journal article·2022-09-13Open access

Rebar Fabrication Plan to Enhance Production Efficiency for Simultaneous Multiple Projects

Eunbin Hong, June-Seong Yi, JeongWook Son, MinYoung Hong, YeEun Jang

Applied Sciences· Volume 12· Issue 18

Abstract

A discrete-event simulation (DES) model was developed to enhance the reinforcing bar (rebar) fabrication efficiency for multiple simultaneous projects at different sites. The production volume and procedure of the actual rebar fabrication plant were compared to the simulation model to ensure its accuracy. By determining the loss rate and necessary processing time, the fabrication plan was then optimized. The rebar type and machine features, which influence the loss rate and time required for rebar fabrication, were configured as the parameters in a discrete-event simulation model. The model considers a situation in which a rebar fabrication plant simultaneously delivers rebars to multiple sites. In this manner, the model can quantify the loss rate and time required in the fabrication process. The determination of the loss rate according to the import ratio of raw steel, site combination, and length can help optimize the rebar fabrication plan and increase work efficiency. In the considered scenario, a two-site combination and import ratio of raw steel of 2:1 (8 m:10 m) was noted to corresponded to the maximum decrease in the loss rate and required time. By extending the proposed approach to the complete rebar process (processing–transportation–construction), the plant member production process can be optimized.
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Research context

OpenAlex topics: BIM and Construction Integration · Manufacturing Process and Optimization · Optimization and Packing Problems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Architectural and Urban Engineering, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea

DL E&C, Donuimun, D Tower, 134 Tongil-ro, Jongno-gu, Seoul 03181, Korea

Funding

Korea Agency for Infrastructure Technology Advancement (KAIA)

References (17)

Show source-provided references
1. BIM-based combination of takt time and discrete event simulation for implementing just in time in construction scheduling under constraints10.1061/(ASCE)CO.1943-7862.0001940 ↗
2. (2018, November 02). AnyLogic: Simulation Modeling Software Tools & Solutions for Business. Why Simulation Modeling?. Available online: https://www.anylogic.com.
3. Success factors of JIT integration with IBS construction projects—A literature review
4. Three-step solutions for cutting stock problem of construction steel bars10.1007/s12205-014-0238-3 ↗
5. Borxhchev, A., and Filippov, A. (2014, January 25–29). From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools. Proceedings of the 22nd International Conference of the System Dynamics Society, Oxford, UK.
6. Ivanov, D. (2017). Operations and Supply Chain Simulation with AnyLogic, The AnyLogic Company.
7. Banks, J., Carson, J.S., Nelson, B.L., and Nicol, D.M. (2005). Discrete-Event System Simulation Fourth Edition, Pearson Education India.
8. Automated reinforcement trim waste optimization in RC frame structures using building information modeling and mixed-integer linear programming10.1016/j.autcon.2021.103599 ↗
9. Lee, D., Son, S., Kim, D., and Kim, S. (2020). Special-length-priority algorithm to minimize reinforcing bar-cutting waste for sustainable construction. Sustainability, 12.10.3390/su12155950 ↗
10. Waste-Based Management of Steel Reinforcement Cutting in Construction Projects10.1061/(ASCE)CO.1943-7862.0002052 ↗
11. Field data-based mathematical simulation of manual rebar cutting
12. Minimizing cutting wastes of reinforcing steel bars through optimizing lap splicing within reinforced concrete elements10.1016/j.conbuildmat.2018.07.023 ↗
13. Simulation-based decision support system for economical supply chain management of rebar10.1061/(ASCE)0733-9364(2007)133:1(29) ↗
14. Robinson, S. (2014). Simulation: The Practice of Model Development and Use, Bloomsbury Publishing.
15. Minimizing cutting wastes of reinforcement steel bars using genetic algorithms and integer programming models10.1061/(ASCE)0733-9364(2007)133:12(982) ↗
16. Holonic construction management: Unified framework for ICT-supported process control10.1061/(ASCE)ME.1943-5479.0000316 ↗
17. Integrated optimization of rebar detailing design and installation planning for waste reduction and productivity improvement10.1016/j.autcon.2019.01.012 ↗