<![CDATA[General Background Ineffective control of raw material inventories can significantly increase operational costs for manufacturing companies. Specific Background This study analyzes the control of 10-20 broken stone raw materials at PT. XYZ using the Economic Order Quantity (EOQ) method combined with linear regression forecasting. Knowledge Gap Existing inventory management lacks optimal order structuring, leading to suboptimal purchasing frequencies and elevated inventory expenses. Aims This study aims to determine the economical order quantity and evaluate cost efficiency improvements for raw material inventories. Results Findings indicate an annual raw material requirement of 37,883 tons, an optimal order quantity of 763 tons per order with a purchase frequency of 50 times per year, and a total inventory cost reduction from Rp181.200.563 to Rp25.084.238. Novelty This work establishes an integrated probabilistic EOQ and linear regression framework tailored for ready-mix concrete aggregate supply chain management. Implications Implementing the EOQ model successfully improves inventory management efficiency, achieving an 86.23% cost saving. KEY FINDINGS HIGHLIGHTS Applying the Economic Order Quantity model reduces total inventory costs from Rp181.200.563 to Rp25.084.238. The optimal order quantity is determined at 763 tons per order with a purchasing frequency of 50 times annually. The proposed inventory control approach successfully achieves an impressive cost efficiency savings of 86.23%. Keywords Raw Material Inventory, Eoq, Inventory Control, Cost Efficiency]]>
Copyrights © 2026
