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Application of Lot-Sizing Models in Raw Material Supply Control at Amra Furniture Dumai

EasyChair Preprint no. 10768

8 pagesDate: August 24, 2023

Abstract

The Supply of raw materials is an important factor in production activities.This activities. Materials supply requires the company to carry out a planning to determine the supply of raw materials so as not  to hampermaintain the running of production, and reduce the level of costs, and improvetime efficiency of the company. Arma Furniture is a manufacturing company engaginged in the furniture sector. Theis company does has not have a particular raw materials inventory planning, planned the inventory of raw materials so that it has an impacts on the production process. This research usesd the Material Requirements Planning (MRP) method.  which is divided into It utilized three models for the lot-sizing process, namely Lot for Lot (LFL), Economic Order Quantity (EOQ), and Periodic Order Quantity (POQ). The forecasted demand The results of forecasting demand  for wardrobes in the period of June 2021 using have an average weight of MA (4) weight oris 12 units. The most optimal Lot- sizing model to be applied at for Amra Furniture in the period June 2022 is the Lot for Lot (LFL) model, because the total cost of procuring raw materials is Rp 300.031.201. It is lower than the total costs resulting from of the calculation of the Economic Order Quantity (EOQ) and Period Order Quantity (POQ) models, which is equal to Rp 330.320.186 and Rp 338.678.243. In conclusion, to overcome problems in the supply of raw materials at Amra Furniture, it is better to apply the Lot for Lot (LFL) method

Keyphrases: EOQ, LFL, MRP, supply

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:10768,
  author = {S Juni and Wisno Laksana Satria and Alizar Hasan and Feri Afrinaldi},
  title = {Application of Lot-Sizing Models in Raw Material Supply Control at Amra Furniture Dumai},
  howpublished = {EasyChair Preprint no. 10768},

  year = {EasyChair, 2023}}
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