Sadeghi, B (2024) Selecting Industry 4.0 technologies for construction activities using clustering analysis and text mining. PhD thesis, University of Wisconsin - Milwaukee, USA.
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.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Seifoddini, H |
| Uncontrolled Keywords: | construction activities; sustainability; artificial intelligence; investment; lifecycle; safety; cluster analysis; data mining; gross domestic product; productivity; robotic |
| Index terms: | lifecycle, robotics, mining, construction technology, artificial intelligence, construction industry, implementation, internet, clustering, digital construction, gross domestic product, industry 4.0, construction 4.0, data mining, productivity, construction activity, project lifecycle, practitioner, strengthening, construction process, construction project, cluster analysis, information technology, appropriate technology, construction sector, survey |
| Subjects: | computing systems, data collection methods, project delivery, data analysis and analytics, data science, technology adoption, artificial intelligence, management, information systems, industry analysis, geotechnical engineering, practitioner, project completion, digital engineering, technological development, economic analysis, contractual arrangements, construction operations, production management, automation and robotics, structural engineering, building construction |
| Topics: | Engineering Principles, Project Management, Sustainability, Procurement, Digital Applications, Site Management, Research Practice, Business Strategy, Roles and Professions |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here