Abstract :
Purpose: Construction productivity is highly dependent upon the overall productivity of labor during the execution of the project. Labor is considered as one of the most flexible factors for successful accomplishment of construction. The purpose of this research is to assess the effects of set of factors on labor productivity during concreting operation using Artificial Neural Network (ANN) model. The factors determined for this research were collected through questionnaire survey from site engineers, supervisors, project managers involved in construction sites. Most common factors affecting labor productivity were identified from Relative Importance Index (RII). Data were collected from active building construction sites during concreting operation of beam and slab. ANN model was used to study the effect of factors on labor productivity during concreting for estimating the production rates. Mean Square Error (MSE) were calculated from the estimated and actual rates which was obtained 0.17 which shows that the model has estimated the productivity rates within acceptable range. The data thus collected were analyzed using sensitivity analysis. The result of this research will enable to estimate labor productivity during concreting under certain variables accurately and provide understanding of the parameters that impact labor productivity in building construction
Keyword :
Concreting, Construction Industry, Labor, Productivity, Productivity Rates, Artificial Neural Network (ANN), Relative Importance Index (RII), Sensitivity Analysis