Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103282
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dc.contributorDepartment of Building and Real Estate-
dc.creatorLi, Xen_US
dc.creatorWu, Cen_US
dc.creatorWu, Pen_US
dc.creatorXiang, Len_US
dc.creatorShen, GQen_US
dc.creatorVick, Sen_US
dc.creatorLi, CZen_US
dc.date.accessioned2023-12-11T00:32:53Z-
dc.date.available2023-12-11T00:32:53Z-
dc.identifier.issn0959-6526en_US
dc.identifier.urihttp://hdl.handle.net/10397/103282-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Li, X., Wu, C., Wu, P., Xiang, L., Shen, G. Q., Vick, S., & Li, C. Z. (2019). SWP-enabled constraints modeling for on-site assembly process of prefabrication housing production. Journal of Cleaner Production, 239, 117991 is available at https://doi.org/10.1016/j.jclepro.2019.117991.en_US
dc.subjectConstraints modelingen_US
dc.subjectDiscrete event simulationen_US
dc.subjectPrefabrication housing productionen_US
dc.subjectSmart work packagingen_US
dc.subjectSystem dynamicsen_US
dc.titleSWP-enabled constraints modeling for on-site assembly process of prefabrication housing productionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume239en_US
dc.identifier.doi10.1016/j.jclepro.2019.117991en_US
dcterms.abstractPrefabrication housing production (PHP) processes are fragmented and full of variability. Their schedule reliability is particularly disturbed by the constraints deriving from task executions in the on-site assembly process. Proactive constraints modeling, including identifying constraints and understanding their interrelationships, is crucial to ensure successful task executions and enhance sociability in collaborative working. However, current methods for constraints modeling are often sluggish and heavily rely on human's commitments because there is no real-time and value-added information for decision-making. To address this issue, this study proposes an approach of smart work packaging (SWP)-enabled constraints modeling service, which consists of three dynamic sub-services: social network analysis (SNA) service, hybrid system dynamics (SD)-discrete event simulation (DES) model service, and constraints scenario analysis service. It can equip the workers with the ability to (1) automatically identify the critical constraints, (2) dynamically explore interactional and interdependent relationships of these constraints, and (3) simulate and analyze the impact on schedule performance under different constraints scenarios. Five critical constraints are identified, including adverse weather conditions, lack of collision-free path planning, lack of visible and audible communication mechanism, lack of optimal buffer layout, and lack of optimal installation sequence. Most interrelationships are depicted in the four modules of the hybrid SD-DES model, including the assembly process, resource availability, operation efficiency, and schedule performance. Finally, the most influential constraint “lack of collision-free path planning” to schedule performance is identified in the constraints scenario analysis process.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of cleaner production, 1 Dec. 2019, v. 239, 117991en_US
dcterms.isPartOfJournal of cleaner productionen_US
dcterms.issued2019-12-01-
dc.identifier.scopus2-s2.0-85070605634-
dc.identifier.artn117991en_US
dc.description.validate202312 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBRE-0464-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextResearch Institute for Sustainable Urban Development of the Hong Kong Polytechnic University, Australian Research Council Discovery Project; National Natural Science Foundation of China; Natural Science Foundation of Guangdong Provinceen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24253491-
dc.description.oaCategoryGreen (AAM)en_US
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