4th Indian International Conference on Industrial Engineering and Operations Management

Inventory Management of Spare Parts in the Ready-to-Eat Food Manufacturing Industry.

tapanut sudjai
Publisher: IEOM Society International
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Abstract

This research examines inventory management of machine spare parts in the prepared food manufacturing industry. The objective is to determine the optimal order quantity for a case study company and compare costs before and after analyzing the appropriate order quantity using the Silver-Meal Heuristic. Based on theoretical studies and detailed data from the case study company, which specializes in manufacturing and importing food industry machinery along with after-sales services, the complexity of inventory management becomes apparent. The case study company faces high inventory management costs, primarily due to a lack of effective ordering tools and reliance on employee expertise for ordering processes. To identify the optimal order quantities, an analysis was conducted using ABC Analysis and FSN Analysis, resulting in a Matrix Analysis that categorized products into nine groups. Groups AF, AN, and AS, comprising 44, 164, and 278 items respectively, represent the highest value products, totaling $715,878.33 per year, which accounts for 80% of the total inventory value. Further analysis of variance coefficients showed that these groups had a relatively stable variance, with only 13 items having a variance less than 0.25 and 172 items exceeding this threshold. The results indicate that inventory costs before applying the Silver-Meal technique amounted to $152,804.03 per year. After implementation, the costs decreased to $97,994.70 per year, demonstrating a reduction of $54,809.32 annually. Thus, the application of the Silver-Meal technique significantly improved inventory cost efficiency.

Published in: 4th Indian International Conference on Industrial Engineering and Operations Management, Hyderabad, India

Publisher: IEOM Society International
Date of Conference: November 7-9, 2024

ISBN: 979-8-3507-1739-6
ISSN/E-ISSN: 2169-8767