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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.