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Innovative Design and Execution Model for Improving Productivity of Interior Prefabricated Commercial Wall Assemblies

Author(s):

ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 1, v. 13
Page(s): 68
DOI: 10.3390/buildings13010068
Abstract:

Field productivity of building trades is the focus of prefabricated construction practitioners as a path to greater profitability and competitiveness in the marketplace. Construction firms are struggling to meet the demand of the marketplace due to shortages of skilled workers and flat to declining productivity. Human capital and productivity challenges are affecting the ability to both acquire new work and complete the work under contract. This study focuses on the development of an innovative model that defines a process for the design, project site preconstruction planning phase, and fabrication of interior prefabricated wall components that improves onsite productivity. The developed model was tested and implemented in a case study of a single project comprised of four identical buildings located on a singular jobsite while utilizing both traditional and model approaches. The results verify that the productivity model developed in this study is capable of reducing on-site labor hours and, therefore, improving field productivity compared to traditional methods. The application of the model saved between 7–23% man-hours compared to the traditional methods and beat the estimate by 17%. Practitioners and researchers are both incentivized to explore, develop, and implement novel methodologies to address the human capital shortage that is facing the construction industry.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10712384
  • Published on:
    21/03/2023
  • Last updated on:
    10/05/2023
 
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