3rd Australian Conference on Industrial Engineering and Operations Management

AI in Inventory Management

Raghunandan Gurumurthy, Ruchita Pereira & Aricson Pereira
Publisher: IEOM Society International
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Abstract

Inventory management is a key component in any organization; however, tackling it using traditional practices comes with numerous issues like inaccurate demand forecast, a relatively closed system, and lots of room for mistake. However, trend problems provide a radical solution using artificial intelligence (AI). This paper seeks to discover how inventory management has embraced the use of AI and what it wants to do for the traditional systems. This article explains technologies such as Artificial intelligence, Machine learning, NLP, and vision computers are adopted for application in demand sensing, inventory management, warehousing, and real-time visibility of the entire inventory chain is also explained. There are several steps that are followed when AI is being deployed in the inventory management unit, something that include data acquisition and pre-processing, model building and selection, integration, and post implementation mastery. The advancement in AI technology benefits the business through optimization of increased accuracy, decreased expenses, effectiveness of the processes involved, and better customer satisfaction. Thus, the paper aims to capture a broad view of AI application in the typology of inventory management and its promising future in the field.

Keywords: Artificial intelligence, Inventory management, Demand forecasting, Supply chain, Automation

Published in: 3rd Australian Conference on Industrial Engineering and Operations Management, Sydney, Australia

Publisher: IEOM Society International
Date of Conference: September 24-26, 2024

ISBN: 979-8-3507-1738-9
ISSN/E-ISSN: 2169-8767