Revolutionizing Inventory Management: The Role of Data Mining in Industry 4.0

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.

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Publication Details

Journal
Advances in Economics Management and Political Sciences
Published
2024-10-12
DOI
https://doi.org/10.54254/2754-1169/109/2024bj0121
Citations
2
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.70
Controls
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article

Revolutionizing Inventory Management: The Role of Data Mining in Industry 4.0

Xiangming Zhan, Zehao Huo
2 citations
Advances in Economics Management and Political Sciences
Digital Transformation in Industry
0.70
article

Revolutionizing Inventory Management: The Role of Data Mining in Industry 4.0

Xiangming Zhan, Zehao Huo
article en
2 citations

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.

Advances in Economics Management and Political SciencesVol. 109(1)
James Cook University Singapore (SG), Chongqing University of Arts and Sciences (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Digital Transformation in Industry
0.70
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