Determining Construction Method Patterns to Automate and Optimise Scheduling – A Graph-based Approach
View / Open Files
Conference Name
European Conference on Computing in Construction
Type
Conference Object
This Version
AM
Metadata
Show full item recordCitation
Hong, Y., Hovhannisyan, V., Xie, H., & Brilakis, I. Determining Construction Method Patterns to Automate and Optimise Scheduling – A Graph-based Approach. European Conference on Computing in Construction. https://doi.org/10.17863/CAM.68385
Abstract
Construction projects have been experiencing project delays for decades. As an executive guide to construction activities, 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 time- and risk-efficient construction method patterns from historic projects to help schedulers improve productivity and accuracy. The method leverages schedule data (including activity names, Work Breakdown Structure, and start and finish date) that were obtained from a Tier-1 contractor for this study. The method was validated for excavation activities. The results indicate that the most time-efficient excavation activities can be done in 0.6% of total project time. The proposed method can help industry professionals standardise scheduling guidelines and automate the generation of construction schedules for critical subtasks.
Sponsorship
Leverhulme Trust (IAF-2018-011)
Innovate UK (104795)
Engineering and Physical Sciences Research Council (EP/S02302X/1)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (860555)
Australian Research Council (DP170104613)
Identifiers
External DOI: https://doi.org/10.17863/CAM.68385
This record's URL: https://www.repository.cam.ac.uk/handle/1810/321261
Rights
All rights reserved
Licence:
http://www.rioxx.net/licenses/all-rights-reserved
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk