Comparing dynamic risk-based scheduling methods with MRP via simulation

摘要

It is well known that material requirements planning (MRP) is a deterministic planning tool which heavily relies on accurate demand forecast, and that its performance under perturbed, constantly changing environment becomes questionable. Although many companies still use basic MRP as a planning tool, there are other alternative tools available. For example, Factory Physics Inc. has developed a tool called dynamic risk-based scheduling (DRS), which creates a set of policy parameters (e.g. work in process (WIP) level, lot sizes, re-order point, and re-order quantity) that work for a range of situations. The main objective of this paper is to compare DRS and MRP scheduling systems for single-machine and multi-machine systems via simulation. Their performance measures are compared for various systems assuming three levels of demand uncertainty. The simulation results suggest that DRS outperforms MRP in terms of robustness, fill rate and inventory level.