Analyzing Cause and Effect Relationships of Obstacles to Applying Intelligent Robots in Construction Projects based on Grey-DEMATEL
Pages 260 - 266
Abstract
With the digital intelligence transformation of the construction industry in recent years, construction projects have faced many obstacles in applying intelligent robots, but the interaction between the obstacles is unclear. This paper aims to clarify the obstacles to applying intelligent robots in construction projects and to investigate the cause and effect relationships between the obstacles further. First, a Systematic Literature Review was used to extract the obstacles from the literature. Second, based on the "Technology-Organization-Environment" model, the dimensions of the obstacles were classified to establish a framework of obstacles to the application of intelligent robots in construction projects. Third, the Grey-DEMATEL was used to explore the cause and effect relationships between obstacles to applying intelligent robots in construction projects. The study found that inadequate incentives and regulatory mechanisms, immature technology and a lack of senior management and leadership are the three main causes of barriers and should be addressed first. This study helps construction projects overcome the obstacles to applying intelligent robots in an orderly manner, promotes digital intelligence transformation in the construction industry, and provide guidance for stakeholders and relevant government departments to develop reasonable policies.
References
[1]
Bademosi, F., & Issa, R. R. A. 2021. Factors Influencing Adoption and Integration of Construction Robotics and Automation Technology in the US. Journal of Construction Engineering and Management. 147, 8 (October 2021), 04021075. http://doi.org/10.1061/(asce)co.1943-7862.0002103.
[2]
Chen, Z., Zhao, Y., Zhou, X., Hao, S., & Li, J. 2022. Identifying the risk factors and their interactions of human–robot collaboration implementation during engineering project construction: evidence from China. Engineering, Construction and Architectural Management. Vol. ahead-of-print No. ahead-of-print. (May 2022), http://doi.org/10.1108/ecam-05-2021-0461.
[3]
Davila Delgado, J. M., Oyedele, L., Ajayi, A., Akanbi, L., Akinade, O., Bilal, M., & Owolabi, H. 2019. Robotics and automated systems in construction: Understanding industry-specific challenges for adoption. Journal of Building Engineering. 26, (July 2019), 100868. http://doi.org/10.1016/j.jobe.2019.100868.
[4]
Emaminejad, N., & Akhavian, R. 2022. Trustworthy AI and robotics: Implications for the AEC industry. Automation in Construction. 139, (May 2022), 104298. http://doi.org/10.1016/j.autcon.2022.104298.
[5]
Gharbia, M., Chang-Richards, A., Lu, Y., Zhong, R. Y., & Li, H. 2020. Robotic technologies for on-site building construction: A systematic review. Journal of Building Engineering. 32, (August 2020), 101584. http://doi.org/10.1016/j.jobe.2020.101584.
[6]
Huang, Z., Mao, C., Wang, J., & Sadick, A.-M. 2021. Understanding the key takeaway of construction robots towards construction automation. Engineering, Construction and Architectural Management. 29, 9 (July 2021), 3664-3688. http://doi.org/10.1108/ecam-03-2021-0267.
[7]
Hwang, B.-G., Ngo, J., & Teo, J. Z. K. 2022. Challenges and Strategies for the Adoption of Smart Technologies in the Construction Industry: The Case of Singapore. Journal of Management in Engineering. 38, 1 (March 2022), 05021014. http://doi.org/10.1061/(asce)me.1943-5479.0000986.
[8]
Kineber, A. F., Oke, A. E., Hamed, M. M., Rached, E. F., Elmansoury, A., & Alyanbaawi, A. 2022. A Partial Least Squares Structural Equation Modeling of Robotics Implementation for Sustainable Building Projects: A Case in Nigeria. Sustainability. 15 (December 2022), 604. http://doi.org/10.3390/su15010604.
[9]
Law, K. K., Chang, S., & Siu, M.-F. F. 2022. Factors Influencing Adoption of Construction Robotics in Hong Kong's Industry: A Multistakeholder Perspective. Journal of Management in Engineering. 38, 2 (May 2022), 04021096. http://doi.org/10.1061/(asce)me.1943-5479.0001011.
[10]
Oke, A. E., Aliu, J., Oluwasefunmi Fadamiro, P., Akanni, P. O., & Stephen, S. S. 2023. Attaining digital transformation in construction: An appraisal of the awareness and usage of automation techniques. Journal of Building Engineering. 67, (May 2023), 105968. http://doi.org/10.1016/j.jobe.2023.105968.
[11]
Oke, A. E., Kineber, A. F., Albukhari, I., & Dada, A. J. 2021. Modeling the robotics implementation barriers for construction projects in developing countries. International Journal of Building Pathology and Adaptation. Vol. ahead-of-print, No. ahead-of-print (November 2021), http://doi.org/10.1108/ijbpa-06-2021-0093.
[12]
Onososen, A. O., & Musonda, I. 2022. Research focus for construction robotics and human-robot teams towards resilience in construction: scientometric review. Journal of Engineering, Design and Technology. 21, 2 (March 2022), 1726-0531. http://doi.org/10.1108/jedt-10-2021-0590.
[13]
Pan, M., Linner, T., Pan, W., Cheng, H.-m., & Bock, T. 2020. Influencing factors of the future utilisation of construction robots for buildings: A Hong Kong perspective. Journal of Building Engineering. 30, (January 2020), 101220. http://doi.org/10.1016/j.jobe.2020.101220.
[14]
Pan, M., & Pan, W. 2019. Determinants of Adoption of Robotics in Precast Concrete Production for Buildings. Journal of Management in Engineering. 35, 5 (December 2019), 05019007. http://doi.org/10.1061/(asce)me.1943-5479.0000706.
[15]
Pradhananga, P., ElZomor, M., & Santi Kasabdji, G. 2021. Identifying the Challenges to Adopting Robotics in the US Construction Industry. Journal of Construction Engineering and Management. 147, 5 (May 2021), http://doi.org/10.1061/(asce)co.1943-7862.0002007.
[16]
Zhao, S., Wang, Q., Fang, X., Liang, W., Cao, Y., Zhao, C., Li, L., Liu, C., & Wang, K. 2022. Application and Development of Autonomous Robots in Concrete Construction: Challenges and Opportunities. Drones. 6, 12 (December 2022), 424-450. http://doi.org/10.3390/drones6120424.
Index Terms
- Analyzing Cause and Effect Relationships of Obstacles to Applying Intelligent Robots in Construction Projects based on Grey-DEMATEL
Recommendations
Neurofuzzy Motion Planners for Intelligent Robots
A neurofuzzy methodology is presented for motion planning in semi-autonomous mobile robots. The robotic automata considered are devices whose main feature is incremental learning from a human instructor. Fuzzy descriptions are used for the robot to ...
Interactive Teaching for Vision-Based Mobile Robots: A Sensory-Motor Approach
For the last decade, we have been developing a vision-based architecture for mobile robot navigation. Using our bio-inspired model of navigation, robots can perform sensory-motor tasks in real time in unknown indoor as well as outdoor environments. We ...
Navigation of mobile robots in the presence of obstacles
Robot navigation is one of the basic problems in robotics. In general, the robot navigation algorithms are classified as global or local, depending on surrounding environment. In global navigation, the environment surrounding the robot is known and the ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
September 2023
564 pages
ISBN:9798400708824
DOI:10.1145/3629378
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 28 December 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICIBE 2023
ICIBE 2023: 2023 the 9th International Conference on Industrial and Business Engineering
September 22 - 24, 2023
Beijing, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 19Total Downloads
- Downloads (Last 12 months)19
- Downloads (Last 6 weeks)0
Reflects downloads up to 30 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format