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Article: SWP-enabled constraints modeling for on-site assembly process of prefabrication housing production

TitleSWP-enabled constraints modeling for on-site assembly process of prefabrication housing production
Authors
KeywordsConstraints modeling
Discrete event simulation
Prefabrication housing production
Smart work packaging
System dynamics
Issue Date2019
Citation
Journal of Cleaner Production, 2019, v. 239, article no. 117991 How to Cite?
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.
Persistent Identifierhttp://hdl.handle.net/10722/326418
ISSN
2023 Impact Factor: 9.7
2023 SCImago Journal Rankings: 2.058
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Xiao-
dc.contributor.authorWu, Chengke-
dc.contributor.authorWu, Peng-
dc.contributor.authorXiang, Liqun-
dc.contributor.authorShen, Geoffrey Qiping-
dc.contributor.authorVick, Steven-
dc.contributor.authorLi, Clyde Zhengdao-
dc.date.accessioned2023-03-09T10:00:31Z-
dc.date.available2023-03-09T10:00:31Z-
dc.date.issued2019-
dc.identifier.citationJournal of Cleaner Production, 2019, v. 239, article no. 117991-
dc.identifier.issn0959-6526-
dc.identifier.urihttp://hdl.handle.net/10722/326418-
dc.description.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.-
dc.languageeng-
dc.relation.ispartofJournal of Cleaner Production-
dc.subjectConstraints modeling-
dc.subjectDiscrete event simulation-
dc.subjectPrefabrication housing production-
dc.subjectSmart work packaging-
dc.subjectSystem dynamics-
dc.titleSWP-enabled constraints modeling for on-site assembly process of prefabrication housing production-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jclepro.2019.117991-
dc.identifier.scopuseid_2-s2.0-85070605634-
dc.identifier.volume239-
dc.identifier.spagearticle no. 117991-
dc.identifier.epagearticle no. 117991-
dc.identifier.isiWOS:000487237100116-

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