REVERSE LOGISTICS USING DEVELOPMENT OF EOQ-REVERSE AND EPQ MULTI PRODUCT METHODS ON THE STEEL PRODUCTION FLOOR

Material procurement in this research is carried out by the EOQ-reverse method, while the production process is managed by a multi product EPQ model, where in the production process of a product there will generally be several types of products produced. The purpose of this research is to obtain the...

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主要作者: Demupa, Lilia
格式: Theses
語言:Indonesia
在線閱讀:https://digilib.itb.ac.id/gdl/view/47207
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機構: Institut Teknologi Bandung
語言: Indonesia
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總結:Material procurement in this research is carried out by the EOQ-reverse method, while the production process is managed by a multi product EPQ model, where in the production process of a product there will generally be several types of products produced. The purpose of this research is to obtain the minimum cost of the planned system through modification of the EOQ model with the development of reverse logistics and combining the EOQ-reverse model with the EPQ model. In this study, there are three sensitivity parameters in the EOQ-reverse model, namely the setup cost of a reverse product, the purchase price of a reverse item, and level collectivity of reverse raw material. While in the EPQ model there are no sensitivity parameters. The results of this study are minimum costs based on some changes in parameters and the most optimal level of product inventory based on consideration of aspects of new and reverse product parameters. Based on research that has been done, it is found that changes in the value of demand and the purchase price of reverse goods that inpr ease enough to affect changes in the inpr ease in the value of the level of inventory of raw materials depr eases. While the changes in the value of setup cost does not significantly affect the change in the decision variables sought. The optimal minimum cost value obtained is then tested again by changing the sensitivity parameter on the demand for new goods, the cost of setup of new raw materials, and the purchase price of new goods. Sensitivity analysis results show that changes in demand for new goods and the purchase price of new goods affect changes in the decision variable. While changes from the cost of setting up new raw materials do not significantly affect changes in decision variables.