The Proposal of Applying Multi Echelon Inventory to Minimize Supply Chain Total Cost for Soft Drinks Products

Santoso, Santoso and Heryanto, Rainisa Maini (2014) The Proposal of Applying Multi Echelon Inventory to Minimize Supply Chain Total Cost for Soft Drinks Products. In: the 15th Asia Pacific Industrial Engineering and Management System Conference, 12-15 October 2014, Jeju, South Korea.

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Inventory management in a supply chain system was an important factor to be considered. Well managed inventory would have a positive impact to meet demand and especially to minimize supply chain total costs to be incurred by the company. A supply chain usually consists of production and distribution of products between entities that were interconnected with each other. In this study would be discussed how the integration between entities in a supply chain of soft drink products using three echelon concept includes echelon production consists of one plant, echelon distribution center which was spread across in six different areas, and echelon outlet for each distribution center. The model used and could represent the real condition that occurs was a model of Bahagia (1999) which used a heuristic approach to find the optimal solution. There were three flavors of soft drinks which produced by the plant that could be categorized into one product family. Before applying the multi echelon inventory concept, first step was forecasting demand for the future and aggregation process. The integration after aggregation process was the implementation of single cycle policy with the final goal to be achieved were the fulfillment of future demand and minimize supply chain total costs. The supply chain costs included the plant total cost, distribution center total cost, and outlet total cost.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: echelon, supply chain, total cost
Subjects: T Technology > T Technology (General)
Depositing User: Perpustakaan Maranatha
Date Deposited: 27 Jul 2017 02:13
Last Modified: 27 Jul 2017 02:13

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