Show simple item record

dc.contributor.authorHong, Yingen
dc.contributor.authorHovhannisyan, Vahanen
dc.contributor.authorXie, Haiyanen
dc.contributor.authorBrilakis, Ioannisen
dc.date.accessioned2021-04-19T14:52:57Z
dc.date.available2021-04-19T14:52:57Z
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/321261
dc.description.abstractConstruction 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.
dc.rightsAll rights reserved
dc.titleDetermining Construction Method Patterns to Automate and Optimise Scheduling – A Graph-based Approachen
dc.typeConference Object
dc.identifier.doi10.17863/CAM.68385
dcterms.dateAccepted2021-03-11en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2021-03-11en
dc.contributor.orcidHong, Ying [0000-0002-6602-6276]
dc.contributor.orcidBrilakis, Ioannis [0000-0003-1829-2083]
rioxxterms.typeConference Paper/Proceeding/Abstracten
pubs.funder-project-idLeverhulme Trust (IAF-2018-011)
pubs.funder-project-idInnovate UK (104795)
pubs.funder-project-idEPSRC (EP/S02302X/1)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (860555)
pubs.funder-project-idAustralian Research Council (DP170104613)
pubs.conference-nameEuropean Conference on Computing in Constructionen
pubs.conference-start-date2021-07-19en
cam.orpheus.counter18*
rioxxterms.freetoread.startdate2021-08-28


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record