK. The results indicate that earthwork sequences can be finished in 4.0% of the project time on average, but earthwork sequences are the least time-efficient ones in a construction project (29% delayed), particularly in road construction (88% delayed). This study compared the time efficiency of sequences learned from previous projects with case study sequences. Results indicated that frequent sequences learned from past projects are 26.7% closer to the actual schedule than the planned ones. Results of this study could assist inexperienced schedulers to create more quality construction schedules and project managers to benchmark project performances.
Sponsorship
Innovate UK (104795)
European Commission Horizon 2020 (H2020) Industrial Leadership (IL) (958398)
Embargo Lift Date
2023-04-01
Identifiers
External DOI: https://doi.org/10.1016/j.aei.2022.101625
This record's URL: https://www.repository.cam.ac.uk/handle/1810/336701
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.