Digital twin-enabled smart facility management: A bibliometric review

doi:10.1007/s42524-023-0254-4

Front. Eng

2024, Vol. 11

Issue (1) : 32-49 https://doi.org/10.1007/s42524-023-0254-4

Digital twin-enabled smart facility management: A bibliometric review

Obaidullah HAKIMI, Hexu LIU(

), Osama ABUDAYYEH

Department of Civil and Construction Engineering, Western Michigan University, Kalamazoo, MI 49008-5316, USA

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Abstract

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.

Keywords digital twin building information modeling facility management semantic interoperability artificial intelligence intelligent monitoring autonomous control feedback

Corresponding Author(s): Hexu LIU

Just Accepted Date: 23 March 2023 Online First Date: 26 April 2023 Issue Date: 13 March 2024

Cite this article:

Obaidullah HAKIMI,Hexu LIU,Osama ABUDAYYEH. Digital twin-enabled smart facility management: A bibliometric review[J]. Front. Eng, 2024, 11(1): 32-49.

URL:

https://academic.hep.com.cn/fem/EN/10.1007/s42524-023-0254-4
https://academic.hep.com.cn/fem/EN/Y2024/V11/I1/32

Fig.1 Research methodology.

Fig.2 Literature retrieval process.

Fig.3 Yearly number of documents published on the topic of DT in FM (January 2012–March 2022).

Fig.4 Distribution of publications on the topic of DT in FM in various research fields: (a) WoS and (b) Scopus.

Fig.5 Scientific publications on the topic of DT in FM by document type.

Fig.6 Co-occurrence network of author keywords related to DT in FM.

Clusters and their keywords	Occurrences	Links	Total link strength	Avg. number of citations	Avg. publication year
Cluster 1: AI-based predictive maintenance (red)
1. Artificial intelligence	10	16	31	1.60	2020.80
2. Computational modeling	3	4	5	0.00	2021.67
3. Deep learning	3	3	4	0.67	2021.00
4. Digitalization	3	9	9	8.00	2019.67
5. Optimization	4	6	7	1.25	2021.25
6. Predictive maintenance	13	17	40	4.00	2020.77
7. Preventive maintenance	5	6	9	7.00	2020.40
8. Simulation	6	7	9	1.00	2020.50
9. Sustainability	5	7	9	1.40	2020.80
Cluster 2: Real-time cyber–physical integration (green)
1. Big data	7	11	18	3.14	2020.57
2. Cyber–physical systems	6	10	16	6.17	2020.50
3. Industry 4.0	11	14	24	8.27	2020.27
4. Internet of Things	29	20	68	8.21	2020.10
5. Prognostics and health management	3	8	10	3.67	2020.33
6. Sensors	5	12	16	2.80	2020.80
7. Smart cities	9	9	19	5.56	2020.44
Cluster 3: Digital FM (blue)
1. Anomaly detection	5	6	9	10.80	2020.20
2. Augmented reality	5	8	13	6.40	2020.20
3. Building information modeling	40	20	81	7.43	2020.40
4. Facility management	20	20	56	6.85	2020.50
5. Maintenance	5	5	6	9.40	2020.60
Cluster 4: As-built/As-is modeling (yellow)
1. Bridges	3	6	8	0.00	2021.67
2. Data analytics	3	7	8	5.00	2020.33
3. Digital transformation	3	4	4	1.00	2021.00
4. Management	3	5	6	0.00	2021.33
5. Monitoring	4	13	13	3.50	2020.25
Cluster 5: Intelligent prognostics and health management (purple)
1. Digital twin	139	34	192	5.09	2020.52
2. Machine learning	9	12	22	1.89	2020.89
3. Operation and maintenance	4	5	8	0.75	2021.25
4. Remaining useful life	4	3	6	5.50	2020.50
5. Wind turbine	3	4	6	1.33	2021.00
Cluster 6: Asset lifecycle management (light blue)
1. Asset management	19	14	36	9.21	2020.26
2. Lifecycle management	3	4	6	32.00	2019.67
3. Smart grid	3	1	1	0.00	2020.00
Cluster 7: Semantic interoperability (brown)
1. Ontology	4	5	8	1.00	2020.00
2. Smart building	12	7	21	3.58	2020.33

Tab.1 Most frequently occurring keywords in research on DT in FM

Tab.2 Most cited documents on DT application in FM

Tab.3 Most cited sources of academic publications on DT application in FM

Fig.7 Network mapping of the most cited sources of academic publications on DT in FM.

Tab.4 Most relevant authors for the topic of DT in FM

Fig.8 Network visualization of most cited authors in the research area of DT in FM.

Tab.5 Countries with the most highly cited publications in the research area of DT in FM

Fig.9 Network mapping of countries with the most cited academic publications on DT in FM.

Tab.6 Authors exhibiting the highest degree of collaboration in the area of DT in FM

Fig.10 Network visualization map of co-authorship analysis of authors publishing on the topic of DT in FM.

Tab.7 Most highly collaborative countries with respect to research on DT in FM

Fig.11 Network mapping of co-authorship of scientific documents on the topic of DT in FM by country.

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