Saline Inventory Management with Simulation Techniques

This research aims to study an inventory system for managing saline in four categories at a community hospital. The objective is to conduct an Economic Order Quantity (EOQ) and Reorder Point (ROP) to improve the saline inventory management system. Monte Carlo Simulation technique was applied to analyze saline inventory management policies under uncertain demands, namely; s, Qmax(1), s, Qavg(2), s, Qmin(3), T, Qmax(4), T, Qavg(5), T, Qmin(6), T, S (7), and s, S(8). An optimization technique was used to conduct the suitable policy of saline inventory management. The simulation results stated that the most appropriate policy without affecting shortage and overstocking was s,Qmax policy. Moreover, the comparison of each demand quantity (bottle) in each type of saline (A, B, C, and D) among the proposed policies indicated that the s,Qmax policy yielded the lowest overstocking value compared to each demand in each saline type equal to 0.20, 0.38, 0.32, and 0.37, respectively. This study ca