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Revolutionizing Inventory Management: The Role of Data Mining in Industry 4.0
- 1 James Cook University, Singapore, Singapore, 387380
- 2 School of Mathematics and Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing, China, 402160
* Author to whom correspondence should be addressed.
Abstract
In the era of Industry 4.0, with the rapid development and application of technologies such as the Internet of Things (IoT), Big Data and Artificial Intelligence (AI), the manufacturing industry is undergoing unprecedented changes. In this context, data mining technology has become integral to inventory management practices in all industries. This study examines the profound impact of data mining on inventory management efficiency. By leveraging advanced analytics and machine learning algorithms, data mining enables organizations to accurately forecast demand, optimize inventory levels, and improve supply chain transparency. Through real-world case studies and comprehensive analysis, this research highlights how data mining techniques, such as central object-based clustering algorithms, can be successfully applied to optimize material classification, warehouse space utilization and operational efficiency. In addition, this study explores the broader applications of data mining beyond inventory management, including marketing, financial risk management, healthcare, transportation, social media, and cybersecurity. Overall, this study provides valuable insights into how data mining can reshape inventory management practices and drive business growth in the digital age.
Keywords
Industry 4.0, Data mining, Algorithms, Inventory management
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Cite this article
Huo,Z.;Zhan,X. (2024). Revolutionizing Inventory Management: The Role of Data Mining in Industry 4.0. Advances in Economics, Management and Political Sciences,109,67-72.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of ICEMGD 2024 Workshop: Innovative Strategies in Microeconomic Business Management
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