Inventory Optimization in Pharmacy Using Inventory Simulation-Based Model During the Covid-19 Pandemic
DOI:
https://doi.org/10.30656/intech.v9i2.5820Keywords:
EOQ, Inventory, Monte-carlo Simulation, Pharmacy, WarehouseAbstract
The problem that often occurs in raw material inventory is overstock or stockout conditions. The healthcare industry, including pharmaceuticals, has been experiencing uncertainty since the Covid-19 pandemic. Then impacts panic buying and stockpiling, which can lead to unpredictable spikes in demand, stockouts, and disruptions to the inventory system. The research was conducted at ABC Pharmacy in Yogyakarta, which experienced this problem. In this study, optimization of drug supply was carried out by measuring wareÂhouse capacity, and safety stock, increasing the number of orders and reorder points using the Min-Max and the economic order quantity models. A simulation of inventory optimiÂzation planning was carried out using Monte Carlo to see inventory projections for the next three months. Overall, the EOQ model simulation shows the most optimal results by showing the average total inventory cost of Rp. 103,579, where this number represents the lowest number of total inventory costs when compared to other simulation models. It also shows that the EOQ model is 86% more efficient in inventory cost than the Min-Max model. Comparison of the total cost of inventory The results of the three methods are calcuÂlated according to current demand and simulation of the EOQ method, which produces the minimum total inventory cost, followed by the company's initial model and the Min Max inventory method.
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