Digital technology for quality management in construction:A review and future research directions

Abstract

Significant developments in digital technologies can potentially provide managers and engineers with the ability to improve the quality of the construction industry. Acknowledging the current and future use of digital technologies in construction quality management (CQM), we address the following research question: What developments in digital technologies can be used to improve quality in the construction industry? In addressing this research question, a systematic review approach is used to examine the studies that have been used for the management of quality in the construction industry. This review indicates that there is a need for digital technology-based quality management to be: (1) enhance defect management for concealed work, (2) enhance pre-construction defects prevention as well as post-completion product function testing, and (3) research on construction compliance inspection as a direction. We suggest that future research focus on quality culture development, advanced data analytics, and behavioral quality assessment.

Publication DOI: https://doi.org/10.1016/j.dibe.2022.100087
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Civil Engineering
Additional Information: © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). Funding Information: The authors would like to acknowledge the financial support provided by the National Natural Science Foundation of China (Grant No. U21A20151 , 51978302).
Uncontrolled Keywords: Quality management,Digital technology,Quality defects,Quality culture,Behavioral quality,Architecture ,Civil and Structural Engineering,Building and Construction,Materials Science (miscellaneous),Computer Science Applications,Computer Graphics and Computer-Aided Design
Publication ISSN: 2666-1659
Last Modified: 12 Dec 2024 08:29
Date Deposited: 05 Sep 2022 15:52
Full Text Link:
Related URLs: https://www.sci ... 666165922000217 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Review article
Published Date: 2022-12
Published Online Date: 2022-08-19
Accepted Date: 2022-08-16
Authors: Luo, Hanbin
Ling, Lin
Chen, Ke
Fordjour, Antwi-Afari Maxwell (ORCID Profile 0000-0002-6812-7839)
Chen, Lijun

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