Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105358
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Building and Real Estate | - |
dc.creator | Taiwo, R | - |
dc.creator | Hussein, M | - |
dc.creator | Zayed, T | - |
dc.date.accessioned | 2024-04-12T06:51:54Z | - |
dc.date.available | 2024-04-12T06:51:54Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/105358 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Taiwo R, Hussein M, Zayed T. An Integrated Approach of Simulation and Regression Analysis for Assessing Productivity in Modular Integrated Construction Projects. Buildings. 2022; 12(11):2018 is available at https://doi.org/10.3390/buildings12112018. | en_US |
dc.subject | Design of experiment | en_US |
dc.subject | Modular construction | en_US |
dc.subject | Productivity | en_US |
dc.subject | Regression | en_US |
dc.subject | Resource planning | en_US |
dc.subject | Simulation | en_US |
dc.subject | Tower crane | en_US |
dc.title | An integrated approach of simulation and regression analysis for assessing productivity in modular integrated construction projects | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 12 | - |
dc.identifier.issue | 11 | - |
dc.identifier.doi | 10.3390/buildings12112018 | - |
dcterms.abstract | Many nations across the globe face the challenge of housing deficit. Modular integrated construction (MiC), which has the highest level of prefabrication among off-site construction manufacturing (OSM), has been adopted as a fast and reliable construction method to address the housing deficit. Previous studies have assessed the productivity of the prefabrication stage of MiC, while investigations into the productivity of the MiC installation process with the consideration of pragmatic factors, especially for high-rise buildings, are lacking in the literature. Therefore, this study contributes by (1) developing a discrete-event simulation (DES) model to assess the productivity of MiC installation while considering pragmatic factors (e.g., weather conditions, topography, work dimension, etc.) and management conditions (e.g., workers’ motivation, training, equipment maintenance, etc.); (2) developing a mathematical model to understand the relationship between productivity and various resources utilized in MiC installation. After verifying and validating the DES model, it was applied to a case study in Hong Kong. A sensitivity analysis using a full factorial experiment design was conducted to identify the parameters (e.g., number of trucks, tower cranes, different crews) that significantly affect a number of performance measures, such as the project duration, productivity, and total costs. Furthermore, the mathematical model shows high prediction accuracy, as the mean absolute percentage error is 8.93%. This study would help construction practitioners in their decision-making process, while planning a project by providing them with a model that can predict the productivity of the MiC installation process before and during the project implementation. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Buildings, Nov. 2022, v. 12, no. 11, 2018 | - |
dcterms.isPartOf | Buildings | - |
dcterms.issued | 2022-11 | - |
dc.identifier.scopus | 2-s2.0-85149482190 | - |
dc.identifier.eissn | 2075-5309 | - |
dc.identifier.artn | 2018 | - |
dc.description.validate | 202403 bcvc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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buildings-12-02018.pdf | 3.12 MB | Adobe PDF | View/Open |
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