A construction productivity study on precast concrete installation

• Main Author: Kaung Set, Zaw.
• Other Authors: Tiong Lee Kong, Robert
• Format: Final Year Project
• Language: English
• Published: 2012
• Subjects: DRNTU::Engineering::Civil engineering::Construction management
• Online Access: http://hdl.handle.net/10356/50275
• Institution: Nanyang Technological University

This report is part of an ongoing study under a research team which consists of one Ph.D student (Ali Najafi) and two final year students (Ting Weiwen Darren and the author). The aim of the study is to examine the factors affecting the installation of precast concrete components in a variety of projects and thereafter create a statistical model which can predict the installation time of the precast concrete panel. It is noted that contractors have a rough estimate for installation time of precast components which is about 30-45 minutes per panel. From the data analysis, it shows that some panels can take up to 80 minutes to install and some can be done less than 20 minutes. Therefore, there is a big difference in time prediction which might have a huge impact on the onsite planning and management. The model is trying to reduce this tolerance by being able to predict the cycle time more accurately with the input of factors that affect the cycle time. Firstly, the basic fundamentals of precast concrete installation method and the factors that might affect the installation procedure were carefully studied. Questionnaire with 17 desired parameters were prepared and contractors were contacted for data collection. Then, the research team made a number of site visits to collect the required data and analysis was done afterwards. A total of 71 data were collected and only fifty five cycle time data were used in the analysis. The main platform used to carry out the statistical analysis is SPSS software. The regression model was developed with relevant independent variables that have a significant impact on cycle time of installation. The result shows that only 9 out of 17 parameters have a significant impact on the cycle time and 71.9% of the variation in the total time can be explained by those independent variables. From this research, the practitioners will be able to plan precast concrete installation process more accurately and effectively. The model can be used to calculate the more precise installation time which will help the daily planning process. They will also have a better understanding of the factors that affect the cycle time and take necessary precautions to achieve higher productivity.