Kota, Akhilesh (2025) Building an intelligent inventory optimization system: A technical overview. International Journal of Science and Research Archive, 14 (1). pp. 694-702. ISSN 2582-8185
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Abstract
This technical article presents a detailed examination of an Intelligent Inventory Optimization System built using machine learning models, Spring Boot, and Apache Kafka. The system addresses modern inventory management challenges through a sophisticated architecture comprising data ingestion, processing, machine learning, and control layers. The implementation significantly improves operational efficiency, cost reduction, and customer satisfaction through real-time data processing and predictive analytics. The article explores comprehensive security measures, scalability features, and fault tolerance mechanisms while providing a detailed performance optimization analysis through advanced caching and batch processing strategies. The system's impact extends across multiple dimensions of business operations, from supply chain optimization to warehouse management, showcasing the transformative potential of AI-driven inventory management solutions in modern enterprise. environments
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/ijsra.2025.14.1.0060 |
Uncontrolled Keywords: | Inventory Optimization; Machine Learning Integration; Supply Chain Management; Real-time Processing; Performance Analytics |
Depositing User: | Editor IJSRA |
Date Deposited: | 13 Jul 2025 14:20 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/629 |