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Chlorine Gas Inventory Model with Exponential Demand and Holt-Winters Forecasting (a) Mathematics Department, Faculty of Mathematics and Natural Sciences, Sriwijaya University, Indralaya, 30662, Indonesia. Abstract Inventory management is very important to Water Supply Company (PDAM) to ensure the consistent availability and reliability of chlorine gas, a crucial chemical required for water treatment and disinfection. This critical function allows company to proactively supervise chlorine gas quantities, maintain quality standards, plan for future needs, and arrange timely deliveries. Consequently, proficient chlorine gas inventory management significantly increases operational efficiency, mitigates the risk of supply shortages, and ensures compliance with government-mandated water quality standards. Therefore, this study aimed to develop a probabilistic Chlorine Gas inventory model, which used the (Q,r) and (R,T) model, with demand following exponential distribution. Demand data used in model were based on forecasts for multiple future periods. The results showed that the most accurate demand forecasting model for Chlorine Gas was achieved through the application of the Multiplicative Exponential Smoothing Winters method, delivering a Mean Absolute Percentage Error (MAPE) of 7, a Mean Absolute Deviation (MAD) of 754, and a Mean Squared Deviation (MSD) of 1,115,038. The optimal inventory management policy, as established by the (R,T) model, prescribed a reorder interval (T) of 0.0061 years or 2.22 days, a maximum stock level (R) of 4,166.267 kg, and a total cost (OT) amounting to IDR 2,673,615,522.833. This model also achieved a service level of 99.98%, signifying an exceptionally high level of service quality. Keywords: Water Supply Company (PDAM), Winters Exponential Smoothing, Exponential probabilistic inventory model Topic: Mathematics and Its Applications |
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