@inproceedings{d425889662f74383b65c33556db6a7c9,
title = "Raw Material Inventory Optimization with Long Leadtime",
abstract = "Inventory management is an essential component in supporting production. Factories must implement inventory control to achieve the desired productivity. Material shortages disturb production, while material excess makes spending soar. To prevent these problems, this study aims to analyze raw material requirements and inventory control management at a factory. This paper compares the classic economic order quantity (EOQ) model and Monte Carlo simulation and optimization considering random elements. The order quantity and the reorder point will be obtained using both methods. The results show that the Monte Carlo simulation produces lower inventory costs.",
keywords = "Cost Inventory, EOQ, Inventory Control, Inventory Management, Long lead time Material, Monte Carlo simulation, Shortage",
author = "Nabilah Febriani and Komarudin",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 7th International Conference on Business and Industrial Research, ICBIR 2022 ; Conference date: 19-05-2022 Through 20-05-2022",
year = "2022",
doi = "10.1109/ICBIR54589.2022.9786476",
language = "English",
series = "ICBIR 2022 - 2022 7th International Conference on Business and Industrial Research, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "523--526",
booktitle = "ICBIR 2022 - 2022 7th International Conference on Business and Industrial Research, Proceedings",
address = "United States",
}