#TITLE_ALTERNATIVE#

• Main Author: DWINANTO (NIM: 13403062) Prof. Dr. Ir. Bermawi P. Iskandar, ARIYA
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/19922
• Institution: Institut Teknologi Bandung

This final project is carried out at the finished product warehouse in PT.TOA-Galva Industries. The factory produces equipment related with the audio-system as example megaphone, speaker and amplifier, which have a total of 535 kind of product. These products are ordered by costumers from overseas as well as costumers in the country. One costumer usually orders many list of product that contains more than one kind of product with a variation in amount. The range of time that a worker spends on searching a SKU (Stock-keeping unit) depends on the SKU density in a warehouse and depends on the storage assignment policy used. The smaller the SKU density will affect the range of time that a worker spending on searching SKU will become much bigger. Based on the earlier observation, the finished product warehouse has a 0.463 item / m2 SKU density. The low SKU density is caused by the random storage assignment policy which is currently used. So that worker has the tendency to put SKU at the nearest available pallet allocation. The limit of the warehouse capacity, the demand that keeps increasing, and a few SKU that are delayed on shipping causing the worker putting SKU at allocation that is not supposed to be put at. Sometimes, pallet is allocated at the material handling aisle which makes problems at transportation. From those problems, this final project is aimed to determine the capacity of the warehouse and to suggest a new storage assignment policy which will increase the SKU density performance. This final project is based on five steps, which is (1) determining the present average SKU density, (2) calculating how much capacity will this warehouse need, (3) generating a better storage assignment policy, (3) the fulfillment of the new storage assignment policy assumption, the making of convenient location mapping, (4) the design of warehouse layout from the clustering view, and (5) determining the betterment average SKU density. There are four alternatives generated and will be evaluated. To select the best alternative will be based on the average SKU density performance. Alternative Ochiai with 4 clusters is the best alternative among the others.