The use of simulation for productivity estimation based on multiple regression analysis

Productivity estimation has been fundamental subject investigated in academia and industry. There are two common methods for estimation of productivity: (1) deterministic and (2) simulation methods. The deterministic method does not reflect actual conditions, such as randomness of work duration, whereas simulation method can overcome this limitation. However, the user without a background in simulation may struggle with implementation due to the difficulty of modeling. The presented productivity estimation model in this research was created using multiple regression analysis with data generated by WebCYCLONE. The model representing the mathematical relations between conditions and productivity allows planners or site personnel to estimate productivity by simply entering input data reflecting actual site conditions. In academia, the research methodology utilized in this research provides a framework for the user to establish other application models for estimating or evaluating the performances of new technologies.