Hexu Liu

Dr. Hexu Liu

Department of Civil and Construction Engineering, Western Michigan University, Kalamazoo, MI, USA
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2019 in Automation in Construction
Verified
Journal Article
Closed access
Xianfei YinXianfei Yin
Xianfei Yin
Hexu LiuHexu Liu
Hexu Liu
YCYuan Chen
Yuan Chen
MAMohamed Al-Hussein
Mohamed Al-Hussein

1 May 2015 in Automation in Construction
Verified
Journal Article
Closed access
Hexu LiuHexu Liu
Hexu Liu
MAMohamed Al-Hussein
Mohamed Al-Hussein
MLMing Lu
Ming Lu

1 January 2018 in Automation in Construction
Verified
Journal Article
Closed access
MAMohammed Sadiq Altaf
Mohammed Sadiq Altaf
ABAhmed Bouferguene
Ahmed Bouferguene
Hexu LiuHexu Liu
Hexu Liu
MAMohamed Al-Hussein
Mohamed Al-Hussein
HYHaitao Yu
Haitao Yu

1 April 2016 in Advanced Engineering Informatics
Verified
Journal Article
Closed access
Hexu LiuHexu Liu
Hexu Liu
MLMing Lu
Ming Lu
MAMohamed Al-Hussein
Mohamed Al-Hussein

26 April 2023 in Frontiers of Engineering Management
Verified
Journal Article
Open access
PDF file
OHObaidullah Hakimi
Obaidullah Hakimi
Hexu LiuHexu Liu
Hexu Liu
OAOsama Abudayyeh
Osama Abudayyeh
In recent years, the architecture, engineering, construction, and facility management (FM) industries have been applying various emerging digital technologies to facilitate the design, construction, and management of infrastructure facilities. Digital twin (DT) has emerged as a solution for enabling real-time data acquisition, transfer, analysis, and utilization for improved decision-making toward smart FM. Substantial research on DT for FM has been undertaken in the past decade. This paper presents a bibliometric analysis of the literature on DT for FM. A total of 248 research articles are obtained from the Scopus and Web of Science databases. VOSviewer is then utilized to conduct bibliometric analysis and visualize keyword co-occurrence, citation, and co-authorship networks; furthermore, the research topics, authors, sources, and countries contributing to the use of DT for FM are identified. The findings show that the current research of DT in FM focuses on building information modeling-based FM, artificial intelligence (AI)-based predictive maintenance, real-time cyber–physical system data integration, and facility lifecycle asset management. Several areas, such as AI-based real-time asset prognostics and health management, virtual-based intelligent infrastructure monitoring, deep learning-aided continuous improvement of the FM systems, semantically rich data interoperability throughout the facility lifecycle, and autonomous control feedback, need to be further studied. This review contributes to the body of knowledge on digital transformation and smart FM by identifying the landscape, state-of-the-art research trends, and future needs with regard to DT in FM.

1 March 2023 in Journal of Construction Engineering and Management
Verified
Journal Article
Closed access
PDF file
Hexu LiuHexu Liu
Hexu Liu
SHSangHyeok Han
SangHyeok Han
Zhenhua ZhuZhenhua Zhu
Zhenhua Zhu
The construction industry has been criticized for low productivity, lack of collaboration and information sharing, poor contract administration, and the like due to its decentralized and fragmented structure as well as sequential and chain-resembling nature. Recently, blockchain technology and its benefits have received wide attention and interest. This research synthesizes the research trends and needs of this growing area by means of a bibliometric-qualitative review method. Scopus and Web of Science were selected as the literature databases to retrieve relevant academic publications. Through a systematic literature search and screening, 181 related articles were identified for bibliometric analysis, and 149 publications were critically discussed in a qualitative review. The bibliometric results indicated the recent research regarding blockchain in construction is primarily directed into several clusters, such as “smart contract,” “Building Information Modeling (BIM),” “supply chain management,” “construction contract,” “construction and project management,” “digital twin,” and “smart city.” These clusters were further synthesized for a qualitative review revealing deep insight into research challenges and gaps. Both quantitative and qualitative review results were then mapped to the future directions. It was noted that future research needs to focus on (1) quantifying the cost-benefits of the blockchain applications in construction, e.g., return on investment, practitioners training, and improving industry readiness, (2) integration of blockchain with different project delivery systems, and (3) technology fusion with blockchain for construction management.