Prefabricated Construction Process Optimization Based on Rework Risk
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 6
Abstract
In prefabricated construction (PC) projects, component manufacturing and site construction are implemented concurrently to improve productivity. However, concurrent PC provides feedback information on each task, and iterations and coupling tasks often exist, which causes rework at a certain probability. Therefore, it is necessary to identify and optimize coupling tasks to reduce feedback information and rework costs and time. In this paper, a PC process optimization model that includes two modules is constructed. The first module is a coupling task optimization module and is built using the design structure matrix (DSM) method with graph theory to identify and reduce coupling tasks. Then a rework risk impact optimization module is built with cost and time minimization as objectives based on a genetic algorithm (GA) according to risk communication, rework probability, and core tasks. A case study is used to verify the model and reveals an 82.24% reduction of the impacts of rework risk on costs and time. The coupling tasks that are optimized as task groups require that the corresponding stakeholders be coordinated. Core tasks should be carried out in advance to avoid greater impacts in later periods. The model extends existing process optimization methods and has value for planning and controlling PC management to enhance coordination among all stakeholders. This study provides a reference for future research on rework risk prediction.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Nos. 51778335 and 51868016). The authors would also like to thank all experts interviewed for their assistance in data collection.
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Journal of Construction Engineering and Management
Volume 148 • Issue 6 • June 2022
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© 2022 American Society of Civil Engineers.
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Received: Jun 10, 2021
Accepted: Jan 18, 2022
Published online: Mar 29, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 29, 2022
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