Simulating the Impact of Forecast Related Overbooking and Underbooking Behavior on MRP Planning and a Reorder Point System

Production Planning and its parameterization is critical to fulfil customer demands and to successfully react on changes in high volatile markets. Therefore, demand updates should be considered to improve production planning. In this paper the performance of two production planning methods MRP (Material Requirements Planning) and RPS (Reorder Point System) are compared in a multi-item single stage system where customer orders are updated in a rolling horizon manner. Applying a simulation study, we investigate the performance of MRP and RPS for biased and unbiased forecast information and discuss the difference in the optimal planning parameters. The study shows that for a production system with underbooking and low demand uncertainty, RPS method is superior, in all other scenarios MRP outperforms RPS. For overbooking scenarios, the results show MRP leads to overall cost improvements ranging from 8 to 30 %.