DETERMINATION OF THE ORDER-UP-TO INVENTORY LEVEL AND LOCATION POOLING TO HEDGE OVERSTOCKING IN A DISTRIBUTION NETWORK
In today's economy, the business environment is becoming more and more competitive. One of the ways to gain competitive advantage for companies in the Fast Moving Consuming Goods (FMCG) Industry is to strive for efficiency. PT X is one of the FMCG companies in Indonesia facing the same situa...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/76387 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | In today's economy, the business environment is becoming more and more competitive. One
of the ways to gain competitive advantage for companies in the Fast Moving Consuming
Goods (FMCG) Industry is to strive for efficiency. PT X is one of the FMCG companies in
Indonesia facing the same situation. Supply chain management is one of the ways PT X can
improve their competitiveness, yet they have been having problems of overstocking of goods
in their Distribution Centers (DC). This leads to incurring extra fees that are unfavorable for
PT X. This research aims to introduce PT X to an inventory model, different from their
existing system.
PT X has been experiencing overstocking of inventory in their DCs. A trend chart of the
overstocking for some of their Stock Keeping Units (SKU) show that this is not a random
occurrence. PT X wants to rid the costs that are associated with having this issue. The
research introduces PT X to order-up-to inventory model for their respective DCs. The
model gives erasure to overstocking as there is a somewhat fixed base level compared to PT
X’s existing ever-changing maximum stock threshold. Ordering frequency is also considered
to best suit the economical interest. With PT X’s vast distribution network, modified location
pooling strategies to hedge demand uncertainty is also introduced, and thus the research
proposes a distribution network. Results show that these three methods will be economically
beneficial compared to PT X’s existing system. A sensitivity analysis is also performed for
changes in demand. The DCs with close proximity from the Central DC is more sensitive to
changes as the decision variables show different result based on the parameter.
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