Determination of Multi-Item Inventory Model with Limitations of Warehouse Capacity and Unit Discount in Leading Garment Industry in Indonesia
Author(s) -
Rafly Isfanur Yassa et al. Rafly Isfanur Yassa et al.,
TJPRC
Publication year - 2019
Publication title -
international journal of mechanical and production engineering research and development
Language(s) - English
Resource type - Journals
eISSN - 2249-8001
pISSN - 2249-6890
DOI - 10.24247/ijmperdapr201915
Subject(s) - warehouse , unit (ring theory) , business , industrial organization , operations management , environmental economics , economics , marketing , mathematics , mathematics education
Inventory is important so that the company's produc tion process runs smoothly and efficiently. To main tain the supply of raw materials, it is necessary to have an appropriate inventory control system so that in ventory problems can be minimized. The raw material used is a type of multi-item to produce intimates of apparel is bra. The actual usage data of raw materials during January December 201 7 experienced a stock out of Nylon Tricot, N / S Ela st ne, FS Fiberfill, Mesh SM135 and Spacer. Management of raw material inventories has constraints that is the li mit of warehouse capacity and discount units. This study ai ms to determine the number of economical orders and the frequency of bookings for a year with constraints on warehouse capacity and discount units. The method u sed is EOQ probabilistic multi-item Lagrange Multiplier (LM) and dynamic programming method approaching the Wagne r-Within algorithm. From the two methods then compared to find the most optimal solution in determining the numbe r of orders that are economical. The Wagner-within method produc es a Total Annual Cost (TAC) of Rp. 137,453,491, while Q * was Rp. 187,339,290 and Q * lagrange multiplier of Rp . 135,982,935. The optimal results seen from the TAC of all the minimum raw materials are obtained by the Q * lagran ge multiplier method. With this method Q * lagrange multiplier is recommended for planning multi-item raw material con trol in the company.
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