Stok Yönetiminde Min/Mak, Ekonomik Sipariş Miktarı ve DDMRP Politikalarının Simülasyonla Kıyaslaması(Benchmarking of Min/Max, Economic Order Quantity, and DDMRP Inventory Management Policies by Simulation

Abstract

Supply chains are adversely affected by increased volatility and uncertainty. Deterministicpush-based MRP (Material Requirement Planning) methods for production and stock management in turbulent markets have difficulty meeting the expected performance. In order to overcome this difficulty, the Dynamic-Drawn Demand Driven Material Requirement Planning (DDMRP) method has been proposed. In this study, with the Hannah's Shop package simulator prepared on AnyLogic by Goldratt Research Labs, MRP-based min/max and economic order quantity (EOQ-Economic Order) for 10 products in 4 different categories having several editable attributes to run under differing variability – capacity – seasonality scenarios. Key performance indicators (KPI) are selected to demonstrate the performance of MRP min-max and MRP EOQ vs DDMRP. While the variability increased in the simulator trials, it was observed that the DDMRP method provided higher performance than the EOQ and min/max methods. However, resource constraints may be seen due to frequent shipments. The DDMRP method has the potential to be used in part or all of the Supply Chain for raw material or finished goods inventory management. It will help determine a stock management strategy, especially in turbulent markets and SMEs with limited stock holding capacity or budget. The simulator allows sector practitioners to compare the EOQ - min/max methods and DDMRP methods by simulating the closest setup to the existing business environments. The reproducibility of the method will meet the need for benchmarking after the pandemic and supply chain breaks.

Keywords

• mrp
• ddmrp
• eoq
• inventory management
• supply chain management
• simulation