Forecast-Driven Spare-Parts Inventory Control in Coal-Mining Operations: An Integrated Operational–Financial Framework
DOI:
https://doi.org/10.38035/dijefa.v7i2.6858Keywords:
Critical Spare Parts, Demand Forecasting, Economic Order Quantity, Reorder Point, Safety StockAbstract
Coal-mining contractors face challenges in maintaining equipment availability while controlling spare-parts inventory costs. This study examines how PT Geobara Energy, a coal-mining contractor in Muara Enim, South Sumatra, can reduce critical spare-parts stockout exposure through an integrated forecasting and continuous-review inventory policy. Using operational and inventory data from 2023–2025, the study applies ABC classification, demand-pattern screening, item-specific forecasting selection, and EOQ–ROP–Safety Stock analysis. The results show that only 11 of 16 high-value spare parts were suitable for quantitative forecasting. Simpler forecasting methods, particularly Single Exponential Smoothing and Trend Analysis, outperformed complex seasonal models. The proposed EOQ-based policy reduced annual inventory cost from Rp124,291,519 to Rp49,375,014, representing a 60.3% reduction while maintaining replenishment protection for critical spare parts. The findings suggest that spare-parts inventory control should be managed as an integrated operational–financial governance system rather than merely as a warehouse activity.
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