预制混凝土
水准点(测量)
过程(计算)
方案(数学)
工程类
组分(热力学)
工业工程
结构工程
计算机科学
数学
大地测量学
热力学
操作系统
物理
数学分析
地理
作者
Zhenmin Yuan,Yuan Chang,Yunfeng Chen,Yaowu Wang,Wei Huang,Chen Chen
标识
DOI:10.1108/ecam-07-2022-0641
摘要
Purpose Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings. Design/methodology/approach This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization. Findings A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added. Originality/value To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.
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