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Real-Time Optimization of Precast Concrete Component Transportation and Storage

Author(s):



Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2020
Page(s): 1-18
DOI: 10.1155/2020/5714910
Abstract:

The construction of prefabricated concrete structures involves many different types of precast concrete (PC) components. Improper arrangements of the transportation, storage, and hoisting of the PC components could lead to unnecessary relocation of PC components, causing a delay in construction progress. To address this problem, this paper presented a dynamic optimization method for PC component transportation and storage based on real-time scheduling and tracking. The real-time schedule can be extracted from a 4D building information model (BIM), and the position of PC components during the whole transportation process is tracked by a proposed tracking system which integrates the global navigation satellite system (GNSS) and the radio frequency identification (RFID) technology. A transportation optimization model was built to obtain a reasonable transportation plan based on real-time construction progress. A cyclic operation network (CYCLONE) simulation model for component storing and hoisting was proposed to calculate the on-site transportation time. A storage optimization model was proposed by considering the real-time transportation information to optimize the storage mode and storage position in the yard. The proposed models were solved in the context of a case study, which indicates that our method can reduce the on-site transportation time by 37% and effectively control the relocation times.

Copyright: © Donghai Liu et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10417177
  • Published on:
    31/03/2020
  • Last updated on:
    02/06/2021
 
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