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.

이 연구는 과거 안전교육 실적, 선원통계연보, 안전교육대상자, 안전교육증서의 유효기간, 선원의 취업률 및 정년퇴직 연령 등의 여러 요소를 고려하여 안전교육대상인원을 예측하고, 선원안전교육 수행 기관의 교육 수용능력을 분석하여 안전교육 수요증대와 집중화 문제를 해소할 수 있는지 분석하였다. 향후 5년간 연평균 안전교육 수요는 선원법 기준으로 약 10,444명으로 예상되며, 현재 안전교육기관이 수용할 수 있는 적정 인원은 연평균 7,280여명으로 조사되었다. 따라서 선원법 개정에 따른 안전교육 수요증대에 효율적으로 대응하기 위해서는 안전교육시설을 확충하여 안전교육 수용능력을 확대할 필요가 있다.

This research fundamentally deals with an analysis of service level for a multi-level inventory distribution system which is consisted of a central distribution center and several branches being supplied stocks from the distribution center, Under continuous review policy, the distribution center places an order for planned order quantity to an outside supplier, and the order quantity is received after a certain lead time. Also, each branch places an order for particular quantity to its distribution center, and receives the order quantity after a lead time. In most practical distribution environment, demands and lead times are generally not fixed or constant, but variable. And these variabilities make the analysis more complicated. Thus, the main objective of this research is to suggest a method to compute the service level at each depot, that is, the distribution center and each branch with variable demands and variable lead times. Further, the model will give an idea to keep the proper level of safety stocks that can attain effective or expected service level for each depot

In this research, the system is assumed to carry a single item of which the demand types vary. Demand type is defined as a management's classification of the item according to the demand source or to the service purpose. The purpose of this research is to find the optimal inventory control policy when the system carries a single item which consists of multiple demand types. In this research, the optimizing algorithm contains a heuristic, therefore, the optimal Is not guaranteed by the algorithm. At least, this research provides the solution to the problems that have not been solved by the existing algorithms.

In this research, the system is assumed to carry a single item of which the demand types vary. Demand type is defined as a management's classification of the item according to the demand source or to the service purpose. The purpose of this research is to find the optimal inventory control policy when the system carries a single item which consists of multiple demand types. In this research, the optimizing algorithm contains a heuristic, therefore, the optimal is not guaranteed by the algorithm. At least, this research provides the solution to the problems that have not been solved by the existing algorithms.