Date of Award

May 2024

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Engineering

First Advisor

Hamid H.S Seifoddini

Committee Members

Mathew M.P Petering, Wilkistar W.O Otieno, Habib H.T Tabatabai, Xiaohang X.Y Yue

Keywords

Clustering Analysis, Construction 4.0, Industry 4.0 Technologies, Productivity Enhancement, Technology Adoption, Text Mining

Abstract

Construction 4.0, which involves the application of Industry 4.0 technologies in construction activities, promises to revolutionize the construction industry by improving productivity, enhancing safety, promoting sustainability, and strengthening quality in the age of the Information Revolution. Industry 4.0 technologies such as Artificial Intelligence (AI), robotics, and the Internet of Things (IoT), have the potential to radically transform the construction industry in the 21st century. Construction activities constitute approximately 4.3% of the US gross domestic product-GDP and account for creating 7.5 million jobs. Although productivity has significantly increased in other industries, progress has been slow in the construction sector. One contributing factor is the relatively low investment in information technologies compared to other industries. The diversity and novelty of Industry 4.0 technologies, along with their wide range of applications in the construction sector present a considerable challenge in selecting the most appropriate technology or technologies for various construction applications. This research examines and categorizes 33 Industry 4.0 technologies and assesses their potential uses for different construction applications. In this study, data mining techniques are combined with clustering analysis to gain insights into various digital construction technologies and to determine which technology is best suited for each type of construction project throughout the project lifecycle. The overall purpose of this research is to survey the latest developments in technologies of construction 4.0 and to identify applications in construction industries that lend themselves to the implementation of these technologies. Specifically, this research aims to: (1) review Industry 4.0 technologies and explore their potential to advance Construction 4.0; (2) examine various construction activities and investigate their characteristics (attributes) in relation to the capabilities of Industry 4.0 technologies; (3) Utilize cluster analysis in conjunction with data mining to identify suitable technologies for specific construction activities; (4) develop a framework that can be used by scholars, practitioners, construction industries and students for the selection of technologies of Industry 4.0 for various construction activities. Additionally, this research will investigate which construction technologies have the potential to automate construction processes and enhance productivity.

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