Comparative analysis of challenges in manual and automated construction progress monitoring in Sri Lanka

Abstract

Construction Progress Monitoring (CPM) plays a pivotal role in ensuring the timely and cost-effective completion of construction projects. Previous research has classified CPM techniques into manual and automated methods. While traditional manual CPM has been prevalent in the Sri Lankan construction industry, it suffers from several limitations that can impede project success. Despite the significance of CPM, both manual and automated techniques face challenges in implementation. Therefore, the research aims to explore the challenges associated with CPM in the Sri Lankan construction industry. A comprehensive literature review was conducted to establish a theoretical framework. A quantitative research approach was employed, utilising a questionnaire survey with a heterogeneous purposive sampling method, involving 68 respondents. Data analysis was performed using IBM SPSS software. The study revealed different challenges in manual CPM and automated CPM specifically within the Sri Lankan context. One of the key takeaways of this study is that the challenges in manual CPM outweigh those in automated techniques. However, statistical analysis indicated that both manual and automated CPM face significant challenges, as evidenced by a negative skewness in survey data. Automated CPM heavily relies on computer vision technologies, with issues primarily arising from reality-capturing technologies. This study significantly contributes to the existing body of knowledge by identifying and categorising challenges in both manual and automated CPM within the Sri Lankan construction industry. The findings provide a platform for future research endeavours to devise strategies and solutions to address these challenges, ultimately enhancing the efficiency and effectiveness of construction progress monitoring in the industry.