Optimization of Inventory Control Using Economic Order Quantity and Safety Stock Approach

Dwi Putra Saputra; Devira Kusuma Wardhani; Michael F. Passon

doi:10.70716/reswara.v2i3.378

Authors

Dwi Putra Saputra Department of Industrial Engineering, Universitas Brawijaya, Malang, Indonesia Author
Devira Kusuma Wardhani Department of Management, Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia Author
Michael F. Passon Department of Logistics and Supply Chain Management, Technical University of Munich, Munich, Germany Author

DOI:

https://doi.org/10.70716/reswara.v2i3.378

Keywords:

economic order quantity, safety stock, inventory control, reorder point, cost optimization

Abstract

Effective inventory control plays a crucial role in ensuring operational efficiency and cost minimization, particularly in manufacturing, retail, and small–medium enterprises. Inefficient inventory policies often lead to excessive holding costs, frequent stockouts, and unstable production schedules. This study aims to optimize inventory control by integrating the Economic Order Quantity (EOQ) model with safety stock and reorder point approaches. The research adopts a quantitative descriptive design using secondary operational data derived from empirical case studies and prior applications in manufacturing firms, retail businesses, and small enterprises. Inventory parameters such as demand rate, ordering cost, holding cost, lead time, and service level were analyzed using EOQ-based mathematical formulations. The results demonstrate that the integrated EOQ and safety stock model significantly reduces total inventory costs while improving service levels and minimizing stockout risks. Comparative analysis with previous studies indicates consistency with earlier findings across different sectors, confirming the robustness of the model. The study contributes theoretically by consolidating deterministic and probabilistic EOQ perspectives and practically by providing a structured decision-making framework for inventory managers. The findings support the applicability of EOQ-based optimization as a cost-efficient and scalable inventory control strategy suitable for diverse industrial contexts.

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