BUILDING MODEL TO PREDICT LABOUR PRODUCTIVITY USING MULTIPLE LINEAR REGRESSION TECHNIQUE FOR "FORMWORK CONCRETE COLUMNS"

Yasser S. Nassar, Tareq A. Khaleel

Abstract


The productivity rate is the main indicator for the development of construction projects for any developed country. The main goal of this paper is to evolve a mathematical model by using the multiple linear regression technique to predict the rate of production of concrete column molds. This is because the currently used methods in estimating productivity, such as the methods that rely on personal experience and old data, are traditional methods characterized by inaccuracy. So, there was a need to adopt new techniques to estimate the construction productivity in an accurate, fast, and easy way. In this study, eleven factors were identified which are the most affecting factors on construction productivity. They are considered independent variables that affect the productivity rate of the item column formworks. The dependent variable is the construction productivity. The work measurement form was designed for the purpose of collecting real initial data from the site. This model is based on 36 samples of data collected from various projects of Multi-story buildings for residential and commercial buildings, which are used to build the model and verify its performance. From the results of the multiple linear regression MLR results, an equation was derived to calculate the construction productivity of the column formworks. It was found that the multi-linear regression model provides a very good predictability of productivity (82.31%), and the correlation coefficient (R%) was 97.15%. The results showed that the relationship between the independent variables for "the built-in model is very good, and the values"calculated from the prediction model are commensurate with actual data".

http://dx.doi.org/10.30572/2018/kje/100202 


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