Modeling and simulating learning development in construction

The time required to perform a given process in a repetitive construction environment tends to fall progressively as the same process is repeated for a sufficient number of successions. This paper discusses the aspects and fundamentals of learning development and its impact on the time requirement of repetitive construction processes from a simulation perspective. Common learning curves and their basic parameters and equations are highlighted. Factors that determine the level of learning rates for construction tasks are also investigated. We also introduce a statistically based approach for modeling learning development. Modeling learning phenomena in a simulation experiment is then introduced as applied in MicroCYCLONE (Halpin 1990). An example application is presented reflecting the impact of learning on the time requirement on a high-rise building; the statistically based approach is compared to the currently used deterministric models. This paper presents a simulation-based methodology for incorporating learning development in process simulation modeling and experimentation. In particular, it is suggested that a stochastic learning model be adopted due to the random factors affecting learning in construction. The paper highlights mathematical models often applied in modeling learning development and reviews the factors that contribute to these phenomena. An example application is also presented to illustrate how learning models can be incorporated into a simulation experiment. The effect of learning on the time required to complete a given process, and the significance of using stochastic versus deterministic learning models on various performance measures are also discussed.