Abstract

To move precast concrete (PC) components to the site through vehicles in a PC project, a construction manager must establish a PC components–vehicle allocation (CVA) plan everyday by integrating factory, transport, and site information and by reflecting various considerations for CVA. However, in practice, the manager establishes the plan manually, which often leads to an increase in transportation costs due to inefficient use of vehicles and plan errors. Thus, this study develops an automated method for CVA by deriving considerations for CVA via interviews and literature review and by formalizing a CVA process that satisfies the considerations. The process has the following five steps: determining component loading type, developing preliminary CVA, determining vehicle loading type, crashing CVA for reducing the number of vehicles, and setting site arrival time and type of vehicles. Charrette test results indicate that the automated method can generate CVA plans faster than practitioners and reduce the number of vehicles by taking the derived considerations into account comprehensively. This study contributes to the off-site construction management theory by formalizing the process knowledge about how to deal with different considerations in CVA. This can help alleviate social and environmental problems, such as increased transportation cost and carbon dioxides emission by supporting decision-making of construction managers in planning installation of PC components and allocating them to vehicles.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure, and Transport (Grant No. 22ORPS-B158109-03).

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Go to Journal of Management in Engineering
Journal of Management in Engineering
Volume 38Issue 6November 2022

History

Received: Jan 21, 2022
Accepted: May 18, 2022
Published online: Aug 1, 2022
Published in print: Nov 1, 2022
Discussion open until: Jan 1, 2023

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Ph.D. Candidate, Division of Architecture and Urban Design, Incheon National Univ., 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea. ORCID: https://orcid.org/0000-0002-7137-1832. Email: [email protected]
Assistant Professor, Dept. of Architecture and Civil Engineering, City Univ. of Hong Kong, Tat Chee Ave., Kowloon 999077, Hong Kong. ORCID: https://orcid.org/0000-0003-0583-0348. Email: [email protected]
Choongwan Koo, Ph.D., A.M.ASCE [email protected]
Assistant Professor, Division of Architecture and Urban Design, Incheon National Univ., 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea. Email: [email protected]
Associate Professor, Division of Architecture and Urban Design, Incheon National Univ., 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea (corresponding author). ORCID: https://orcid.org/0000-0002-7887-1055. Email: [email protected]

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Cited by

  • Quantitative Analysis of the Factors Influencing Field Installation Time for Precast Concrete Building Components: An Empirical Study, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5816, 40, 3, (2024).
  • Automated Generation of Horizontal Precast Slab Stacking Plans, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-13424, 149, 12, (2023).

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