MATHEMATICAL-MODELING OF THE EFFECT OF HUMAN LEARNING IN THE FINITE PRODUCTION INVENTORY MODEL

It is a natural phenomenon that the performance of a person engaged in a repetitive task improves with time. In the manufacturing engineering literature,1,2 this phenomenon is referred to as the learning curve, which is a decrease in the effort required for producing each unit in a repetitive manufacturing operation. Factors contributing to this improved performance include more effective use of tools and machines, increased familiarity with operation tasks and work environment, and enhanced management efficiency. Deterministic production inventory models found in the literature3,4 have been formulated to show the effects of numerous variables or a combination of variables on model outputs. Variables considered include stock shortages, safety stock, and level of customer patience. More recently, a finite production inventory model was formulated taking into consideration the effect of machine unavailability on optimum production quantity.5 Because the learning phenomenon is believed to have economic and decision-making implications in an inventory management system,6 it is the objective of the study presented herein to investigate the effect of learning on both optimum production quantity and minimum total inventory system cost.