3rd Asia Pacific International Conference on Industrial Engineering and Operations Management

Analysis of Raw Material Planning with Optimal Cost Consideration Using Safety Stocks, Material Requirement Planning, and Lot Sizing Methods at Plastic Jar Company

Lina Gozali, Dennis Marchello, Ahad Ali & Jessica Jessica
Publisher: IEOM Society International
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Track: Supply Chain and Logisitcs Competition
Abstract

PT. XYZ is a manufacturing company specializing in creating and producing plastic jars. Usually, a company has to plan the requirement of raw resources, including the quantity and delivery timetable of raw materials to meet the
consumer's needs. Henceforth, to determine the consumer's needs, the company must do thorough calculations to find the optimal quantity of required raw materials. In most cases, there's a chance for any company to receive an unexpected request that comes abruptly. As a result, a safety stocks calculation is carried out to prevent the materials from running out. The main problem of PT. XYZ lies in material requirement planning, which is conducted solely using experience estimation. Hence, a new material requirement calculation needs to be performed utilizing Material Requirement Planning (MRP) and Lot Sizing methods to determine the best quantity and proper delivery timetable while considering the most optimal cost of required raw materials. The most optimal method for procurement of raw materials is the method that has the lowest total cost of procurement. According to the result, the best Lot sizing method is the silver Meal method, with a total cost of USD 35.67 which can reduce the total cost of procurement to 50,8%. Thus, MRP is an effective way to reduce the cost of raw material procurement compared to the usual method used in the company

Published in: 3rd Asia Pacific International Conference on Industrial Engineering and Operations Management, Johor Bahru, Malaysia

Publisher: IEOM Society International
Date of Conference: September 13-15, 2022

ISBN: 978-1-7923-9162-0
ISSN/E-ISSN: 2169-8767