This research focused on deciding optimal manufacturing WIP (Work-In-Process) limit for a small production system. Reducing WIP leads to stable capacity, better manufacturing flow and decrease inventory. WIP is the one of the important issue, since it can affect manufacturing area, like productivity and line efficiency and bottlenecks in manufacturing process. Several approaches implemented in this research. First, two strategies applied to decide WIP limit. One is roulette wheel selection and the other one is elite strategy. Second, for each strategy, JIT (Just In Time), CONWIP (Constant WIP), Gated Max WIP System and CWIPL (Critical WIP Loops) system applied to find a best material flow mechanism. Therefore, pull control system is preferred to control production line efficiently. In the production line, the WIP limit has been decided based on mathematical models or expert’s decision. However, due to the complexity of the process or increase of the variables, it is difficult to obtain optimal WIP limit. To obtain an optimal WIP limit, GA applied in each material control system. When evaluating the performance of the result, fitness function is used by reflecting WIP parameter. Elite strategy showed better performance than roulette wheel selection when evaluating fitness value. Elite strategy reach to the optimal WIP limit faster than roulette wheel selection and generation time is short. For this reason, this study proposes a fast and reliable method for determining the WIP level by applying genetic algorithm to pull system based production process. This research showed that this method could be applied to a more complex production system.

This study develops a dynamic scheduling model for parallel machine scheduling problem based on genetic algorithm (GA). GA combined with discrete event simulation to minimize the makespan and verifies the effectiveness of the developed model. This research consists of two stages. In the first stage, work sequence will be generated using GA, and the second stage developed work schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlapping work, which causes bottleneck and long lead time. If not, go back to the first stage and develop another schedule until satisfied. Small size problem was experimented and suggested a reasonable schedule within limited resources. As a result of this research, work efficiency is increased, cycle time is decreased, and due date is satisfied within existed resources.

최근 경험경제의 가속화 시대에서, 사용자 경험이 무엇보다 중시되는 대표적인 키워드가 게이미피케이션 연구 분야이다. 게이미피케이션은 제공자와 사용자의 다양한 상호작용으로 무형의 요소가 생산, 소비되는 특성이 있으며, 경제적인 가치로 일반화하고, 객관화하기 어려운 구조로 되어 있다. 본 연구는 사용자에게 경험을 제공하고 가치를 창출하는, 기업의 어떠한 지식, 디자인, 콘텐츠, 서비스 등 무형의 기술에 대한 경제적 가치를 평가하는 견해에서, 게이미피케이션 기술에 대한 경제적 가치를 포괄하는 평가 셈식과 전체 구조를 정형화하는 데 연구의 목적이 있다.