Predicting Future Performance by Learning Curves

Mathematical learning curve models can be used in construction to predict the time or cost required to perform a repetitive activity. The objective of this paper is to describe the results of an exploratory study to evaluate the predictive capabilities of various learning curve models and data presentation methods for labor-intensive construction operations. In this study, we evaluated mathematical models for different learning curves for construction work. Our evaluation was based on a survey conducted in the spring of 2009 in Budapest and data obtained from literature. Several mathematical models, Wright model, DeJong model and Stanford B model and data presentation method, unit, cumulative average, moving average and exponential average were identified, and each was used for prediction. The results showed that Stanford B model and cumulative average and exponential average give the best future prediction.