Comparative Representation of Two Models for Predicting the Productivity of Column and Wall Concreting Process

Abstract

One of the most important tasks of managing the construction process is to achieve the highest possible productivity. The productivity that can be achieved on a construction site depends on a number of influencing factors and on the type of work that is executed. Concrete works are a crucial activity when constructing high-rise buildings built in the RC frame structural system. Therefore, it is very important to adequately manage the concreting process in order to meet the set deadlines and reduce costs. This paper presents an approach for predicting the productivity of the concreting process based on the conducted quantitative research, by recording the concreting process on construction sites of buildings in Niš, Serbia. The concreting of reinforced concrete columns and walls on seven construction sites was recorded for 20 months. The total amount of fresh concrete that is built into the elements is 848 m3 and the total duration is 114 h of work. Factors that can affect productivity have been identified and, by applying the multiple linear regression and simulation methods and techniques and using the discrete event method and the agent-based method, models have been developed to predict the productivity of the concreting of reinforced concrete columns and walls. An analysis of the developed models was performed, and a comparative presentation was provided.

Keywords

• concreting process
• prediction
• productivity
• reinforced concrete columns and walls
• the regression model
• the simulation model