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Article: Smart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process

TitleSmart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process
Authors
KeywordsBuilding information modeling
Constraints management
Crane path planning
Prefabrication housing production
Smart work packaging
Issue Date2020
Citation
Advanced Engineering Informatics, 2020, v. 43, article no. 101008 How to Cite?
AbstractLack of constraint-free crane path planning is one of the critical concerns in the dynamic on-site assembly process of prefabrication housing production (PHP). For decades, researchers and practitioners have endeavored to improve both the efficiency and safety of crane path planning from either static environment or re-planning the path when colliding with constraints or periodically updating the path in the dynamic environment. However, there is a lack of approach related to the in-depth exploration of the nature of dynamic constraints so as to assist the crane operators in making adaptive path re-planning decisions by categorizing and prioritizing constraints. To address this issue, this study develops the smart work packaging (SWP)-enabled constraints optimization service. This service embraces the core characteristics of SWP, including adaptivity, sociability, and autonomy to achieve autonomous initial path planning, networked constraints classification, and adaptive decisions on path re-planning. This service is simulated and verified in the BIM environment, and it is found that SWP-enabled constraints optimization service can generate the constraint-free path when it is necessary.
Persistent Identifierhttp://hdl.handle.net/10722/326203
ISSN
2021 Impact Factor: 7.862
2020 SCImago Journal Rankings: 1.107

 

DC FieldValueLanguage
dc.contributor.authorLi, Xiao-
dc.contributor.authorChi, Hung lin-
dc.contributor.authorWu, Peng-
dc.contributor.authorShen, Geoffrey Qiping-
dc.date.accessioned2023-03-09T09:58:52Z-
dc.date.available2023-03-09T09:58:52Z-
dc.date.issued2020-
dc.identifier.citationAdvanced Engineering Informatics, 2020, v. 43, article no. 101008-
dc.identifier.issn1474-0346-
dc.identifier.urihttp://hdl.handle.net/10722/326203-
dc.description.abstractLack of constraint-free crane path planning is one of the critical concerns in the dynamic on-site assembly process of prefabrication housing production (PHP). For decades, researchers and practitioners have endeavored to improve both the efficiency and safety of crane path planning from either static environment or re-planning the path when colliding with constraints or periodically updating the path in the dynamic environment. However, there is a lack of approach related to the in-depth exploration of the nature of dynamic constraints so as to assist the crane operators in making adaptive path re-planning decisions by categorizing and prioritizing constraints. To address this issue, this study develops the smart work packaging (SWP)-enabled constraints optimization service. This service embraces the core characteristics of SWP, including adaptivity, sociability, and autonomy to achieve autonomous initial path planning, networked constraints classification, and adaptive decisions on path re-planning. This service is simulated and verified in the BIM environment, and it is found that SWP-enabled constraints optimization service can generate the constraint-free path when it is necessary.-
dc.languageeng-
dc.relation.ispartofAdvanced Engineering Informatics-
dc.subjectBuilding information modeling-
dc.subjectConstraints management-
dc.subjectCrane path planning-
dc.subjectPrefabrication housing production-
dc.subjectSmart work packaging-
dc.titleSmart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.aei.2019.101008-
dc.identifier.scopuseid_2-s2.0-85074894959-
dc.identifier.volume43-
dc.identifier.spagearticle no. 101008-
dc.identifier.epagearticle no. 101008-

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