Stochastic Inventory Policy Design for 100 KVA Distribution Transformers Using Monte Carlo Simulation

To support more reliable infrastructure which in line with SDG 9 on Industry, Innovation, and Infrastructure, public electric utilities must maintain its services even during uncertain times. In Banjarmasin, Indonesia, the 100 kVA distribution transformers are needed to support communities nearby. However, its inventory management is unpredictable, especially under fluctuating demand and uncertain lead times. Therefore, this study aims to optimize the inventory system that has high stochastic demand. Through Monte Carlo Simulation, this study has proven to address such problems and eventually implement the model. The study shows that the average lead-time demand is 101.76 units, with the 95th percentile value reaching 198 units. Based on these results, the recommended Reorder Point (ROP) is 198 units, with a safety stock of 96.24 units for the 100 kVA transformers inventory. The result of achieved service level is 97.90%, exceeding minimum target of 95%, that is mean model simulation is capable to meeting the required service performance. Model validation using the Kolmogorov-Smirnov Test and Anderson-Darling Test get the p-values greater than 0.05 indicating the model represent the real system. While the QQ Plot result displayed a linear pattern indicating a strong conformity between the simulated distribution and the historical data distribution.