An interference-adjusted power learning curve for tasks with cognitive and motor elements

Production and operations management (POM) uses learning curve (LC) models to determine the length of training sessions for new workers predicting future task performance. Empirically validated LC parameters provide managers with quantitative information on effects presumed factors behind process. Previous studies considered compose cognitive motor curves. Another widely acknowledged but only recently parameterized phenomenon in POM field is interference, which assumes some loss or experience could occur over a session. This paper takes logical step this line research by developing an interference-adjusted power model, composite elements. accounts decay memory traces from repetitions measure residual (interference-adjusted) capture these phenomena. Three variants model are developed that assume exponential functions approximate version one. Assembly data representing various forms individual profile have been used test fits models. In addition those models, four potential literature were selected comparison purposes. The results show very well profile. findings highlight confluence three phenomena learning, component (cognitive/motor) plateauing.