<![CDATA[General Background: Inventory control is a critical operational function to maintain cost efficiency and balance between stockout and overstock conditions in spare parts management. Specific Background: PT XYZ, a port heavy equipment spare parts provider, experienced excessive lubricating oil orders, leading to overstock levels of up to 21.2% and increased total inventory costs. Knowledge Gap: Prior studies on ABC–FSN and min–max stock primarily rely on historical data, resulting in static inventory parameters that insufficiently address future demand fluctuations. Aims: This study aims to control lubricating oil inventory by integrating ABC–FSN classification, min–max stock policy, and time series forecasting to minimize total inventory costs. Results: ABC–FSN analysis identified two Fast-A items, CC-0442 and CC-0444, as priority products. The company’s method generated total inventory costs of Rp 22,195,200, whereas the min–max stock method reduced costs to Rp 16,936,576, yielding savings of Rp 5,258,624 (23.69%). Forecasting for January–December 2026 produced average monthly demands of 2,439 liters for CC-0442 and 1,413 liters for CC-0444, resulting in order quantities of 1,000 liters every 8 days and 600 liters every 9 days, with projected total costs of Rp 15,416,000. Novelty: The integration of ABC–FSN classification with forecasting-based min–max parameters provides a more adaptive inventory control framework. Implications: The proposed approach supports systematic prioritization, cost minimization, and responsive inventory planning for lubricating oil management. Highlights: Fast-A prioritization identified CC-0442 and CC-0444 as critical high-turnover, high-value items. Cost comparison revealed savings of Rp 5,258,624 (23.69%) versus the existing practice. Forecast-based planning established 8-day and 9-day replenishment cycles for 2026. Keywords: ABC-FSN, Forecasting, Inventory Control, Min Max Stock]]>
Copyrights © 2026
