생산스케줄 변동대비 자동차배송모형 시뮬레이션 (A Simulation of Automobile Distribution Model against Production Schedule Variance)

서지정보

· 발행기관 : 한국로지스틱스학회
· 수록지 정보 : 로지스틱스연구 / 21권 / 4호 / 19 ~ 33페이지
· 저자명 : 김영대, 문성암, 김태현

초록

본 연구는 경영환경의 불확실성 요소 중에서 자동차제조회사의 생산스케줄 변동에 초점을 두고, 생산스케줄이 변경되었을 때, 이에 대한 조정의 역할을 하는 (1)직접배송모형과 (2)공동배송모형을 시뮬레이션 실험을 통해 비교분석한다. 직접배송모형과 공동배송모형의 재고수준과 품절수준을 비교하여 제조업체의 생산스케줄변동수준에 따라 공급사슬네트워크설정이 성과변수에 어떤 영향을 미치는지를 분석하고자 한다.
직접배송모형과 공동배송모형의 비교분석 결과, 생산스케줄변동수준에 따라 재고성과와 품절성과는 다르게 나타났다. 스케줄변동이 없었을 때, 품절수준에서는 두 모형간의 차이가 없었으며, 재고수준은 공동배송모형이 더 적게 나타났다. 그러나 스케줄변동수준이 증가함에 따라 재고수준과 품절수준은 직접배송모형과 공동배송모형 모두 증가하는 것으로 나타났으나, 재고수준과 품절수준에서 두 모형간의 성과의 차이가 다르게 나타났다. 모형간의 성과의 차이를 보면, 재고수준의 성과차이가 비례적으로 증가하는 것이 아닌 30%의 변동수준까지는 스케줄변동수준이 증가함에 따라 로케이션풀링효과에 의해 재고수준의 효과가 더 증가되는 것으로 나타났지만, 40% 이상의 변동수준에서는 로케이션풀링효과가 줄어드는 것으로 나타났다. 품절수준의 경우는 스케줄변동수준이 증가함에 따라 두 모형의 성과의 차이가 더 크게 나타났다. 결과적으로, 생산스케줄 변동수준이 증가할수록 공동배송모형이 직접배송모형보다 재고수준과 품절수준에서 더 우수한 결과를 나타냈지만, 그 성과의 차이가 비례적으로 증가하는 것이 아닌 일정수준까지 증가하다가 성과의 차이가 감소하는 것으로 나타났다. 그것은 버퍼로서의 리드타임 및 로케이션풀링의 한계로 볼 수 있다.
본 연구의 시사점은 스케줄변동수준에 따른 공급사슬네트워크조정은 달라져야 하며, 버퍼로서 공동배송모형을 통한 리드타임 및 로케이션풀링효과도 그 한계가 존재하며, 그 한계를 벗어났을 때, 공급사슬의 성과 향상을 위한 네트워크의 조정이 필요하다는 것을 의미한다.

영어초록

This study focuses on the variations in production schedules among the elements of uncertainty in a business environment, and conducts a comparative analysis on the Coordination role of distribution centers when there is a variation in Automaker’s production schedule through simulation tests under a direct-delivery model and a consolidated-delivery model. Further, the study attempts to analyze what kind of effects the supply chain network design based on variations in the production schedule of a manufacturing company has on the result variables by comparing the inventory levels and out-of-stock levels of a direct-delivery model and a consolidated-delivery model.
As a result of the comparative analysis of a direct-delivery model and a consolidated-delivery model, the inventory levels and out-of-stock levels differed depending on the fluctuation level of the production schedules. When there were no variations in the schedules, there were no differences between the models in terms of the out-of-stock levels and the level of inventory was found to be lower in the consolidated-delivery model. On the other hand, as the fluctuation levels in the production schedules increased, the inventory levels and out-of-stock levels all appeared to increase in both the direct-delivery model and the consolidated-delivery models. However, there were differences between the results from the two models in terms of inventory levels and out-of-stock levels. In examining the differences between the results from the two models, although it appeared that the effects of the increase in inventory levels further increased due to the effects of location pooling as the difference between results in inventory levels in increased in relation to the fluctuation levels in schedule up to 30% of the fluctuation levels rather than increase in proportion, it was found that the effects of location pooling decreased when fluctuation levels were at 40% or more. In the case of out-of-stock levels, the differences between the results from the two models were greater as the fluctuation levels in the schedules increased. Consequently, the more the fluctuation levels in production schedules increased, the consolidated-delivery model resulted in better results than the direct-delivery model with respect to inventory levels and out-of-stock levels. However, it was found that the difference in such results did not increase proportionately and only increased up to a certain level and then decreased. Such findings may be viewed as limitations for lead time and location pooling to be used as a buffering mechanism.
The results of this study implicates that the supply chain network coordination depending upon the variation levels of schedules should be changed and there exists limitations to the effects of lead time and location pooling as a buffering mechanism based on the consolidated-delivery model. This means that, when such limitations are removed, there will be a need to coordinate the network to improve the results in the supply chain.

참고자료

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