Economic manufacturing quantities under conditions of learning and forgetting (EMQ/LaF)

Abstract

Abstract. It has been empirically observed that productivity improves as production continues due to system 'learning’, but that it deteriorates once the activity is stopped due to system 'forgetting’. Both learning and forgetting follow an exponential form with a 'doubling factor’ ranging between 0.75 and 0.98. We review and critique two previously proposed models, correct some minor errors in them, and expand one of them to accommodate a finite horizon. We also propose a new model that is more in harmony with the established learning function, for the determination of the optimal number and size of the lots in the finite and infinite horizon. The methodology used throughout is dynamic programming. We investigate the impact of all three models on the optimal lot sires and their costs, and establish the functional relations between the total cost and the various factors affecting them.