Modeling simultaneous worker learning and forgetting in dual resource constrained systems

This paper addresses issues related to modeling worker learning and forgetting effects in Dual Resource Constrained (DRC) systems. The learn–forget–learn (LFL) model of Carlson and Rowe is used to critically evaluate several worker training related issues that are associated with the learning and forgetting phenomenon. A numerical analysis is performed on the LFL model within a DRC system to gain insights into the nature of relationships between the extent of worker flexibility, forgetting rates, attrition rates, and flexibility acquisition policies. Results suggest that in the presence of higher attrition and forgetting rates, a worker may not be able to achieve full efficiency in as little as two different departments. Thus acquiring even incremental worker flexibility under such conditions may be infeasible. We also show that managers can use different flexibility acquisition policies designed in this study to reduce relearning losses and consequently improve the system performance.