<![CDATA[PT. X, a water tank manufacturer in Indonesia, has long faced inventory management challenges due to the lack of a structured policy. The current MRP system relies heavily on subjective employee judgment, leading to a reactive and imbalanced inventory system with frequent stockouts or overstock. This study aims to develop a more structured inventory policy that is examined using Monte Carlo simulations in order to achieve more effective and efficient control. Materials are first classified into two groups, namely general components and special components and mixtures. These two groups receive different treatment according to their characteristics. The general components utilize a probabilistic inventory model (R, s, S) to create structured inventory parameters, which are then evaluated against the existing system. Special and mixed components improve the existing MRP system to DDMRP (Demand Driven Material Requirements Planning) with buffer levels across different materials. This adjustment is necessary because the behavior of the MRP system causes system instability, as it is highly dependent on the estimated demand for the final product. Overall, the selected inventory policy resulted in total cost savings of IDR 494,464,820 per week, equivalent to IDR 25,712,170,632 per year. This study proves that pull-based inventory system adjustments, namely DDMRP for special and mixed components and probabilistic inventory models (R, s, S) for general components, are effective in minimizing overstock, stabilizing demand variability, and significantly improving service levels.]]>
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