ITcon Vol. 26, pg. 303-318, http://www.itcon.org/2021/17

Machine learning - based framework for construction delay mitigation

DOI:10.36680/j.itcon.2021.017
submitted:April 2020
revised:March 2021
published:July 2021
editor(s):Amor R
authors:Muizz O. Sanni-Anibire, Mr.,
Dammam Community College, King Fahd University of Petroleum and Minerals, Kingdom of Saudi Arabia;
muizzanibire@kfupm.edu.sa

Rosli M. Zin, Prof.,
School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor, 81310, Malaysia;
roslizin@utm.my

Sunday O. Olatunji, Assoc. Prof.,
Department of Computer Science, College of Computer Science and Information Technology,
Imam Abdulrahman Bin Faisal University, Dammam, 31441, Kingdom of Saudi Arabia;
osunday@iau.edu.sa
summary:The construction industry, for many decades, has been underperforming in terms of the success of project delivery. Construction delays have become typical of many construction projects leading to lawsuits, project termination, and ultimately dissatisfied stakeholders. Experts have highlighted the lack of adoption of modern technologies as a cause of underproductivity. Nevertheless, the construction industry has an opportunity to tackle many of its woes through Construction 4.0, driven by enabling digital technologies such as machine learning. Consequently, this paper describes a framework based on the application of machine learning for delay mitigation in construction projects. The key areas identified for machine learning application include "cost estimation", "duration estimation", and "delay risk assessment". The developed framework is based on the CRISP-DM graphical framework. Relevant data were obtained to implement the framework in the three key areas identified, and satisfactory results were obtained. The machine learning methods considered include Multi Linear Regression Analysis, K-Nearest Neighbours, Artificial Neural Networks, Support Vector Machines, and Ensemble methods. Finally, interviews with professional experts were carried out to validate the developed framework in terms of its applicability, appropriateness, practicality, and reliability. The main contribution of this research is in its conceptualization and validation of a framework as a problem-solving strategy to mitigate construction delays. The study emphasized the cross-disciplinary campaign of the modern construction industry and the potential of machine learning in solving construction problems.
keywords:machine learning, construction delays, construction 4.0, delay mitigation, risk assessment, cost estimation, duration estimation
full text: (PDF file, 0.417 MB)
citation:Sanni-Anibire M O, Zin R M, Olatunji S O (2021). Machine learning - based framework for construction delay mitigation, ITcon Vol. 26, pg. 303-318, https://doi.org/10.36680/j.itcon.2021.017