A Dynamic Simulation Model for Near-Zero Rebar-Cutting Waste through Special-Length-Priority Optimization

Author:

Oh Jinhyuk1ORCID,Kim Sunkuk2ORCID,Widjaja Daniel Darma1ORCID

Affiliation:

1. Department of Architectural Engineering, Kyung Hee University, Yongin-si 17104, Republic of Korea

2. Department of R&D, Earth Turbine Co., Ltd., Dong-gu, Daegu 41057, Republic of Korea

Abstract

Global economic fluctuations as exemplified by the recent COVID-19 financial crisis significantly impact the construction industry, particularly steel rebar supply chain and procurement. This impedes engineers’ efforts toward achieving near-zero rebar-cutting waste due to dynamic rebar minimum order quantities and maximum lengths imposed by steel mills. This study addresses the challenge of achieving near-zero rebar-cutting waste by proposing a model that simulates the level of optimization in minimizing rebar-cutting waste amidst such dynamics. The model was implemented in a case study involving reinforced concrete columns in a high-rise building. While achieving near-zero waste consistently proved challenging, particularly for greater than 50 tons of minimum quantity, the study identified a maximum 12 m rebar variant that attained this target regardless of minimum order quantity. Nonetheless, this study introduces a real-time decision-support system for rebar procurement, empowering engineers to optimize usage and minimize waste. This system facilitates near-zero rebar-cutting waste levels in response to rebar procurement requirement dynamics.

Funder

National Research Foundation of Korea

Publisher

MDPI AG

Reference48 articles.

1. The effects of the late 2000s global financial crisis on Australia’s construction demand;Jiang;Australas. J. Constr. Econ. Build.,2013

2. Relationship between the financial crisis of Korean construction firms and macroeconomic fluctuations;Kim;Eng. Constr. Archit. Manag.,2011

3. Quantification and benchmarking of construction waste and its impact on cost—A case of Pakistan;Shahid;Eng. Constr. Archit. Manag.,2023

4. Predicting construction market growth for urban metropolis: An econometric analysis;Fan;Habitat Int.,2011

5. Fusing multi-source quality statistical data for construction risk assessment and warning based on deep learning;Gao;Knowl.-Based Syst.,2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3