The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

1. 서 론
2. 선행 연구
3. 데이터 기반의 재고정책
    3.1 제조공정
    3.2 분석 절차 및 전제조건
    3.2 안전재고 모델
    3.3 수요예측 모델
4. 시뮬레이션 결과
5. 결 론
References

• Hung-Su Park(스톨베르그 & 삼일 주식회사) | 박흥수
• Woo-Yong Choi(동아대학교 산업경영공학과) | 최우용 Corresponding Author