Impact of the Learning-Forgetting Effect on Mixed-Model Production Line Sequencing

In this study, the learning-forgetting (L-F) effect is considered in a mixed-model sequencing problem to investigate its impact on makespan minimization. To this end, mathematical models of the learning and forgetting effects are modified in accordance with a mixed-model production environment, and the L-F functions for a serial workstation and multiple products are established. Subsequently, their impact on production is demonstrated via data experiments. The relationships between the learning effect, forgetting effect, product model combination, and makespan are also discussed based on the experimental results. The results show that the learning and forgetting functions can significantly affect the work time in the mathematical scheduling model and that a balanced product model combination and small MPS (minimum part set) batch can help to reduce the L-F effect.