Summary: | 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.
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