<![CDATA[This study develops an optimized inventory control policy for pipe products characterized by intermittent demand in a manufacturing company in Surabaya. Monthly demand data from January to December 2024 were analyzed using the Average Demand Interval (ADI) and the Coefficient of Variation Squared (CV²) to classify demand behavior. The results indicate an ADI of 2.6 and a CV² of 0.82, confirming a lumpy intermittent demand pattern. Based on this classification, inventory parameters were determined for a 15-day lead time. The proposed policy yields a safety stock of 18 units and a reorder point of 25 units at a 95% service level. Implementation of the integrated forecasting–inventory approach reduces annual inventory costs by 21.7% and improves material availability from 89% to 95%. Findings demonstrate that demand classification-based inventory decisions provide measurable operational and economic improvements for project-oriented manufacturing environments.]]>
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