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Dynamic Simulation Model for Estimating In-situ Production Quantity of PC Members

Abstract

The objective of this research is to present a dynamic simulation model for in-situ production quantity estimate of precast concrete members. The cost estimation model was developed using the system dynamics methodology by considering the influence factors for in-situ production of precast concrete members. The model was then applied to a real warehouse project to compare the costs of the quantity reflecting the field condition for in-situ production with those of in-plant production under the different scenarios with the available production sites within the construction site. The results of simulation tests indicated that the cost reduction of up to 16.9% was achieved from in-plant production to in-situ production when 100% of the precast concrete members are in-situ produced. When considering the field conditions of the real warehouse project site, the cost reduction of 13.9% was achieved in the site where in-situ production of precast concrete members is applicable within a limited space due to the production and yard stock areas. The model helps save production costs of the precast concrete members for project owners because it can estimate the actual in-situ production quantity and costs by varying the in-situ production areas compared to the construction site areas.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MOE) (No. NRF-2019R1A6A3A12032427). The writers thank three anonymous reviewers for their critical and helpful comments and suggestions that improved the quality of this paper.

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Correspondence to Joseph J. Kim.

Appendix: Symbols

Appendix: Symbols

See Table 5.

Table 5 Abbreviation for equations

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Lim, J., Kim, S. & Kim, J.J. Dynamic Simulation Model for Estimating In-situ Production Quantity of PC Members. Int J Civ Eng 18, 935–950 (2020). https://doi.org/10.1007/s40999-020-00509-4

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Keywords

  • Precast concrete
  • In-situ production
  • Quantity estimation
  • System dynamics
  • Dynamic analysis
  • Simulation model