4 research outputs found
Development of the Simulation Model for Ready Mixed Concrete Supply Chain Cost Structure
Supply of Ready Mixed Concrete (RMC) is a common process of concrete works on any structure. There is often a need to supply one or more construction sites simultaneously from multiple concrete plants. This paper presents a new simulation model of RMC supply and delivery from three concrete plants to three construction sites. The model is dynamic, easily managed, and adjustable and it allows proper estimation of the cost and time required to solve the problem of RMC supply. Model verification was performed using a case study of concrete supply to construction sites in the city of Niš, Serbia. The case study is based on real parameters obtained from specific concrete plants and construction sites. The results of the simulation experiment with varying number of mixers indicate that there is a significant influence of vehicle number and volume on idling costs. Based on the model analysis in the case study, scenario 10 (minimum total idling cost is 14,09 €) is recommended as the optimal combination of truck mixers for the considered case study. The simulation results indicate that the selection of an adequate combination can significantly reduce the costs of idling, for both the mixer and the pump, which leads to minimal idling time and, consequently, to timely pouring of concrete without reducing its quality
Comparative Representation of Two Models for Predicting the Productivity of Column and Wall Concreting Process
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
Comparative Representation of Two Models for Predicting the Productivity of Column and Wall Concreting Process
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