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Title: Developing a conceptual framework of smart work packaging for constraints management in prefabrication housing production
Authors: Li, X 
Shen, GQ 
Wu, P
Xue, F
Chi, HL 
Li, CZ
Issue Date: Oct-2019
Source: Advanced engineering informatics, Oct. 2019, v. 42, 100938
Abstract: Constraints management is the process of satisfying bottlenecks to facilitate tasks assigned to crews being successfully executed. However, managing constraints is inherently challenging in prefabrication housing production (PHP), due to the fragmentation of processes and information during project delivery. Enlightened by the broadly accepted work packaging method and the smart construction objects (SCOs) model, this study aims to define and implement smart work packaging (SWP) for constraints management in PHP. Firstly, the framework of SWP-enabled constraints management (SWP-CM) with three primary functions, including constraints modeling, constraints optimization, and constraints monitoring, is established. In addition, this study develops a layered abstract model as a prototype representation to elaborate on the implementation of SWP for practitioners. Finally, a laboratory-based test is applied to validate the framework. It can prove that SWP indeed opens new avenues for smart constraints management for PHP.
Keywords: Building information modeling (BIM)
Constraints management
Prefabrication housing production (PHP)
Smart work packaging (SWP)
Publisher: Elsevier Ltd
Journal: Advanced engineering informatics 
ISSN: 1474-0346
EISSN: 1873-5320
DOI: 10.1016/j.aei.2019.100938
Rights: © 2019 Elsevier Ltd. All rights reserved.
© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Li, X., Shen, G. Q., Wu, P., Xue, F., Chi, H. L., & Li, C. Z. (2019). Developing a conceptual framework of smart work packaging for constraints management in prefabrication housing production. Advanced Engineering Informatics, 42, 100938 is available at https://doi.org/10.1016/j.aei.2019.100938.
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